AR5: Impacts, Adaptation, and Vulnerability (PART A)

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Chapter 
13: Livelihoods and Poverty

AR5: Impacts, Adaptation, and Vulnerability (PART A)

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Chapter 13: Livelihoods and Poverty

FAQ 13.1 | What are multiple stressors and how do they intersect with inequalities to influence livelihood trajectories?:

This is particularly the case for livelihoods and households that have limited asset flexibility and/or those that experience disadvantages and marginalization due to gender, age, class,race, (dis)ability, or being part of a particular indigenous or ethnic group. Weather events and climate compound these stressors, allowing some to benefit and enhance their well-being while others experience severe shocks and may slide into chronic poverty. Who is affected, how, where, and for how long depends on local contexts. For example, in the Humla district in Nepal, gender roles and caste relations influence livelihood trajectories in the face of multiple stressors including shifts in the monsoon season (climatic), limited road linkages (socioeconomic), and high elevation (environmental). Women from low castes have adapted their livelihoods by seeking more daylabor employment, whereas men from low castes ventured into trading on the Nepal-China border, previously an exclusively upper caste livelihood.

13.2. Assessment of Climate Change Impacts on Livelihoods and Poverty

13.2.1. Evidence of Observed Climate Change Impacts on Livelihoods and Poverty

13.2.1.5. Multidimensional Inequality and Vulnerability

Mounting inequality is not just a side effect of weather and climate but of the interaction of related impacts with multiple deprivations at the context-specific intersections of gender, age, race,class,caste, indigeneity, and (dis)ability, embedded in uneven power structures, also known as intersectionality (Nightingale, 2011; Kaijser and Kronsell, 2013;see Figure 13-5). This section illustrates how climate impacts intersect with inequality, primarily along the lines of gender, age, and indigeneity. Other chapters are referenced.

Box 13-1 | Climate and Gender Inequality: Complex and Intersecting Power Relations:

Existing gender inequality (see Box CC-GC) is increased or heightened as a result of weather events and climate-related disasters intertwined with socioeconomic, institutional,cultural, and political drivers that perpetuate differential vulnerabilities (robust evidence; Lambrou and Paina, 2006; Adger et al., 2007; Brouwer et al., 2007; Shackleton et al., 2007; Carr, 2008; Demetriades and Esplen, 2008; Galaz et al., 2008; Osbahr et al., 2008; Buechler, 2009; Nightingale, 2009; Terry, 2009; Dankelman, 2010; MacGregor, 2010; Alston, 2011; Arora-Jonsson, 2011; Resurreccion, 2011; Heckenberg and Johnston, 2012; Zotti et al., 2012; Alston and Whittenbury, 2013; Rahman, 2013; Shah et al., 2013).While earlier studies have tended to highlight women’s quasi-universal vulnerability in the context of climate change (e.g., Denton, 2002), this focus can ignore the complex, dynamic, and intersecting power relations and other structural and place-based causes of inequality (Nightingale, 2009; UNFPA, 2009; Arora-Jonsson, 2011). Moreover, the construction of economically poor women as victims denies women’s agency and emphasizes their vulnerability as their intrinsic problem (MacGregor, 2010; Manzo, 2010; Arora-Jonsson, 2011).

Gendered livelihood impacts: Men and women are differentially affected by climate variability and change. The 10-year drought in Australia’s Murray-Darling Basin differentially affected men and women, owing to their distinct roles within agriculture (e.g., Eriksen et al., 2010). Alston (2011) noted social disruption and depression, most profound in areas with almost total reliance on agriculture, no substitute employment, and limited service infrastructure (Table 13-1). In India, more women than men, especially women of lower castes, work as wage laborers to compensate for crop losses (Lambrou and Nelson, 2013) while in Tanzania, wealthier women hire poorer women to collect animal fodder during droughts (Muthoni and Wangui, 2013). Climate variability amplifies food shortages in which women consume less food (Lambrou and Nelson, 2013) and suffer from reproductive tract infections and water-borne diseases after floods (Neelormi et al., 2008; Campbell et al., 2009). Women farmers in the Philippines relying on high-interest loans were sent to jail after defaulting on debts following crop failure (Peralta, 2008). In Uganda, men were able to amass land after floods while droughts reduced women’s non-land assets (Quisumbing et al., 2011). In Ghana, some husbands prevent their wives from cultivating individual plots as a response to gradually shifting rainfall seasonality, thereby undermining both women’s agency and household well-being (Carr, 2008).

Feminization of responsibilities: Campbell et al. (2009) and Resurreccion (2011), in case studies from Vietnam, found increased workloads for both partners linked to weather events and climate, contingent on socially accepted gender roles: men tended to work longer hours during extreme events and women adopted extra responsibilities during disaster preparation and recovery (e.g., storing food and water and taking care of the children, the sick, and the elderly) and when their husbands migrated. In Cambodia, Khmer men and women accepted culturally taboo income-generating activities under duress, when rice cropping patterns shifted due to higher temperatures and more irregular rainfall (Resurreccion, 2011). Despite increased workloads for both sexes, women’s extra work adds to already many labor and caring duties (Nelson and Stathers, 2009; MacGregor, 2010; Petrie, 2010; Arora-Jonsson, 2011; Kakota et al., 2011; Resurreccion, 2011; Muthoni and Wangui, 2013; Shah et al., 2013). In Nepal, shifts in the monsoon season, longer dry periods, and decreased snowfall push Dalit girls and women (“untouchable” caste) to grow drought-resistant buckwheat and offer more day labor to the high caste Lama landlords while Dalit men seek previously taboo patronage protection to engage in cross-border trade (Onta and Resurreccion, 2011). Rising male out-migration, for example, in Niger and South Africa, leave women with all agricultural tasks yet limited extra labor (Goh, 2012). Additional workloads exhaust women emotionally and physically, shown in South Africa (Babugura, 2010).

Emotional and psychological distress: Climate-related disasters or gradual environmental deterioration can affect women’s mental health disproportionally due to their multiple social roles (UN ECLAC, 2005; Babugura, 2010; Boetto and McKinnon, 2013; Hargreaves, 2013). Increased gender-based violence within households is reported as an indirect social consequence of climate-related disasters, as well as slow-onset climate events, owing to greater stress and tension, loss and grief, and disrupted safety nets, reported for Australia (Anderson, 2009; Alston, 2011; Parkinson et al., 2011; Hazeleger, 2013;Whittenbury, 2013), New Zealand (Houghton, 2009), the USA (Jenkins and Phillips, 2008; Anastario et al., 2009), Vietnam (Campbell et al., 2009), and Bangladesh (Pouliotte et al., 2009).

Mortality: Social conditioning affects mortality for women and men. Rahman (2013) and Nellemann et al. (2011) confirm patterns of gender disparity with respect to swimming that contribute to high number of female deaths due to climate-related disasters. Restricted mobility keeps women in Bangladesh and Nicaragua waiting in risk-prone houses during floods (Saito, 2009; Bradshaw, 2010). Some disaster relief structures that lack facilities appropriate for women may contribute to increased harm and mortality (World Bank, 2010).When they are socioeconomically disadvantaged and the disasters exacerbate existing patterns of discrimination, more women die in hurricanes and floods (Neumayer and Plümper, 2007; Ray-Bennett, 2009). Yet, men experience a higher mortality rate when fulfilling culturally imposed roles as heroic life-savers (Röhr, 2006; Campbell et al., 2009; Resurreccion, 2011).

13.3. Assessment of Impacts of Climate Change Responses on Livelihoods and Poverty

13.3.1. Impacts of Mitigation Responses

13.3.1.2. Reduction of Emissions from Deforestation and Forest Degradation

Benefit flows may be unevenly distributed with regards to ethnicity (Krause and Loft, 2013), gender (Peach Brown, 2011; UN-REDD, 2011), or simply not target the poor (Hett et al., 2012). The absence of a global REDD+ mechanism means that progress on REDD+ may occur as much through voluntary bilateral and public-private processes as through multilateral, regulatory requirements (Agrawal et al., 2011). Positive future benefits for poor people from REDD+ will require attention to tenure and property rights, gender interests, and community engagement (Danielsen et al., 2011;Mustalahti et al., 2012).

13.3.1.4. Biofuel Production and Large-Scale Land Acquisitions:

LSLA have also triggered a land rush in LICs, which affects livelihood choices and outcomes,with some distinct gender dimensions (Chu, 2011; De Schutter, 2011;Julia and White, 2012; Peters, 2013). (...) There is growing apprehension that increased competition for scarce land undermines women’s access to land and their ability to benefit economically from biofuel investment (Arndt et al., 2011; Chu, 2011; Molony, 2011; Behrman et al., 2012; Julia and White, 2012; Perch et al., 2012). 

13.3.2. Impacts of Adaptation Responses on Poverty and Livelihoods

13.3.2.1. Impacts of Adaptation Responses on Livelihoods and Poverty

National Action Plans of Adaptation tend to overemphasize technological and infrastructural measures while often overlooking poor people’s needs, gender issues, and livelihood and adaptation strategies (Agrawal and Perrin, 2009; Perch, 2011)

Elaborated language

Chapter 13: Livelihoods and Poverty

FAQ 13.1 | What are multiple stressors and how do they intersect with inequalities to influence livelihood trajectories?:

Multiple stressors are simultaneous or subsequent conditions or events that provoke/require changes in livelihoods. Stressors include climatic (e.g., shifts in seasons), socioeconomic (e.g., market volatility), and environmental (e.g., destruction of forest) factors, that interact and reinforce each other across space and time to affect livelihood opportunities and decision making (see Figure 13-1). Stressors that originate at the macro level include climate change, globalization, and technological change. At the regional, national, and local levels, institutional context and policies shape possibilities and pitfalls for lessening the effects of these stressors. Which specific stressors ultimately result in shocks for particular livelihoods and households is often mediated by institutions that connect the local level to higher levels. Moreover, inequalities in low-, medium-, and high-income countries often amplify the effects of these stressors. This is particularly the case for livelihoods and households that have limited asset flexibility and/or those that experience disadvantages and marginalization due to gender, age, class,race, (dis)ability, or being part of a particular indigenous or ethnic group. Weather events and climate compound these stressors, allowing some to benefit and enhance their well-being while others experience severe shocks and may slide into chronic poverty. Who is affected, how, where, and for how long depends on local contexts. For example, in the Humla district in Nepal, gender roles and caste relations influence livelihood trajectories in the face of multiple stressors including shifts in the monsoon season (climatic), limited road linkages (socioeconomic), and high elevation (environmental). Women from low castes have adapted their livelihoods by seeking more daylabor employment, whereas men from low castes ventured into trading on the Nepal-China border, previously an exclusively upper caste livelihood.

13.2. Assessment of Climate Change Impacts on Livelihoods and Poverty

[...]

13.2.1. Evidence of Observed Climate Change Impacts on Livelihoods and Poverty

[...]

13.2.1.5. Multidimensional Inequality and Vulnerability

Climate variability and change as well as climate-related disasters contribute to and exacerbate inequality, in urban and rural areas, in LICs, MICs, and HICs. Mounting inequality is not just a side effect of weather and climate but of the interaction of related impacts with multiple deprivations at the context-specific intersections of gender, age, race,class,caste, indigeneity, and (dis)ability, embedded in uneven power structures, also known as intersectionality (Nightingale, 2011; Kaijser and Kronsell, 2013;see Figure 13-5). This section illustrates how climate impacts intersect with inequality, primarily along the lines of gender, age, and indigeneity. Other chapters are referenced.

Box 13-1 | Climate and Gender Inequality: Complex and Intersecting Power Relations:

Existing gender inequality (see Box CC-GC) is increased or heightened as a result of weather events and climate-related disasters intertwined with socioeconomic, institutional,cultural, and political drivers that perpetuate differential vulnerabilities (robust evidence; Lambrou and Paina, 2006; Adger et al., 2007; Brouwer et al., 2007; Shackleton et al., 2007; Carr, 2008; Demetriades and Esplen, 2008; Galaz et al., 2008; Osbahr et al., 2008; Buechler, 2009; Nightingale, 2009; Terry, 2009; Dankelman, 2010; MacGregor, 2010; Alston, 2011; Arora-Jonsson, 2011; Resurreccion, 2011; Heckenberg and Johnston, 2012; Zotti et al., 2012; Alston and Whittenbury, 2013; Rahman, 2013; Shah et al., 2013).While earlier studies have tended to highlight women’s quasi-universal vulnerability in the context of climate change (e.g., Denton, 2002), this focus can ignore the complex, dynamic, and intersecting power relations and other structural and place-based causes of inequality (Nightingale, 2009; UNFPA, 2009; Arora-Jonsson, 2011). Moreover, the construction of economically poor women as victims denies women’s agency and emphasizes their vulnerability as their intrinsic problem (MacGregor, 2010; Manzo, 2010; Arora-Jonsson, 2011).

Gendered livelihood impacts: Men and women are differentially affected by climate variability and change. The 10-year drought in Australia’s Murray-Darling Basin differentially affected men and women, owing to their distinct roles within agriculture (e.g., Eriksen et al., 2010). Alston (2011) noted social disruption and depression, most profound in areas with almost total reliance on agriculture, no substitute employment, and limited service infrastructure (Table 13-1). In India, more women than men, especially women of lower castes, work as wage laborers to compensate for crop losses (Lambrou and Nelson, 2013) while in Tanzania, wealthier women hire poorer women to collect animal fodder during droughts (Muthoni and Wangui, 2013). Climate variability amplifies food shortages in which women consume less food (Lambrou and Nelson, 2013) and suffer from reproductive tract infections and water-borne diseases after floods (Neelormi et al., 2008; Campbell et al., 2009). Women farmers in the Philippines relying on high-interest loans were sent to jail after defaulting on debts following crop failure (Peralta, 2008). In Uganda, men were able to amass land after floods while droughts reduced women’s non-land assets (Quisumbing et al., 2011). In Ghana, some husbands prevent their wives from cultivating individual plots as a response to gradually shifting rainfall seasonality, thereby undermining both women’s agency and household well-being (Carr, 2008).

Feminization of responsibilities: Campbell et al. (2009) and Resurreccion (2011), in case studies from Vietnam, found increased workloads for both partners linked to weather events and climate, contingent on socially accepted gender roles: men tended to work longer hours during extreme events and women adopted extra responsibilities during disaster preparation and recovery (e.g., storing food and water and taking care of the children, the sick, and the elderly) and when their husbands migrated. In Cambodia, Khmer men and women accepted culturally taboo income-generating activities under duress, when rice cropping patterns shifted due to higher temperatures and more irregular rainfall (Resurreccion, 2011). Despite increased workloads for both sexes, women’s extra work adds to already many labor and caring duties (Nelson and Stathers, 2009; MacGregor, 2010; Petrie, 2010; Arora-Jonsson, 2011; Kakota et al., 2011; Resurreccion, 2011; Muthoni and Wangui, 2013; Shah et al., 2013). In Nepal, shifts in the monsoon season, longer dry periods, and decreased snowfall push Dalit girls and women (“untouchable” caste) to grow drought-resistant buckwheat and offer more day labor to the high caste Lama landlords while Dalit men seek previously taboo patronage protection to engage in cross-border trade (Onta and Resurreccion, 2011). Rising male out-migration, for example, in Niger and South Africa, leave women with all agricultural tasks yet limited extra labor (Goh, 2012). Additional workloads exhaust women emotionally and physically, shown in South Africa (Babugura, 2010).

[...]

Emotional and psychological distress: Climate-related disasters or gradual environmental deterioration can affect women’s mental health disproportionally due to their multiple social roles (UN ECLAC, 2005; Babugura, 2010; Boetto and McKinnon, 2013; Hargreaves, 2013). Increased gender-based violence within households is reported as an indirect social consequence of climate-related disasters, as well as slow-onset climate events, owing to greater stress and tension, loss and grief, and disrupted safety nets, reported for Australia (Anderson, 2009; Alston, 2011; Parkinson et al., 2011; Hazeleger, 2013;Whittenbury, 2013), New Zealand (Houghton, 2009), the USA (Jenkins and Phillips, 2008; Anastario et al., 2009), Vietnam (Campbell et al., 2009), and Bangladesh (Pouliotte et al., 2009).

Mortality: Social conditioning affects mortality for women and men. Rahman (2013) and Nellemann et al. (2011) confirm patterns of gender disparity with respect to swimming that contribute to high number of female deaths due to climate-related disasters. Restricted mobility keeps women in Bangladesh and Nicaragua waiting in risk-prone houses during floods (Saito, 2009; Bradshaw, 2010). Some disaster relief structures that lack facilities appropriate for women may contribute to increased harm and mortality (World Bank, 2010).When they are socioeconomically disadvantaged and the disasters exacerbate existing patterns of discrimination, more women die in hurricanes and floods (Neumayer and Plümper, 2007; Ray-Bennett, 2009). Yet, men experience a higher mortality rate when fulfilling culturally imposed roles as heroic life-savers (Röhr, 2006; Campbell et al., 2009; Resurreccion, 2011).

13.3. Assessment of Impacts of Climate Change Responses on Livelihoods and Poverty

[...]

13.3.1. Impacts of Mitigation Responses

[...]

13.3.1.2. Reduction of Emissions from Deforestation and Forest Degradation

Latent negative impacts include exclusion of local people from forest use, and loss of local ownership in documenting the state of forests due to external monitoring and verification mechanisms (Gupta et al., 2012; Pokorny et al., 2013). Benefit flows may be unevenly distributed with regards to ethnicity (Krause and Loft, 2013), gender (Peach Brown, 2011; UN-REDD, 2011), or simply not target the poor (Hett et al., 2012). The absence of a global REDD+ mechanism means that progress on REDD+ may occur as much through voluntary bilateral and public-private processes as through multilateral, regulatory requirements (Agrawal et al., 2011). Positive future benefits for poor people from REDD+ will require attention to tenure and property rights, gender interests, and community engagement (Danielsen et al., 2011;Mustalahti et al., 2012).

[...]

13.3.1.4. Biofuel Production and Large-Scale Land Acquisitions:

LSLA have also triggered a land rush in LICs, which affects livelihood choices and outcomes,with some distinct gender dimensions (Chu, 2011; De Schutter, 2011;Julia and White, 2012; Peters, 2013). New competition for land dispossesses smallholders, displaces food production, degrades the environment, and pushes poor people onto more marginal lands less adaptable to climatic stressors (Cotula et al., 2009; BorrasJr. et al., 2011a; Rulli et al., 2013; Weinzettel et al., 2013). The expansion of bioenergy, and biofuels in particular, increases the corporate power of international actors over governments and local actors with harmful effects on national food and agricultural policies (Dauvergne and Neville, 2009; Glenna and Cahoy, 2009; Hollander, 2010; Mol, 2010; Fortin, 2011; Jarosz, 2012), further marginalizing smallholders (Ariza-Montobbio et al., 2010; De Schutter, 2011; Neville and Dauvergne, 2012) and indigenous peoples (Montefrio, 2012; Obidzinski et al., 2012; Manik et al., 2013; Montefrio and Sonnenfeld, 2013). There is growing apprehension that increased competition for scarce land undermines women’s access to land and their ability to benefit economically from biofuel investment (Arndt et al., 2011; Chu, 2011; Molony, 2011; Behrman et al., 2012; Julia and White, 2012; Perch et al., 2012). Concerns differ somewhat among regions, with the greatest risk for negative outcomes for smallholders in Africa (Daley and Englert, 2010; Borras et al., 2011b).

13.3.2. Impacts of Adaptation Responses on Poverty and Livelihoods

[...]

13.3.2.1. Impacts of Adaptation Responses on Livelihoods and Poverty

Few rigorous studies about pilot adaptation projects exist outside of organizations’ own assessments (Mapfumo et al., 2010; Nkem et al., 2011) or evaluations of how planned adaptation was implemented or integrated into development (Gagnon-Lebrun andAgrawala, 2006; Gigli and Agrawala, 2007). An assessment of the only completed Global Environment Facility/World Bank (GEF/WB)-funded adaptation project, in the Caribbean, Colombia, and Kiribati, did not directly appraise the effects on poverty and livelihoods due to scarce baseline poverty data. Other projects, such as in India’s KarnatakaWatershed, are said to have increased agricultural productivity, income, and employment, benefiting the poorest and landless and improving equity (IEG, 2012). National Action Plans of Adaptation tend to overemphasize technological and infrastructural measures while often overlooking poor people’s needs, gender issues, and livelihood and adaptation strategies (Agrawal and Perrin, 2009; Perch, 2011)

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