FINAL DRAFT IPCC WGII AR5 Chapter 13 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 Chapter 13. Livelihoods and Poverty Coordinating Lead Authors Lennart Olsson (Sweden), Maggie Opondo (Kenya), Petra Tschakert (USA) Lead Authors Arun Agrawal (USA), Siri Eriksen (Norway), Shiming Ma (China), Leisa Perch (Barbados), Sumaya Zakieldeen (Sudan) Contributing Authors Catherine Jampel (USA), Eric Kissel (USA), Valentina Mara (Romania), Andrei Marin (Norway), David Satterthwaite (UK), Asuncion Lera St. Clair (Norway), Andy Sumner (UK) Review Editors Susan Cutter (USA), Etienne Piguet (Switzerland) Volunteer Chapter Scientist Anna Kaijser (Sweden) Contents Executive Summary 13.1. Scope, Delineations, and Definitions: Livelihoods, Poverty, and Inequality 13.1.1. Livelihoods 13.1.1.1. Dynamic Livelihoods and Trajectories 13.1.1.2. Multiple Stressors 13.1.2. Dimensions of Poverty 13.1.2.1. Framing and Measuring Multidimensional Poverty 13.1.2.2. Geographic Distribution and Trends of the World’s Poor 13.1.2.3. Spatial and Temporal Scales of Poverty 13.1.3. Inequality and Marginalization 13.1.4. Interactions between Livelihoods, Poverty, Inequality, and Climate Change Assessment of Climate Change Impacts on Livelihoods and Poverty 13.2.1. Evidence of Observed Climate Change Impacts on Livelihoods and Poverty 13.2.1.1. Impacts on Livelihood Assets and Human Capabilities 13.2.1.2. Impacts on Livelihood Dynamics and Trajectories 13.2.1.3. Impacts on Poverty Dynamics: Transient and Chronic Poverty 13.2.1.4. Poverty Traps and Critical Thresholds 13.2.2. Understanding Future Impacts of and Risks from Climate Change on Livelihoods and Poverty 13.2.2.1. Projected Risks and Impacts by Geographic Region 13.2.2.2. Anticipated Impacts on Economic Growth and Agricultural Productivity 13.2.2.3. Implications for Livelihood Assets, Trajectories, and Poverty Dynamics 13.2.2.4. Impacts on Transient and Chronic Poverty, Poverty Traps, and Thresholds Assessment of Impacts of Climate Change Responses on Livelihoods and Poverty 13.3.1. Impacts of Mitigation Responses 13.3.1.1. The Clean Development Mechanism (CDM) 13.3.1.2. Reduction of Emissions from Deforestation and Forest Degradation (REDD+) 13.3.1.3. Voluntary Carbon Offsets 13.3.1.4. Biofuel Production and Large-Scale Land Acquisitions 13.3.2. Impacts of Adaptation Responses on Poverty and Livelihoods 13.2. 13.3. Subject to Final Copyedit 1 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 13 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 13.3.2.1. Impacts of Adaptation Responses on Livelihoods and Poverty 13.3.2.2. Insurance Mechanisms for Adaptation 13.4. Implications of Climate Change for Poverty Alleviation Efforts 13.4.1. Lessons from Climate-Development Efforts 13.4.2. Toward Climate-Resilient Development Pathways Synthesis and Research Gaps 13.5. References Chapter Boxes 13-1. Climate and Gender Inequality: Complex and Intersecting Power Relations 13-2. Lessons from Social Protection, Disaster Risk Reduction, and Energy Access Frequently Asked Questions 13.1: What are multiple stressors and how do they intersect with inequalities to influence livelihood trajectories? 13.2: How important are climate change-driven impacts on poverty compared to other drivers of poverty? 13.3: Are there unintended negative consequences of climate change policies for people who are poor? Executive Summary This chapter discusses how livelihoods, poverty and the lives of poor people, and inequality interact with climate change, climate variability, and extreme events in multifaceted and cross-scalar ways. It examines how current impacts of climate change, projected impacts up until 2100, and responses to climate change affect livelihoods and poverty. The Fourth Assessment Report stated that socially and economically disadvantaged and marginalized people are disproportionally affected by climate change. However, no comprehensive review of climate change, poverty, and livelihoods has been undertaken to date by the IPCC. This chapter addresses this gap, presenting evidence of the dynamic interactions between these three principal factors. At the same time, the chapter recognizes that climate change is rarely the only factor that affects livelihood trajectories and poverty dynamics; climate change interacts with a multitude of non-climatic factors, which makes detection and attribution challenging. Observed climate variability, climate change, and extreme events constitute an additional burden to rural and urban people living in poverty. These climate-related hazards act as a threat multiplier, often with negative outcomes for livelihoods (high confidence, based on medium evidence, high agreement). • Climate-related hazards, including subtle shifts and trends to extreme events, affect poor people’s lives directly through impacts on livelihoods, such as losses in crop yields, destroyed homes, food insecurity, and loss of sense of place, and indirectly through increased food prices (robust evidence, high agreement). [13.2.1, 13.3] • Changing climate trends lead to shifts in rural livelihoods with mixed outcomes, such as from crop-based to hybrid livestock-based livelihoods or to wage labor in urban employment. Climate change is one stressor that shapes dynamic and differential livelihood trajectories (robust evidence, high agreement). [13.1.4, 13.2.1.2] • Urban and rural transient poor who face multiple deprivations slide into chronic poverty as a result of extreme events, or a series of events, when unable to rebuild their eroded assets. Poverty traps also arise from food price increase, restricted mobility, and discrimination (limited evidence, high agreement). [13.2.1.3, 13.2.1.4] • Many events that affect poor people are weather-related and remain unrecognized by standard climate observations in many low-income countries, due to short time series and geographically sparse, aggregated, or partial data, inhibiting detection and attribution. Such events include short periods of extreme temperature, minor changes in the distribution of rainfall, and strong wind events (robust evidence, high agreement). [13.2.1] Subject to Final Copyedit 2 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 13 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 Observed evidence suggests that climate change and climate variability worsen existing poverty, exacerbate inequalities, and trigger both new vulnerabilities and some opportunities for individuals and communities. Poor people are poor for different reasons and thus are not all equally affected, and not all vulnerable people are poor. Climate change interacts with non-climatic stressors and entrenched structural inequalities to shape vulnerabilities (very high confidence, based on robust evidence, high agreement). • Socially and geographically disadvantaged people exposed to persistent inequalities at the intersection of various dimensions of discrimination based on gender, age, race, class, caste, indigeneity, and (dis)ability are particularly negatively affected by climate change and climate-related hazards. Context-specific conditions of marginalization shape multidimensional vulnerability and differential impacts. [13.1.2.3, 13.1.3., 13.2.1.5] • Existing gender inequalities are increased or heightened by climate-related hazards. Gendered impacts result from customary and new roles in society, often entailing higher workloads, occupational hazards indoors and outdoors, psychological and emotional distress, and mortality in climate-related disasters. [13.2.1.5] • There is little evidence that shows positive impacts of climate change on poor people, except isolated cases of social asset accumulation, agricultural diversification, disaster preparedness, and collective action. The more affluent often take advantage of shocks and crises, given their flexible assets and power status. [13.1.4, 13.2.1.4] Climate change will create new poor between now and 2100, in low-, medium, and high-income countries (LICs, MICs, and HICs), and jeopardize sustainable development. The majority of severe impacts are projected for urban areas and some rural regions in sub-Saharan Africa and Southeast Asia (medium confidence, based on medium evidence, medium agreement). • Future impacts of climate change, extending from the near-term to the long-term, mostly expecting 2C scenarios, will slow down economic growth and poverty reduction, further erode food security, and trigger new poverty traps, the latter particularly in urban areas and emerging hotspots of hunger. [13. 2.2.2, 13.2.2.4, 13.4] • Climate change will exacerbate multidimensional poverty in LICs and lower MICs, including high mountain states, countries at risk from sea level rise, and countries with indigenous peoples. Climate change will also create new poverty pockets in upper MICs and HICs where inequality is on the rise. [13.2.2] • Wage-labor dependent poor households that are net buyers of food will be particularly affected due to food price increases, in urban and rural areas, especially in regions with high food insecurity and high inequality (particularly in Africa), although the agricultural self-employed could benefit [13.2.2.3, 13.2.2.4] Current policy responses for climate change mitigation or adaptation will result in mixed, and in some cases even detrimental, outcomes for poor and marginalized people, despite numerous potential synergies between climate policies and poverty reduction (medium confidence, based on limited evidence, high agreement). • Mitigation policies with social co-benefits expected in their design, such as CDM and REDD+, have had limited or no effect in terms of poverty alleviation and sustainable development. [13.3.1.1, 13.3.1.2] • Mitigation efforts focused on land acquisition for biofuel production show preliminary negative impacts on the lives of poor people, such as dispossession of farmland and forests, in many LICs and MICs, particularly for indigenous peoples and (women) smallholders. [13.3.1.4] • Insurance schemes, social protection programs, and disaster risk reduction may enhance long-term livelihood resilience among poor and marginalized people, if policies address multidimensional poverty. [13.3.2.2, 13.4.1] • Climate-resilient development pathways will have only marginal effects on poverty reduction, unless structural inequalities are addressed and needs for equity among poor and non-poor people are met. [13.4.2] 13.1. Scope, Delineations, and Definitions: Livelihoods, Poverty, and Inequality Understanding the impacts of climate change on livelihoods and poverty requires examining the complexities of poverty and the lives of poor and non-poor people, as well as the multifaceted and cross-scalar intersections of Subject to Final Copyedit 3 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 13 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 poverty and livelihoods with climate change. This chapter is devoted to exploring poverty in relation to climate change, a novelty in the IPCC. It uses a livelihood lens to assess the interactions between climate change and multiple dimensions of poverty. We use the term “the poor,” not to homogenize, but to describe people living in poverty, people facing multiple deprivations, and the socially and economically disadvantaged, as part of a conceptualization broader than income-based measures of poverty, acknowledging gradients of prosperity and poverty. This livelihood lens also reveals how inequalities perpetuate poverty to shape differential vulnerabilities and in turn the differentiated impacts of climate change on individuals and societies. The chapter first presents the concepts of livelihoods, poverty, and inequality, and their relationships to each other and to climate change. Second, it describes observed impacts of weather events and climate on livelihoods and rural and urban poor people as well as projected impacts up to 2100. We use “weather events and climate” as an umbrella term for climate change, climate variability, and extreme events, and also highlight subtle shifts in precipitation and localized weather events. Third, this chapter discusses impacts of climate change mitigation and adaptation responses on livelihoods and poverty. Finally, it outlines implications for poverty alleviation efforts and climate-resilient development pathways. Livelihoods and Poverty is a new chapter in the AR5. Although the AR4 WGII contributions mentioned poverty, as one of several non-climatic factors contributing to vulnerability, as a serious obstacle to effective adaptation, and in the context of endemic poverty in Africa (Technical Summary, Chapters 7, 8, 18, 20), no systematic assessment was undertaken. Livelihoods were more frequently addressed in the AR4 and in the SREX, predominantly with reference to livelihood strategies and opportunities, diversification, resource-dependent communities, and sustainability. Yet, a comprehensive livelihood lens for assessing impacts was lacking. This chapter addresses these gaps. It assesses how climate change intersects with other stressors to shape livelihood choices and trajectories, to affect the spatial and temporal dimensions of poverty dynamics, and to reduce or exacerbate inequalities given differential vulnerabilities. 13.1.1. Livelihoods Livelihoods (see also Glossary) are understood as the ensemble or opportunity set of capabilities, assets, and activities that are required to make a living (Chambers and Conway, 1992; Ellis et al., 2003). They depend on access to natural, human, physical, financial, social, and cultural capital (assets); the social relations people draw upon to combine, transform, and expand their assets; and the ways people deploy and enhance their capabilities to act and make lives meaningful (Scoones, 1998; Bebbington, 1999). Livelihoods are dynamic and people adapt and change their livelihoods with internal and external stressors. Ultimately, successful livelihoods transform assets into income, dignity, and agency, to improve living conditions, a prerequisite for poverty alleviation (Sen, 1981). Livelihoods are universal. Poor and rich people both pursue livelihoods to make a living. However, as shown in this chapter, the adverse impacts of weather events and climate increasingly threaten and erode basic needs, capabilities, and rights, particularly among poor and disenfranchised people, in turn reshaping their livelihoods (UNDP, 2007; Leary et al., 2008; Adger, 2010; Quinn et al., 2011). Some livelihoods are directly climate-sensitive, such as rainfed smallholder agriculture, seasonal employment in agriculture (e.g. tea, coffee, sugar), fishing, pastoralism, and tourism. Climate change also affects households dependent on informal livelihoods or wage labor in poor urban settlements, directly through unsafe settlement structures or indirectly through rises in food prices or migration. 13.1.1.1. Dynamic Livelihoods and Trajectories A livelihood lens is a grounded and multidimensional perspective that recognizes the flexibility and constraints with which people construct their complex lives and adapt their livelihoods in dynamic ways. By paying attention to the wider institutional, cultural, and policy contexts as well as shocks, seasonality, and trends, this lens reveals processes that push people onto undesirable trajectories or toward enhanced well-being. Better infrastructure and technology as well as diversification of assets, activities, and social support capabilities can boost livelihoods, spreading risks and broadening opportunities (Batterbury, 2001; Ellis et al., 2003; Clot and Carter, 2009; Reed et al., 2013; Carr, 2013). The sustainable livelihoods framework (Chambers and Conway, 1992) is widely used for identifying how specific strategies may lead to cycles of livelihood improvements or critical thresholds beyond which certain livelihoods are no longer sustainable (Sabates-Wheeler et al., 2008). It emerged as a reaction to the predominantly Subject to Final Copyedit 4 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 13 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 structural views of poverty and “underdevelopment” in the 1970s and became adopted by many researchers and development agencies (Ellis and Biggs, 2001). With the neoliberal turn in the late 1980s, the livelihoods approach became associated with a more individualistic development agenda, stressing various forms of capital (Scoones, 2009). Consequently, it has been criticized for its analytical limitations, such as measuring capitals or assets, especially social capital, and for not sufficiently explaining wider structural processes (e.g., policies) and ecological impacts of livelihood decisions (Small, 2007; Scoones, 2009). An overemphasis on capitals also eclipses power dynamics and the position of households in class, race, and other dimensions of inequality (Van Dijk, 2011). 13.1.1.2. Multiple Stressors Livelihoods rarely face only one stressor or shock at a time. The literature emphasizes the synergistic relationship between weather events and climate and a variety of other environmental, social, economic, and political stressors; together, they impinge on livelihoods and reinforce each other in the process, often negatively (Reid and Vogel, 2006; Schipper and Pelling, 2006; Tschakert, 2007; IPCC, 2007; Morton, 2007; Easterling et al., 2007; O'Brien et al., 2008; Eakin and Wehbe, 2009; Eriksen and Silva, 2009; Ziervogel et al., 2010). “Double losers” may emerge from simultaneous exposure to climatic change and other stressors such as the spread of infectious diseases, rapid urbanization, and economic globalization, where climate change acts as a threat multiplier, further marginalizing vulnerable groups (O'Brien and Leichenko, 2000; Eriksen and Silva, 2009). Climatic and other stressors affect livelihoods at different scales: spatial (e.g., village, nation) or temporal (e.g., annual, multi-annual). Both direct and indirect impacts are often amplified or weakened at different levels. Global or regional processes generate a variety of stressors, typically mediated by cross-level institutions, that result in locally experienced shocks (Reid and Vogel, 2006; Thomas et al., 2007; Paavola, 2008; Pouliotte et al., 2009) (see Figure 13-1 in FAQ 13.1). Multiple stressors, simultaneous and in sequence, shape livelihood dynamics in distinct ways due to inequalities and differential vulnerabilities between and within households. More affluent households may be able to capitalize on shocks and crises while poorer households with fewer options are forced to erode their assets. Limited ability to adapt and some coping strategies may result in adverse consequences. Such maladaptive actions (see Glossary, and Chapters 14, 16) undermine the long-term sustainability of livelihoods, resulting in downward trajectories, poverty traps, and exacerbated inequalities (Ziervogel et al., 2006; Tanner and Mitchell, 2008; Barnett and O’Neill, 2010). [INSERT FIGURE 13-1 HERE (within FAQ 13.1) Figure 13-1: Multiple stressors related to climate change, globalizations, and technological change interact with national and regional institutions to create shocks to place-based livelihoods, inspired by Reason (2000).] 13.1.2. Dimensions of Poverty Poverty is a complex concept with conflicting definitions and considerable disagreement in terms of framings, methodologies, and measurements. Despite different approaches emphasizing distinct aspects of poverty at the individual or collective level, such as income, capabilities, and quality of life (Laderchi et al., 2003), poverty is recognized as multidimensional (UNDP, 1990). It is influenced by social, economic, institutional, political, and cultural drivers; its reversal requires efforts in multiple domains that promote opportunities and empowerment, and enhance security (World Bank, 2001). In addition to material deprivation, multidimensional conceptions of poverty consider a sense of belonging and socio-cultural heritage (O'Brien and Leichenko, 2003), identity, and agency, or “the culturally constrained capacity to act” (Ahearn, 2001 p.54). The AR4 identified poverty as “the most serious obstacle to effective adaptation” (Confalonieri et al., 2007, p.417). 13.1.2.1. Framing and Measuring Multidimensional Poverty Over the last six decades, conceptualizations of poverty have broadened, expanding the basis for understanding poverty and its drivers. Poverty measurements now better capture multidimensional characteristics and spatial and temporal nuances. Attention to multidimensional deprivations, such as hunger, illiteracy, unclean drinking water, Subject to Final Copyedit 5 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 13 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 lack of access to health, credit, or legal services, social exclusion, and empowerment, have shifted the analytical lens to the dynamics of poverty and its institutionalization within social and political norms (UNDP, 1994; Sen, 1999; World Bank, 2001). Regardless of these shifting conceptualizations over time, comparable and reliable measures remain challenging and income per capita remains the default method to account for the depth of global poverty. In climate change literature, poverty and poverty reduction have been predominantly defined through an economic lens, reflecting various growth and development discourses (Sachs, 2006; Collier, 2007). Less attention has been paid to relational poverty, produced through material social relations and in relation to privilege and wealth (Sen, 1976; Mosse, 2010; Alkire and Foster, 2011; UNDP, 2011a). Yet, such framing allows for addressing the social and political contexts that generate and perpetuate poverty and structural vulnerability to climate change (McCright and Dunlap, 2000; Bandiera et al., 2005; Leichenko and O'Brien, 2008). Many climate policies to date favor marketbased responses using sector-specific and economic growth models of development, although some responses may slow down achievements of international development such as those outlined in the Millennium Development Goals (MDGs). For instance, the World Bank encourages “mitigation, adaptation, and the deployment of technologies” that “allow[s] developing countries to continue their growth and reduce poverty” (World Bank, 2010, p.257), mainly promoted through market tools. A relational approach to poverty highlights the integral role of poor people in all social relations (Pogge, 2009; O'Brien et al., 2010; UNRISD, 2010; Gasper et al., 2013; St.Clair and Lawson, 2013). It emphasizes equity, human security, and dignity (O'Connor, 2002; Mosse, 2010). Akin to the capabilities approach (Sen, 1985; Sen, 1999; Nussbaum, 2001; Alkire, 2005; Nussbaum, 2011), the relational approach stresses the needs, skills, and aims of poor people while tackling structural causes of poverty, inequalities, and uneven power relations. The IPCC AR4 (Yohe et al., 2007) highlighted that – with very high confidence – climate change will impede the ability of nations to alleviate poverty and achieve sustainable development, as measured by progress towards the MDGs. Empirical assessments of the impact of climate change on MDG attainment are limited (Fankhauser and Schmidt-Traub, 2011), and the failure to reach these goals by 2015 has significant non-climatic causes (e.g. Hellmuth and IRI, 2007; UNDP, 2007). The 2010 UNDP Multidimensional Poverty Index, measuring intensity of poverty based on patterns of simultaneous deprivations in basic services (education, health, and standard of living) and core human functionings, states that close to 1.7 billion people face multidimensional poverty, a significantly higher number than the 1.2 billion (World Bank, 2012a) indicated by the International Poverty Line (IPL) set at $1.25/day. Figure 13-2 depicts country-level examples of how the two poverty measures differ. Caution is required for poverty projections. Estimates of poverty made using national accounts means (see Chapter 19) yield drastically different estimates to those produced by survey means, both for current estimates and future projections (Edward and Sumner, 2013a). Diverse conceptions of poverty further complicate projections, as multidimensional conceptions rely on concepts difficult to measure and compare. Data availability constrains current estimates let alone projections and their core assumptions (Alkire and Santos, 2010; Karver et al., 2012). [INSERT FIGURE 13-2 HERE Figure 13-2: A) Multidimensional poverty and income-based poverty using the International Poverty Line $1.25/day (in Purchasing Power Parity terms), with linear regression relationship (dotted line) based on 96 countries (UNDP, 2011b). The position of the countries relative to the dotted line illustrates the extent to which these two poverty measures are similar or divergent (e.g., Niger). B) The map insets show the intensity of poverty in two countries, based on the Poverty Gap Index at district level (per capita measure of the shortfall in welfare of the poor from the poverty line, expressed as a ratio of the poverty line). The darker the purple shading, the larger the shortfall.] 13.1.2.2. Geographic Distribution and Trends of the World’s Poor Geographic patterns of poverty are uneven and shifting. Despite its limitations, most comparisons to date rely on the IPL. In 1990, most of the world’s $1.25 and $2 poor lived in low-income countries (LICs). By 2008, the majority of the $1.25 and $2 poor (>70%) resided in lower and upper middle-income countries (LMICs and UMICs), in part because some populous LICs such as India, Nigeria, and Pakistan grew in per capita income to MIC status (Sumner, 2010; Sumner, 2012a). Estimates suggest about one billion people currently living under $1.25/day in MICs and a second billion between $1.25 and $2, with an additional 320m and 170m in LICs, respectively (Sumner, 2012b). Subject to Final Copyedit 6 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 13 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 About 70% of the $1.25 poor live in rural areas in the global South (IFAD, 2011), despite worldwide urbanization. Yet, this poverty line understates urban poverty as it does not fully account for the higher costs of food and non-food items in many urban contexts (Mitlin and Satterthwaite, 2013). Of the approximately 2.4 billion living under $2/day, half live in India and China. At the same time, relative poverty is rising in HICs. Many European countries face rapid increases in poverty, unemployment, and the number of working poor due to recent austerity measures. For example, 20% of Spanish citizens were ranked poor in 2009 (Ortiz and Cummins, 2013). See also Chapter 23. The shift in distribution of global poverty toward MICs and the increase in relative poverty in HICs challenge the orthodox view that most of the world’s poorest people live in the poorest countries, and suggests that substantial pockets of poverty persist in countries with higher levels of average per capita income. Understanding this shift in the geography of poverty and available social safety nets is vital for assessing climate change impacts on poverty. To date, both climate finance and research on climate impacts and vulnerabilities are largely directed towards LICs. Less attention has been paid to poor people in MICs and HICs. In the upper and lower MICs, the incidence of $2 poverty, despite declines, remains as high as 60% and 20%, respectively (Sumner, 2012b). Projections for 2030 suggest $2 poverty as high as 963 million people in sub-Saharan Africa and 851 million in India (Sumner et al., 2012; Edward and Sumner, 2013a). However, uncertainty is high in terms of future growth and inequality trends; by 2030, $1.25 and $2 global poverty could be reduced to 300m and 600m respectively or remain at or above current levels, including in stable MICs (Edward and Sumner, 2013a). These future scenarios become more uncertain if climate change impacts on people who are socially and economically disadvantaged are taken into account or diversion of resources from poverty reduction and social protection to mitigation strategies is considered. 13.1.2.3. Spatial and Temporal Scales of Poverty Poverty is also socially distributed, across spatial and temporal scales. Not everybody is poor in the same way. Spatially, factors such as access to and control over resources and institutional linkages from individuals to the international level affect poverty distribution (Anderson and Broch-Due, 2000; Murray, 2002; O'Laughlin, 2002; Rodima-Taylor, 2011). Even at the household level, poverty differs between men and women and age groups, yet data constraints impede systematic intra-household analysis (Alkire and Santos, 2010). The distribution of poverty also varies temporally, typically between chronic and transient poverty (Sen, 1981; Sen, 1999). Chronic poverty describes an individual deprivation, per capita income, or consumption levels below the poverty line over many years (Gaiha and Deolalikar, 1993; Jalan and Ravallion, 2000; Hulme and Shepherd, 2003). Transient poverty denotes a temporary state of deprivation, and is frequently seasonal and triggered by an individual’s or household’s inability to maintain income or consumption levels in times of shocks or crises (Jalan and Ravallion, 1998). Individuals and households can fluctuate between different degrees of poverty and shift in and out of deprivation, vulnerability, and well-being (Leach et al., 1999; Little et al., 2008; Sallu et al., 2010). Yet, the most disadvantaged often find themselves in poverty traps, or situations in which escaping poverty becomes impossible without external assistance due to unproductive or inflexible asset portfolios (Barrett and McPeak, 2006). A poverty trap can also be seen as a “critical minimum asset threshold, below which families are unable to successfully educate their children, build up their productive assets, and move ahead economically over time” (Carter et al., 2007 p.837). As of 2008, a total of 320 to 443 million of people were trapped in chronic poverty (Chronic Poverty Research Centre, 2008), leading Sachs (2006) to label <$1.25/day poverty as a trap in itself. Poverty traps at the national level are often related to poor governance, reduced foreign investment, and conflict (see Chapters 10 and 12). 13.1.3. Inequality and Marginalization Specific livelihoods and poverty alone do not necessarily make people vulnerable to weather events and climate. The socially and economically disadvantaged and the marginalized are disproportionately affected by the impacts of climate change and extreme events (robust evidence) (Kates, 2000; Paavola and Adger, 2006; Adger et al., 2007; Cordona et al., 2012). The AR4 identified poor and indigenous peoples in North America (Field et al., 2007) and in Africa (Boko et al., 2007) as highly vulnerable. Vulnerability, or the propensity or predisposition to be adversely Subject to Final Copyedit 7 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 13 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 affected (Field et al., 2012a) by climatic risks and other stressors (see also Glossary), emerges from the intersection of different inequalities, and uneven power structures, and hence is socially-differentiated (Sen, 1999; Banik, 2009; Field et al., 2012a). Vulnerability is often high among indigenous peoples, women, children, the elderly, and disabled people who experience multiple deprivations that inhibit them from managing daily risks and shocks (Eriksen and O'Brien, 2007; Ayers and Huq, 2009; Boyd and Juhola, 2009; Barnett and O’Neill, 2010; O'Brien et al., 2010; Petheram et al., 2010) and may present significant barriers to adaptation. Global income inequality has been relatively consistent since the late 1980s. In 2007, the top quintile of the world’s population received 83% of the total income whereas the bottom quintile took in 1% (Ortiz and Cummins, 2011). Since 2005, between-country inequality has been falling more quickly and, consequently, has triggered a notable decline in total global inequality in the last few years (Edward and Sumner, 2013b). However, within-country inequality is rising in Asia, especially China, albeit from relatively low levels, and is falling in Latin America, albeit from very high levels, while trends in sub-Saharan Africa are difficult to discern regionally (Ravallion and Chen, 2012). Income inequality is rising in many fast growing LICs and MICs (Dollar et al., 2013; Edward and Sumner, 2013b). It is also growing in many HICs due to a combination of factors such as changing tax systems, privatization of social services, labor market regulations, and technological change (OECD, 2011). The 2008 financial crisis, combined with climate change, has further threatened economic growth in HICs, such as the U.K., and resources available for social policies and welfare systems (Gough, 2010). Recognizing how inequality and marginalization perpetuate poverty is a prerequisite for climate-resilient development pathways (see 13.4; and Chapters 1, 20, 27). 13.1.4. Interactions between Livelihoods, Poverty, Inequality, and Climate Change This chapter opens its analytical lens from a conventional focus on the poor in LICs as the prime victims of climate change to a broader understanding of livelihood and poverty dynamics and inequalities, revealing the highly unequal impacts of climate change. It highlights the complex relationship between climate change and poverty. The SREX recognizes that addressing structural inequalities that create and sustain poverty and vulnerability (Huq et al., 2005; Schipper, 2007; Lemos et al., 2007; Boyd and Juhola, 2009; Williams, 2010; Perch, 2011) is a crucial precondition for confronting climate change (Field et al., 2012a). If ignored, uneven social relations that disproportionally burden poor people with climate change’s negative impacts provoke maladaptation (Barnett and O’Neill, 2010). Poverty and persistent inequality are the “most salient of the conditions that shape climate-related vulnerability” (Ribot, 2010, p.50). They affect livelihood options and trajectories, and create conditions in which people have few assets to liquidate in times of hardship or crisis (Mearns and Norton, 2010). People who are poor and marginalized usually have the least buffer to face even modest climate hazards and suffer most from successive events with little time for recovery. They are the first to experience asset erosion, poverty traps, and barriers and limits to adaptation. As shown in 13.2 and 13.3, climate change is an additional burden to people in poverty (very high confidence), and it will force poor people from transient into chronic poverty and create new poor (medium confidence). The complex interactions among weather events and climate, dynamic livelihoods, multidimensional poverty and deprivation, and persistent inequalities, including gender inequalities, create an ever-shifting context of risk. The SREX concluded that climate change, climate variability, and extreme events synergistically add on to and often reinforce other environmental, social, and political calamities (Field et al., 2012a). Despite the recognition of these complex interactions, the literature shows no single conceptual framework that captures them concurrently, and few studies exist that overlay gradual climatic shifts or rapid-onset events onto livelihood risks. Hence, explicit attention to how livelihood dynamics interact with climatic and non-climatic stressors is useful for identifying processes that push poor and vulnerable people onto undesirable trajectories, trap them in destitution, or facilitate pathways toward enhanced well-being. Figure 13-3 illustrates these dynamics as well as critical thresholds in livelihood trajectories. [INSERT FIGURE 13-3 HERE Figure 13-3: Illustrative depiction of livelihood dynamics under simultaneous climatic, environmental, and socioeconomic stressors and shocks leading to differential livelihood trajectories over time, based on four case studies. The red boxes indicate specific critical moments when stressors converge, threatening livelihoods and well-being. Key variables and impacts numbered in the illustrations correspond to the developments described in the captions.] Subject to Final Copyedit 8 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 13 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 13.2. Assessment of Climate Change Impacts on Livelihoods and Poverty This section reviews the evidence and agreement about the relationships among climate change, livelihoods, poverty, and inequality. Building on deductive reasoning and theorized linkages about these dynamic relationships, this section draws on a wide range of empirical case studies and simulations to illustrate linkages across multiple scales, contexts, and social and environmental processes and assess impacts of climate change. Although cases of observed impacts often rely on qualitative data and at times lack methodological clarity in terms of detection and attribution, they provide a vital evidence base for conveying these complex relationships. This section first describes observed impacts to date (13.2.1) and then projected risks and impacts (13.2.2). 13.2.1. Evidence of Observed Climate Change Impacts on Livelihoods and Poverty Weather events and climate affect the lives and livelihoods of millions of poor people (Field et al., 2012b). Even minor changes in precipitation amount or temporal distribution, short periods of extreme temperatures, or localized strong winds can harm livelihoods (Douglas et al., 2008; Ostfeld, 2009; Midgley and Thuiller, 2011; Bele et al., 2013; Bryan et al., 2013). Many such events remain unrecognized given that standard climate observations typically report precipitation or temperature by month, season, or year, thus obscuring changes that shape decision making, for instance, in agriculture (Tennant and Hewitson, 2002; Barron et al., 2003; Usman and Reason, 2004; Douglas et al., 2008; Salack et al., 2012; Lacombe et al., 2012). This difficulty in detection and attribution is compounded by a lack of long-term continuous and dense networks of climate data in many LICs (UNECA, 2011). Felt experiences of events such as drought, as shown among the Sumbanese in Eastern Indonesia through phenomenological research on perceptions of climatic phenomena, such as shade and dew (Orr et al., 2012), further add to the complexity. 13.2.1.1. Impacts on Livelihood Assets and Human Capabilities Climate change, climate variability, and extreme events interact with numerous aspects of people’s livelihoods. This section presents empirical evidence of impacts on natural, physical, financial, human, and social and cultural assets (see also Chapters 22-29). Impacts on access to assets, albeit important, are poorly documented in the literature, as are impacts on power relations and active struggles in designing effective and relational livelihood arrangements. Weather events and climate affect natural assets on which certain livelihoods depend directly, such as rivers, lakes, and fish stocks (robust evidence) (Thomas et al., 2007; Nelson and Stathers, 2009; Osbahr et al., 2010; Bunce et al., 2010a; Bunce et al., 2010b; D’Agostino and Sovacool, 2011) (see Chapters 3, 4, 5, 6, and 30). During the 20th century, water temperatures increased and winds decreased in Lake Tanganyika (Verburg and Hecky, 2009; Adrian et al., 2009; Tierney et al., 2010). Since the late 1970s, a drop in primary production and fish catches, a key protein source, has been observed, and climate change may exceed the effects of overfishing and other human impacts in this area (O'Reilly et al., 2003). The Middle East and North Africa (MENA) face dwindling water resources due to less precipitation and rising temperatures combined with mounting water demand due to population and economic growth (Tekken and Kropp, 2012), resulting in rapidly decreasing water availability that, in 2025, could be 30-70% less per person (Sowers et al., 2011). In MENA (Sowers et al., 2011), the Andes and Himalayas (Orlove, 2009), the Caribbean (Cashman et al., 2010), Australia (Alston, 2011), and in cities (Satterthwaite, 2011), policy allocation often favors more affluent consumers, at the expense of less powerful rural and/or poor users. Weather events and climate also erode farming livelihoods (see Chapters 7, 9), via declining crop yields (Hassan and Nhemachena, 2008; Apata et al., 2009; Sissoko et al., 2011; Sietz et al., 2012; Li et al., 2013), at times compounded by increased pathogens, insect attacks, and parasitic weeds (Stringer et al., 2007; Byg and Salick, 2009), and less availability of and access to non-timber forest products (Hertel and Rosch, 2010; Nkem et al., 2012) and medicinal plants and biodiversity (Van Noordwijk, 2010). For agropastoral and mixed crop-livestock livelihoods, extreme high temperatures threaten cattle (Hahn, 1997; Thornton et al., 2007; Mader, 2012; Nesamvuni et al., 2012); in Kenya, for instance, people may shift from dairy to beef cattle and from sheep to goats (Kabubo‐Mariara, 2008). Subject to Final Copyedit 9 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 13 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 The most extreme form of erosion of natural assets is the complete disappearance of people’s land on islands and in coastal regions (McGranahan et al., 2007; Solomon et al., 2009), exacerbating livelihood risks due to loss of economic and social assets (see Chapters 5 and 29) (Perch and Roy, 2010). Densely populated coastal cities with high poverty such as Alexandria and Port Said in Egypt (El-Raey et al., 1999), Cotonou in Benin (Dossou and Glehouenou-Dossou, 2007), and Lagos and Port Harcourt in Nigeria (Abam et al., 2000; Fashae and Onafeso, 2011) are already affected by floods and at risk of submersion. Resettlements are planned for the Limpopo River and the Mekong River Delta (de Sherbinin et al., 2011) and small island states may become uninhabitable (Burkett, 2011). Damage to physical assets due to weather events and climate is well documented for poor urban settlements, often built in risk-prone floodplains and hillsides susceptible to erosion and landslides. Impacts include homes destroyed by flood water and disrupted water and sanitation services. Flooding has adversely affected large cities in Africa (Douglas et al., 2008) and Latin America (Hardoy and Pandiella, 2009; Hardoy et al., 2011), in predominantly dense informal settlements due to inadequate drainage, and health infrastructure (UNDP, 2011c). Yet, upper middle- and high-income households living in flood-prone areas or high-risk slopes frequently can afford insurance and lobby for protective policies, in contrast to poor residents (Hardoy and Pandiella, 2009). Loss of physical assets in poor areas after disasters is often followed by displacement due to loss of property (Douglas et al., 2008). Increasing flash floods attributed to climate change (Sudmeier-Rieux et al., 2012) have severely damaged terraces, orchards, roads, and stream embankments in the Himalayas (Hewitt and Mehta, 2012; Azhar-Hewitt and Hewitt, 2012). Erosion of financial assets as a result of climatic stressors include losses of farm income and jobs (Hassan and Nhemachena, 2008; Iwasaki et al., 2009; Alderman, 2010; Jabeen et al., 2010; Alston, 2011) and increased costs of living such as higher expenses for funerals (Gabrielsson et al., 2012). In South and Central America, >630 weather and extreme events occurred 2000-2010, resulting in 16,000 fatalities, 46.6 million people affected, and economic losses of US$ 208 million (CRED, 2012). Income losses due to weather events mean less money for agricultural inputs (seeds, equipment), school tuition, uniforms, and books, and health expenses throughout the year (Thomas et al., 2007). Flooding in informal settlements in Lagos undermines job opportunities (Adelekan, 2010). Equally important, albeit frequently overlooked, is the damage to human assets as a result of weather events and climate, such as food insecurity, undernourishment, and chronic hunger due to failed crops (medium evidence) (Patz et al., 2005; Funk et al., 2008; Zambian Government, 2011; Gentle and Maraseni, 2012) or spikes in food prices most severely felt among poor urban populations (Ahmed et al., 2009; Hertel and Rosch, 2010). During the Ethiopian drought (1998-2000) and Hurricane Mitch in Nicaragua (1998), poorer households tended to engage in asset smoothing, reducing their consumption to very low levels to protect their assets, whereas wealthier households sold assets and smoothed consumption (Carter et al., 2007). In such cases, poor people further erode nutritional levels and human health while holding on to their limited assets. Dehydration, heat stroke, and heat exhaustion from exposure to heat waves undermine people’s ability to carry out physical work outdoors and indoors (Semenza et al., 1999; Kakota et al., 2011). Psychological effects from extreme events include sleeplessness, anxiety and depression (Byg and Salick, 2009; Keshavarz et al., 2013), loss of sense of place and belonging (Tschakert et al., 2011; Willox et al., 2012), and suicide (Caldwell et al., 2004; Alston, 2011) (see also Chapter 11 and CC-HS). Finally, weather events and climate also erode social and cultural assets. In some contexts, climatic and nonclimatic stressors and changing trends disrupt informal social networks of the poorest, elderly, women, and womenheaded households, preventing mobilization of labor and reciprocal gifts (Osbahr et al., 2008; Buechler, 2009) as well as formal social networks, including social assistance programs (Douglas et al., 2008). Indigenous peoples (see Chapter 12) witness their cultural points of reference disappearing (Ford, 2009; Green et al., 2010; Bell et al., 2010). 13.2.1.2. Impacts on Livelihood Dynamics and Trajectories Weather events and climate also affect livelihood trajectories and dynamics in livelihood decision making, often in conjunction with cross-scalar socio-economic, institutional, or political stressors. Shifting in and out of hardship and well-being on a seasonal basis is not uncommon. To a large extent, the shifts from coping and hardship to recovery Subject to Final Copyedit 10 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 13 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 are driven by annual and inter-annual climate variability, but may become exacerbated by climate change. Figure 13-4 illustrates seasonal livelihood sensitivity for the Lake Victoria Basin in East Africa (Gabrielsson et al., 2012). [INSERT FIGURE 13-4 HERE Figure 13-4: Seasonal sensitivity of livelihoods to climatic and non-climatic stressors for one calendar year, based on experiences of smallholder farmers in the Lake Victoria Basin in Kenya and Tanzania (Gabrielsson et al., 2012).] Shifts in livelihoods often occur due to changing climate trends, linked to a series of environmental, socio-economic, and political stressors (robust evidence). Farmers may change their crop choices instead of abandoning farming (Kurukulasuriya and Mendelsohn, 2007) or take on more lucrative income-generating activities (see Figure 13-3). Uncertainty about West Africa’s rainy season threatens small-scale farming and water management (Yengoh et al., 2010a; Yengoh et al., 2010b; Armah et al., 2011; Karambiri et al., 2011; Lacombe et al., 2012). Around Mali’s drying Lake Faguibine, livelihoods shifted from water-based to agro-sylvo-pastoral systems, as a direct impact of lower rainfall and more frequent and more severe droughts (Brockhaus and Djoudi, 2008). Diverse indigenous groups in Russia have changed their livelihoods as result of Soviet legacy and climate change; for example, many Viliui Sakha have abandoned cow-keeping due to youth out-migration, growing access to consumer goods, and seasonal changes in temperature, rainfall, and snow (Crate, 2013). Under certain converging shocks and stressors, people adopt entirely new livelihoods. In South Africa, higher precipitation uncertainty raised reliance on livestock and poultry rather than crops alone in 80% of households interviewed (Thomas et al., 2007). In southern Africa and India, people migrated to the coasts, switching from climate-sensitive farming to marine livelihoods (Coulthard, 2008; Bunce et al., 2010a; Bunce et al., 2010b). After Hurricane Stan (2005), land-poor coffee farmers in Chiapas, Mexico, turned from specializing in coffee to being day laborers and subsistence farmers (Eakin et al., 2012). 13.2.1.3. Impacts on Poverty Dynamics: Transient and Chronic Poverty Limited evidence documents the extent to which climate change intersects with poverty dynamics, yet, there is high agreement that shifts from transient to chronic poverty due to weather and climate are occurring, especially after a series of weather or extreme events (Scott-Joseph, 2010). Households in transient poverty may become chronically poor due to a lack of effective response options to weather events and climate, compared with more affluent households (see Figure 13-2). Often, multiple deprivations drive these shifts, with socially and economically marginalized groups particularly prone to slipping into chronic poverty. Women-headed households, children, people in informal settlements (see Chapter 8), and indigenous communities are particularly at risk, due to compounding stressors such as lack of governmental support, urban infrastructure, and insecure land tenure (see 13.2.1.5 and Chapter 12). Poor people in urban areas in LICs and MICs in Africa, Asia, and Latin America may slip from transient to chronic poverty given the combination of population growth and flooding threats in low-elevation cities and water stress in drylands (Balk et al., 2009) along with other multiple deprivations (Mitlin and Satterthwaite, 2013). Poverty shifts also occur in response to food price increases, though the strength of the relationship between weather events and climate and food prices is still debated (see Chapter 7 and 13.3.1.4). Poor households in urban and rural areas are particularly at risk when they are almost exclusively net buyers of food (Cranfield et al., 2007; Cudjoe et al., 2010; Ruel et al., 2010). Misselhorn (2005) showed in a meta-study of 49 cases of food insecurity in southern Africa that climatic drivers and poverty were the two dominant and interacting causal factors. Poor pastoralists have collapsed into chronic poverty when livestock assets have been lost (Thornton et al., 2007). In rural areas, restricted forest access may exacerbate poverty among already income-poor and elderly households who rely on forest resources to respond to climatic shocks (Fisher et al., 2010). Yet, many such shifts remain underexplored, incompletely captured in poverty data and adaptation monitoring. The bulk of evidence in the literature is oriented toward extreme events, rapid-onset disasters, and subsequent impacts on livelihoods and poor people’s lives. Subtle changes are rarely tracked, making quantification of long-term trends and detection of impacts difficult. Subject to Final Copyedit 11 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 13 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 13.2.1.4. Poverty Traps and Critical Thresholds Poverty traps arise when climate change, variability, and extreme events keep poor people poor and make some poor even poorer. Yet, attribution remains a challenge. Among disadvantaged people in urban areas, poverty traps are reported especially for wage laborers who erode their financial capital due to increases in food prices (Ahmed et al., 2009; Hertel and Rosch, 2010) and for those in informal settlements exposed to floods and landslides (Hardoy and Pandiella, 2009). In rural areas, poverty traps are reported when climate change impacts on poor people persist over decades, such as through environmental degradation and recurring stress on ecosystems in the Sahel (Kates, 2000; Hertel and Rosch, 2010; Sissoko et al., 2011; UNCCD, 2011), or when people are unable to rebuild assets after a series of stresses (Eriksen and O'Brien, 2007; Sabates-Wheeler et al., 2008; Sallu et al., 2010). Poverty traps and destitution are also described in pastoralist systems, triggered through droughts, restricted mobility due to conflict and insecurity, adverse terms of trade, and the conversion of grazing areas to agricultural land, such as for biofuel production (Eriksen and Lind, 2009; Homewood, 2009; Eriksen and Marin, 2011). Other poverty traps result from heavy debt loads due to the inability to repay loans and distress sales (Renton, 2009; Ahmed et al., 2012), persistent discrimination through legal structures and formal institutions, especially for women and other marginalized groups (Campbell et al., 2009; McDowell and Hess, 2012), and at the nexus of climate, health and conflict (see Chapter 10). Despite limited evidence, there is high agreement that critical thresholds, or irreversible damage (Heltberg et al., 2009), result from the convergence of various factors, many of which are not directly related to climate change. For instance, poor people often rely on social networks, including reciprocal gifts and exchanges, to protect themselves from shocks and crises such as droughts and illness (Little et al., 2006). Yet, given limited assets and ability to mobilize labor and food, particularly for smaller and women-headed households and the elderly, the exhaustion of these reciprocal ties can indicate an imminent slipping into poverty traps or chronic poverty (Pradhan et al., 2007; Osbahr et al., 2008). Injuries, disabilities, disease, psychological distress, for example from accidents during flood events, diminish poor people’s main asset, labor (Douglas et al., 2008), and may plunge them into chronic poverty. Few studies illustrate positive livelihood impacts as a result of climate change or climate-induced shocks, and they often tend to refer to more affluent and powerful constituencies. Very scarce evidence exists of poor people escaping poverty traps (see Figure 13-2). In Cameroon, though, farming communities benefit from occasional rainfall during the dry season and more food stuffs while the drying of swamps allows maize off season (Bele et al., 2013). In Lake Victoria Basin, collective action has increased as a result of HIV/AIDS and climate change, boosting social assets (Gabrielsson and Ramasar, 2012). Lessons from Hurricane Mitch (1998) in Honduras point toward more equitable land distribution and better flood preparedness that benefit the poor after disasters (McSweeney and Coomes, 2011). 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. [INSERT FIGURE 13-5 HERE Figure 13-5: Multidimensional vulnerability driven by intersections dimensions of inequality.] _____ START BOX 13-1 HERE _____ 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 climaterelated disasters intertwined with socioeconomic, institutional, cultural, and political drivers that perpetuate differential vulnerabilities (robust evidence) (Lambrou and Paina, 2006; Brouwer et al., 2007; Shackleton et al., Subject to Final Copyedit 12 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 13 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 2007; Adger et al., 2007; Carr, 2008; Galaz et al., 2008; Osbahr et al., 2008; Demetriades and Esplen, 2008; Buechler, 2009; Nightingale, 2009; Terry, 2009; Dankelman, 2010; MacGregor, 2010; Alston, 2011; Arora-Jonsson, 2011; Resurreccion, 2011; Zotti et al., 2012; Heckenberg and Johnston, 2012; Shah et al., 2013; Alston and Whittenbury, 2013; Rahman, 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; AroraJonsson, 2011). Gendered livelihood impacts: Men and women are differentially affected by climate variability and change. The ten-year drought in Australia’s Murray-Darling Basin differentially affected men and women, due 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, e.g., 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). Occupational hazards: Increasing cases of heat death are reported among male workers on sugarcane plantations in El Salvador due to kidney failure (Peraza et al., 2012) and heat-related indoor work emergencies in Spain among young (<50) able-bodied urban men (García-Pina et al., 2008). Anecdotal evidence suggests that women tea pickers in Malawi, Kenya, India, and Sri Lanka suffer and die from heat stress as payment by quantity discourages rest breaks (Renton, 2009) (see also Chapter 11 and CC-HS). In cases of male outmigration due to unsustainable rural livelihoods, women in Bangladesh face unsafe working conditions, exploitation, and loss of respect (Pouliotte et al., 2009). Yet, male outmigration could provide opportunities for women to move beyond traditionally constrained roles, explore new livelihood options, and access public decision-making space (CIDA, 2002; Fordham et al., 2011). 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, due to greater stress and tension, loss and grief, and disrupted safety nets, reported for Australia (Anderson, 2009; Alston, 2011; Subject to Final Copyedit 13 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 13 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 Parkinson et al., 2011; Whittenbury, 2013; Hazeleger, 2013), New Zealand (Houghton, 2009), the U.S. (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 socio-economically 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). [INSERT TABLE 13-1 HERE Table 13-1: Examples of gendered climate experiences.] _____ END BOX 13-1 HERE _____ Medium evidence highlights impacts of climate stresses and extreme events on children (Cutter et al., 2012; O'Brien et al., 2012). Children in urban slums suffer from inadequate water supplies and malnutrition, which exacerbates impacts from heat stress, while excessive rain heightens water-borne diseases (Bartlett, 2008). Flood-related mortality in Nepal was twice as high for girls as for women (13.3 per 1,000 girls) and also higher for boys than for men, and for young children in general six times higher than before the flood (Pradhan et al., 2007). Lower caloric intake due to two back-to-back droughts and price shocks in Zimbabwe in the 1980s resulted in physical stunting among children and reduced lifetime earnings (Alderman, 2010). In Mali, the incidence of child food poverty increased from 41% to 52% since the 2006 food price increases (Bibi et al., 2010). See Chapter 11 for more details. Health impacts of weather events and climate differentially affect the elderly and socially isolated (Frumkin et al., 2008) (see also Chapter 11). In Vietnam the elderly, widows, and disabled people, in addition to single mothers and women-headed households with small children, were least resilient to floods and storms and slow-onset events such as recurrent droughts (Campbell et al., 2009). In Australia, older citizens have shown feelings of distress as a result of familiar landscapes altered by drought, loss of home gardens, social isolation, and physical harm related to heat stress and wild fires (Pereira and Pereira, 2008; Horton et al., 2010; Polain et al., 2011). Elderly citizens in the U.K. may underestimate the risk and severity of heat waves through their social networks and fail to act (Wolf et al., 2010). In the U.S., Europe, and South Korea, the elderly, children, and persons of lower socio-economic status have a heightened risk of heat-related mortality (Baccini et al., 2008; Balbus and Malina, 2009; Son et al., 2012). Preliminary evidence suggests differential harm of 2012 Superstorm Sandy in New York, observed among elderly people and medically underserved populations (Pagán Motta, 2013; Teperman, 2013; Uppal et al., 2013). Inequality and disproportionate effects of climate-related impacts also occur along the axes of indigeneity and race. Disproportionate climate impacts are documented for Afro-Latinos and displaced indigenous groups in urban Latin America (Hardoy and Pandiella, 2009), and indigenous peoples in the Russian North (Crate, 2013) and the Andes (Andersen and Verner, 2009; Valdivia et al., 2010; McDowell and Hess, 2012; Sietz et al., 2012). See Chapter 12 for impacts on indigenous cultures. In the U.S., low-income people of color are more affected by climate-related disasters (Sherman and Shapiro, 2005; Morello-Frosch et al., 2009; Lynn et al., 2011) as demonstrated in the case of low-income African-American residents of New Orleans after Hurricane Katrina (Elliott and Pais, 2006). 13.2.2. Understanding Future Impacts of and Risks from Climate Change on Livelihoods and Poverty Future climate change, as projected through modeling, will continue to affect poor people in rural and urban areas in LICs, MICs, and HICs, alter their livelihoods, and make efforts to reduce poverty more difficult (high confidence). Studies reveal a broad range of impacts for the near- (2030-2040) and long-term (2080-2100) future, depending on the climatic, agro-economic, and demographic models employed, their key variables, and spatial scale, which vary from a country’s agro-ecological zones to the global. Few projections take into account policy options or adaptation. Subject to Final Copyedit 14 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 13 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 Projections emphasize the complexity and heterogeneity of future climate impacts, including winners and losers in close geographic proximity. Anticipated impacts on the poor are expected to interact with multiple stressors, most notably social vulnerability (Iglesias et al., 2011), low adaptive capacity and subsistence constraints under chronic poverty (Liu et al., 2008), weak institutional support (Menon, 2009; Xu et al., 2009; Skoufias et al., 2011a; Skoufias et al., 2011b), population increases (Müller et al., 2011), natural resource dependence (Adano et al., 2012), ethnic conflict and political instability (Challinor et al., 2007; Adano et al., 2012), large-scale land conversions (Assuncao and Cheres, 2008; Thornton et al., 2008), and inequitable trade relations (Challinor et al., 2007; Jacoby et al., 2011). Table 13-2 illustrates estimated risks and adaptation potentials for livelihoods and poverty dimensions until 2100. [INSERT TABLE 13-2 HERE Table 13-2: Key risks from climate change for poor people and their livelihoods and the potential for risk reduction through adaptation. Key risks are identified based on assessment of the literature and expert judgment by chapter authors, with evaluation of evidence and agreement in the supporting chapter sections. Each key risk is characterized as very low, low, medium, high, or very high. Risk levels are presented in three timeframes: present, near-term (2030-2040), and long-term (2080-2100). Near-term indicates that projected levels of global mean temperature do not diverge substantially across emissions scenarios. Long-term differentiates between a global mean temperature increase of 2°C and 4°C above preindustrial levels. For each timeframe, risk levels are estimated for a continuation of current adaptation and for a hypothetical highly adaptive state. Bars that only show the latter indicate a limit to adaptation (see Chapter 16). Relevant climate variables are indicated by symbols. This table should not be used as a basis for ranking severity of risks.] 13.2.2.1. Projected Risks and Impacts by Geographic Region Climate change will exacerbate risks and in turn further entrench poverty (very high confidence). The well known and highly referenced Wheeler data set (2011) analyzes climate risk and coping ability by country. Future increases in the frequency of extreme events are overlaid with considerable poverty, although not all poor people will be at risk. Of the 20 countries and regions most at risk, seven are LICs (Bangladesh, Ethiopia, Kenya, Madagascar, Mozambique, Somalia, and Zimbabwe), eight are LMICs (Bolivia, Djibouti, Honduras, India, Philippines, Sri Lanka, Vietnam, and Zambia), four are UMICs (China, Colombia, Cuba, and Thailand), and one is a HIC (Hong Kong). For China, Djibouti, India, Kenya, and Somalia, climate contributes between 46.4% and 87.5% to a 20082015 rise in national risk, compared to income and urbanization. Highest sensitivity to sea level rise by 2050, based on low-elevation coastal zones, population density, and areas of storm surge zones, is expected for India, Indonesia, China, the Philippines, and Bangladesh. India and Indonesia are projected to experience a 80% and 60% increase, respectively, in their populations at risk from sea level rise, housing a combined total of >58 million people most at risk by 2050; six million people more at risk from sea level rise in China will bring its total to 22 million, and Bangladesh’s at-risk population is predicted to grow to 27 million – more than double since 2008 (Wheeler, 2011). Specific regions at high risk are those exposed to sea-level rise and extreme events and with concentrated multidimensional poverty, including pockets of poor people in LICs and MICs: mega-deltas in Bangladesh, Thailand, Myanmar, and Vietnam (Eastham et al., 2008; Wassmann et al., 2009), drylands (Anderson et al., 2009; Piao et al., 2010; Sietz et al., 2011), mountain areas (Beniston, 2003; Valdivia et al., 2010; Gerlitz et al., 2012; McDowell and Hess, 2012; Gentle and Maraseni, 2012), watersheds in the Himalayas (Xu et al., 2009), ecologically-fragile areas in China (Taylor and Xiaoyun, 2012), coastal areas with severe ecosystem deterioration in eastern and southern Africa (Bunce et al., 2010a; Bunce et al., 2010b) and river deltas subject to resource extraction (Syvitski et al., 2009). 13.2.2.2. Anticipated Impacts on Economic Growth and Agricultural Productivity Most projected future impact studies focus on the long-term effects of climatic changes and shocks on agricultural productivity, mainly in Africa, Asia, and Latin America. They typically examine impacts on economic growth (see also Chapter 10), changes in food prices and food security, and extrapolated changes in poverty head counts. Subject to Final Copyedit 15 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 13 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 For future poverty head counts caused by climate change, the literature shows disagreement. For the very near future, a study by Thurlow et al. (2009) estimates that, by 2016, Zambia’s poverty headcount would increase by 300,000 people under average climate variability, and by 650,000 under a worst ten-year rainfall sequence. Skoufias et al. (2011b), using 2055 predictions based on the Nordhaus (2010) RICE model, state that under business-as-usual and optimal abatement, global poverty (measured at $2/day) could be reduced by 800 million people, due to annual and real per capita growth rate of 2.2% up to 2055. However, lower probability extreme events would reverse this trend, and mitigation under optimal abatement typically excludes people living in poverty (Skoufias et al., 2011b). In contrast, Tubiello et al. (2008) project that, by 2080, the number of undernourished people may increase by up to 170 million, using the A2 SRES scenarios, and up to a total of 1,300 million people assuming no CO2 fertilization. Projections of future climate change impacts on GDP use non-disaggregated poverty data. For instance, Mendelsohn et al. (2006) use dynamic coupled ocean–atmosphere models and market response functions to simulate the distribution of climate impacts for 2100. Independent of the climate scenarios, poor countries, mainly in Africa and Southeast Asia, will face the largest losses (0.2-1.2% reduction in GDP) and, under experimental models, up to 23.8% drop in GDP; in contrast, the richest quartile will encounter both positive and negative effects, ranging -0.1% to +0.2% GDP, and up to a 0.9% GDP increase under experimental models. Changes in GDP reflect climatesensitive economic sectors, especially water and energy, with poor nations in low latitudes already facing high temperatures and thus more vulnerable to decreased agricultural productivity with increased warming. One study for the U.S., using the SRES A2 scenario, projects that four climate change impacts − hurricane damage, energy costs, water costs, and real estate − are expected to cost 1.8% of the country’s GDP by 2100, leading to higher household costs for basic necessities like energy and water (Ackerman et al., 2008). Groups that spend the highest proportion of their income on these necessities will be disproportionately affected. A growing body of literature estimates future changes in agricultural production and food prices due to climate change, variability, and extreme events (Slater et al., 2007; Thomas et al., 2007; Assuncao and Cheres, 2008; Burke et al., 2011) (see Chapters 7, 9, and CC-HS). Mixed trends are projected for major staples for all continents until the mid-21st century. For the near-term future, the production of coarse grains in Africa may be reduced by 17-22% due to climate change; well-fertilized modern seed varieties are projected to be more susceptible to heat stress than traditional ones (Schlenker and Lobell, 2010). By 2080, a major decrease in land productivity is expected for subSaharan Africa (-14% to -27%) and Southeast Asia (-18% to -32%), coupled with increase in water demand, while lowest risks are projected for North America, Europe, East Asia, Russia, and Australia (Iglesias et al., 2011). 13.2.2.3. Implications for Livelihood Assets, Trajectories, and Poverty Dynamics Projections of near- and long-term climate change impacts on livelihood assets highlight the erosion of financial assets as a result of increased food prices (Thurlow et al., 2009; Seo et al., 2009; Ahmed et al., 2009; Hertel et al., 2010; Jacoby et al., 2011; Skoufias et al., 2011b), human assets due to decline in nutritional status (Liu et al., 2008), and natural assets due to lower agricultural productivity (Thurlow et al., 2009; Jones and Thornton, 2009; Skoufias et al., 2011b). They also show a substantial increase in future heat-related mortality (Basu and Samet, 2002; McGregor et al., 2006; Sherwood and Huber, 2010; Huang et al., 2011), increasing infectious disease transmission rates (Green et al., 2010), and other health impacts (see Chapter 11). Impacts on social and cultural assets have received little attention. Exceptions address losses of social identity and cultural connections with land and sea among indigenous populations threatened by sea level rise and potential relocation (Green et al., 2010) and conflicts between ethnic and/or religious groups (Adano et al., 2012) (see Chapter 12). Poor households with limited social networks will be worst off, including in places such as Nepal (Menon, 2009) and Indonesia (Skoufias et al., 2011a). Climate change is also projected to cause shifts in livelihood trajectories. In Mali’s agricultural-pastoralist transition zone, due to temperature increase and drying projected for 2025 and coupled with a 50% increase in population, shifts from rain-fed millet and sorghum to semi-arid, predominantly livestock subsistence are expected to expose an extra six million people to malnutrition, including 250,000 children suffering from stunting (Jankowska et al., 2012). Simulated probabilities of failed seasons, using current daily rainfall data and 2050 projections for the length of growing period, show transitions from cropping to livestock in other marginal cropping areas in Africa (Thomas Subject to Final Copyedit 16 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 13 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 et al., 2007; Jones and Thornton, 2009). The HadCM3 and A1F1 models show that, by 2050, expanding vector populations, especially tsetse, and a >20% decline in growing period, in livestock-dependent and mixed croplivestock livelihoods in semi-arid to arid Africa and Asia, combined with increasing water scarcity and stover loss due to maize substitution (Thornton et al., 2007) will stress livelihoods of poor farmers and pastoralists. Future climate change impacts on disaggregated poverty are mainly addressed through projected changes in food prices and earnings associated with impacts on agricultural production (Schmidhuber and Tubiello, 2007). Changes in price-induced earnings lower the welfare of low-income households, particularly urban and wage-labor dependent households that use a large income share to purchase staple crops. In the near-term future, under low productivity scenarios assuming rapid temperature increase by 2030, poverty among the agricultural self-employed in 15 LICs and MICs may drop due to benefits from selling surplus production at higher prices, by as much as 40% in Chile and the Philippines; however, higher food prices may lead to a drop in national welfare, as steep as 55% in South Africa (Hertel et al., 2010). In most LICs and MICs, the poverty headcount is expected to drop in some occupational strata and increase in others; only in most African countries are yield impacts expected to be too severe to allow benefits (Hertel and Rosch, 2010). Long-term, a one-time maximum extreme dry event, simulated for 1971-2000 and 20712100 using the IPCC-SRES A2 scenario for 16 LICs and MICs, shows a 95-110% raise in poverty for urban wage groups in Malawi, Zambia, and Mexico, while self-employed farming households consolidate assets and face the smallest increase in vulnerability (Ahmed et al., 2009). By 2100, climate change would leave low-income, minority, and politically marginalized groups in California’s agriculture with fewer economic opportunities, based on SRES B1 and A1Fi scenarios, particularly in dairy and grape production (Cordova et al., 2006; Shonkoff et al., 2011). 13.2.2.4. Impacts on Transient and Chronic Poverty, Poverty Traps, and Thresholds Existing projections do not provide robust evidence to estimate whether shifts from transient to chronic poverty will occur as a result of climate change, and to what extent. However, a predicted increase in the number of urban poor, especially wage laborers, suggests that a large number may shift from transient to chronic poverty due to exposure to food price increases, or find themselves in a poverty trap, especially under scenarios with long-duration climatic shifts and prolonged droughts (Ahmed et al., 2009; Hertel et al., 2010). In Zambia, almost half of the 650,000 new poor under the worst historic 10-year period projected till 2016 are expected to be in urban areas while rural poverty remains high (Thurlow et al., 2009). In Tanzania, Ahmed et al. (2011), based on a high precipitation volatility GCM, predict up to 1.17 million new poor into the near-term future (up to 2031). Shifts in and out of poverty may occur by 2050 for small-scale coffee farmers in Central America, as suitable coffee growing areas move to higher altitudes, especially when constrained by unequal access to agro-technical and climatic information (Laderach et al., 2011). Poor countries will face greater poverty as a result of climate change and extreme events (medium confidence), due to location and low-latitude high temperatures (Mendelsohn et al., 2006) anticipated further decline in adaptive capacity combined with reductions in agricultural productivity (Iglesias et al., 2011), greater inequality and deeprooted poverty (Jones and Thornton, 2009), and lower levels of education and large numbers of young dependents (Skoufias et al., 2011c). Although robust projections on poverty traps are lacking, they may be associated with emerging hotspots of hunger, such as those projected for Tanzania, Mozambique, and the Democratic Republic of Congo (DRC) by 2030 (Liu et al., 2008). Based on SRES scenarios, Devitt and Tol (2012) project long-term coupled climate change- and conflict-induced poverty traps for the DRC and several other sub-Saharan countries. Some climate change projections (see CC-HS and WG1 Chapters 11, 12, and 14) indicate the possibility of large impacts that may exceed thresholds of detrimental shocks to livelihoods and poverty, unless strong adaptation and/or mitigation responses are implemented in a timely manner (Kovats and Hajat, 2008; Sherwood and Huber, 2010). Since women do most of the agricultural work, they will suffer disproportionally from heat stress; for instance, in parts of Africa, women carry out 90% of hoeing and weeding and 60% of harvesting work (Blackden and Wodon, 2006). Toward the end of the century, the risk of heat stress may become acute in parts of Africa, particularly the Sahel, and the Indian sub-continent, potentially preventing people from practicing agriculture (Patricola and Cook, 2010; Dunne et al., 2013). In the glacier-dependent Himalayan region, excessive runoff and flooding will threaten livelihoods (Xu et al., 2009). Relocation would represent a critical threshold for indigenous groups, due to sea level Subject to Final Copyedit 17 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 13 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 rise for the Torres Strait Islanders between Australia and Papua New Guinea (Green et al., 2010) and permafrost degradation and higher and seasonally erratic precipitation for the Viliui Sakha in the Russian North (Crate, 2013). 13.3. Assessment of Impacts of Climate Change Responses on Livelihoods and Poverty Climate change responses interact with social and political processes to affect sustainable development and climate resilient pathways (Chapter 20), and in turn, livelihoods and poverty. Climate mitigation and adaptation responses include formal policies by governments, NGOs, bilateral and multilateral organizations as well as actions by individuals and communities. Such policy responses were designed to have positive effects on sustainable development or at least be neutral in terms of unintended side effects. Yet, much of the peer-reviewed literature scrutinizing these responses suggests otherwise. This section reviews empirical evidence of impacts of particular mitigation (13.3.1) and adaptation (13.3.2) responses in the context of livelihood and poverty trajectories and inequalities. Some of this evidence is preliminary as several policies are still in their infancy while other cases fail to assess multidimensional poverty or dynamic livelihood decision making in the context of climate change responses. 13.3.1. Impacts of Mitigation Responses Many synergies between climate change mitigation policies and poverty alleviation have been identified in the literature (Klein et al., 2005; Ürge-Vorsatz and Tirado Herrero, 2012), but evidence of positive outcomes is limited. Impacts of current mitigation policies on livelihoods and poverty are controversial with polarized views on the potential of such policies for sustainable development in general and poverty alleviation in particular (Collier et al., 2008; Böhm, 2009; Hertel and Rosch, 2010; Michaelowa, 2011). This section assesses the observed and potential impacts of four climate change responses on livelihoods and poverty: the two mitigation responses most significant for poverty alleviation under the UNFCCC, the CDM and REDD+, and two mitigation responses outside of the UNFCCC, voluntary carbon offsets and biofuel production. 13.3.1.1. The Clean Development Mechanism (CDM) The CDM (see Chapter 13 in WGIII) aims to promote sustainable development and thus CDM projects require approval by the host country’s designated national authority. CDM projects as diverse as low-cost energy services in India, micro-hydro projects in Bhutan and Peru, efficient firewood use in Nigeria, and biogas digesters in China and Vietnam, are expected to generate livelihood benefits and employment, and reduce poverty among beneficiaries (UNFCCC, 2011; UNFCCC, 2013). The secretariat’s own assessment of the CDM’s development benefits along 15 indicators suggested much room for improvement (UNFCCC, 2011). Most of the statistical information in official reports on CDM is based either on project documents or on surveys of project personnel rather than in-depth studies. The assessment of the CDM in the peer-reviewed literature is more cautious and pessimistic than UNFCCC, and three reviews (Olsen, 2007; Sutter and Parreño, 2007; Michaelowa and Michaelowa, 2011) contend that the current CDM design is neither pro-poor nor contributes to sustainable development. One reason for the low performance on sustainable development criteria is that the CDM does not have any requirements for monitoring and verification of development impacts as required for emissions reductions (Boyd et al., 2009). Critiques entail obstacles and ethical dilemmas in carbon trading (Liverman, 2009; Newell and Bumpus, 2012), difficulties with implementation (Borges da Cunha et al., 2007; Minang et al., 2007; Gong, 2010), procedural limitations (Lund, 2010), and carbon offset goals favored over poverty reduction goals (Wittman and Caron, 2009). While some authors claim that the CDM undermines local and non-governmental input (Shin, 2010; Corbera and Jover, 2012), others stress its transparency, including the voices of local stakeholders (Michaelowa et al., 2012). Also, the CDM may compete with the informal sector (Newell and Bumpus, 2012) and accentuate uneven development by eroding local livelihood security (Boyd and Goodman, 2011). In a meta-analysis of 114 CDM projects, Crowe (2013) conclude that <10% of CDM projects had successfully delivered pro-poor benefits and only one of them had positive ratings on all seven criteria for propoor benefits. Among the most promising examples are CDM projects in India supporting community-designed plans to strengthen participation of marginalized groups (Subbarao and Lloyd, 2011; Boyd and Goodman, 2011). Subject to Final Copyedit 18 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 13 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 13.3.1.2. Reduction of Emissions from Deforestation and Forest Degradation (REDD+) Experience with REDD+ and other forest carbon projects is inadequate to permit generalizations about effects on livelihoods and poverty (Cotula et al., 2009; Hayes and Persha, 2010; Springate-Baginski et al., 2010) (see Chapter 9). A study of 20 avoided deforestation projects prior to REDD+ in Latin America, Africa, and Asia shows that only five conducted some outcome or impact assessment, revealing a lack of rigor in evaluation (Caplow et al., 2011). Despite optimism in policy analyses about the potential of REDD+ for poverty alleviation (Angelsen et al., 2009; Kanowski et al., 2011; Rahlao et al., 2012; Somorin et al., 2013), there is growing evidence and high agreement in the peer-reviewed literature that REDD+ may not lead to poverty alleviation and that there may even be negative consequences. Concerns include threats to the poor (Phelps et al., 2010; Ghazoul et al., 2010; Larson, 2011; Van Dam, 2011; McDermott et al., 2011; Börner et al., 2011; Neupane and Shrestha, 2012; Mahanty et al., 2012) and indigenous peoples (Shankland and Hasenclever, 2011). 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 (UN-REDD, 2011; Peach Brown, 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). The 2010 Cancun Agreements highlight safeguards for governments to observe in REDD+ implementation, such as respect for the interests, knowledge, rights, and sustainable livelihoods of communities and indigenous peoples. If these safeguards will be observed in practice is unclear due to the early implementation state of REDD+ in most countries as well as the uncertainty of the future of the global carbon market (Lohmann, 2010; Savaresi, 2013). 13.3.1.3. Voluntary Carbon Offsets The voluntary carbon offset (VCO) market is significant from a livelihoods and poverty perspective because it typically targets smaller projects and may be better at reaching poor communities (Estrada and Corbera, 2012), though it is modest in size compared to the regulated market (~1%). Also, those involved in the VCO market, namely individuals, companies, organizations, and countries that have not ratified the Kyoto Protocol, are often more willing to pay for carbon offsets with co-benefits such as poverty alleviation (MacKerron et al., 2009). Activities under VCO are dominated by renewable energy, primarily wind power (30%), forestation projects, including REDD+ (19%), and methane destruction in landfills (7%) (Peters-Stanley and Hamilton, 2012). It is too early to tell whether these VCO projects are successful in terms of poverty alleviation and other social goals, and results to date are highly mixed (Jindal et al., 2008; Swallow and Meinzen-Dick, 2009; Jindal, 2010; Estrada and Corbera, 2012; Stringer et al., 2012). Reported benefits include livelihood diversification, increased disposable income, biodiversity conservation, and strengthening local organizations, while exacerbated inequalities and loss of access to local resources are known negative impacts (Estrada and Corbera, 2012). A study in Kenya, Senegal, and Peru shows reduced losses of soil fertility in three soil carbon sequestration projects, but also the inability of the poorest farmers to participate and only marginal impacts on poverty reduction (Antle and Stoorvogel, 2009). Out of 78 projects in 23 countries in sub-Saharan Africa, only one promoted local social, economic, and environmental benefits while the rest focused mainly on efficiency of emission reductions (Karavai and Hinostroza, 2013). 13.3.1.4. Biofuel Production and Large-Scale Land Acquisitions Biofuel production, often linked to transnational large-scale land acquisitions (LSLA), is a near-term climate change mitigation response that raises two major livelihood and poverty concerns: food price increases and dispossession of Subject to Final Copyedit 19 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 13 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 land (see Chapters 4 and 9). LSLA have soared since 2008 (Von Braun et al., 2009; Deininger et al., 2011; Borras Jr et al., 2011), partly linked to climate change responses (medium evidence, high agreement). Biofuel production is considered the primary driver, but there may be links to climate change through high food prices (Daniel, 2011), food insecurity (Robertson and Pinstrup-Andersen, 2010; Rosset, 2011; Sulser et al., 2011), and carbon markets potentially raising land prices, e.g. REDD+ (Cotula et al., 2009; Zoomers, 2010; Anseeuw et al., 2012). LSLA global targets are biofuels (40%), food (25%) and forestry (3%), with much regional variation (Anseeuw et al., 2012). The IPCC special report on renewable energy highlighted the uncertainties around the role of biofuels in food price increases and risks of deteriorating food security with future deployment of bioenergy (Edenhofer et al., 2011). Increasing demand for biofuels shifts land from food to fuel production, which may increase food prices (Collier et al., 2008) disproportionally affecting the poor (Von Braun and Ahmed, 2008; Ruel et al., 2010; Bibi et al., 2010). Despite high agreement that biofuel production plays a role in food prices, little consensus exists on the size of this influence (Von Braun and Ahmed, 2008; Mitchell, 2008; Aksoy and Isik-Dikmelik, 2008; Elobeid and Hart, 2008; Baffes and Haniotis, 2010; Ajanovic, 2011; Condon et al., 2013). Some studies link the 2007/08 price spike to speculation in agricultural futures markets (Runge and Senauer, 2007; Ghosh, 2010) driven partly by potential future profits from biofuels while their role was relatively less important in the 2010/11 price spike (Trostle et al., 2011). 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; Borras Jr et al., 2011; 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; Montefrio and Sonnenfeld, 2013; Manik et al., 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 (Molony, 2011; Arndt et al., 2011; Chu, 2011; Julia and White, 2012; Behrman et al., 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., 2011). Mainstream economic modeling offers optimism that biofuels may boost investment, employment, and economic growth, in LICs such as Mozambique (Arndt et al., 2009) and MICs such as India (Gopinathan and Sudhakaran, 2011) and Thailand (Silalertruksa et al., 2012) yet limited evidence exists on potential benefits being realized. A major government initiative to promote jatropha cultivation in India has failed (Kumar et al., 2011) and in some cases has left rural people worse off (Bastos Lima, 2012), whereas in Malawi it offered supplemental livelihood opportunities (Dyer et al., 2012). Even though income and employment in Brazil may have increased due to ethanol production (Ferreira and Passador, 2011), structural inequalities in the sector remain (Peskett, 2007; Hall et al., 2009; Bastos Lima, 2012). Biofuel production in itself will not transform living conditions in rural areas without being integrated into development policies (Hanff et al., 2011; Jarosz, 2012; Dyer et al., 2012). 13.3.2. Impacts of Adaptation Responses on Poverty and Livelihoods Local responses to climate variability, shocks, and change have always been part of livelihoods (Morton, 2007). Formal policy responses to climate change, however, have developed more recently as the urgency of adaptation, in addition to mitigation, became a clear international policy mandate (Pielke Jr et al., 2007). Even well-intentioned adaptation projects (see Chapters 14-16) and efforts may have unintended and sometimes detrimental impacts on livelihoods and poverty, and may exacerbate existing inequalities. This section assesses the near-term effects of autonomous and planned adaptation and formal insurance schemes on the livelihoods of poor populations. Since adaptation policies and projects are relatively recent, understanding of their long-term effects is very limited. Subject to Final Copyedit 20 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 13 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 13.3.2.1. Impacts of Adaptation Responses on Livelihoods and Poverty Autonomous adaptation strategies, such as diversification of livelihoods (Smith et al., 2000; Mertz et al., 2009) migration (McLeman and Smit, 2006; Tacoli, 2009) (see Chapter 12), storage of food (Smit and Skinner, 2002; Howden et al., 2007) communal pooling (Linnerooth-Bayer and Mechler, 2006), market responses (Halstead and O'Shea, 2004), and saving, credit societies, and systems of mutual support (Andersson and Gabrielsson, 2012) have been found to have positive effects on poverty reduction in certain contexts, or at least prevent further deterioration due to weather events and climate, especially when supported by policy measures (Adger et al., 2003; Urwin and Jordan, 2008; Stringer et al., 2009). Yet, some autonomous strategies such as diversification and storage are often unavailable to the poorest, who lack the required resources or surplus (Smithers and Blay-Palmer, 2001; Osbahr et al., 2008; Seo, 2010) or require more labor-intensive practices that undermine people’s health and may push them over a poverty threshold (Eriksen and Silva, 2009). Moreover, autonomous adaptation strategies can increase vulnerability for others or be subject to local elite capture (McLaughlin and Dietz, 2008; Eriksen and Silva, 2009; Bhattamishra and Barrett, 2010). Men’s migration in Northern Mali, for example, increases the workload of the rest of the family, especially women, and reduces children’s school attendance (Brockhaus et al., 2013). There is no evidence regarding the impacts of autonomous responses on people living in poverty in MICs and HICs. 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 and Agrawala, 2006; Gigli and Agrawala, 2007). An assessment of the only completed 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 Karnataka Watershed, 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). 13.3.2.2. Insurance Mechanisms for Adaptation Insurance mechanisms (see Glossary and Chapter 10) reflect the tendency that some formal adaptation measures reach the wealthier more easily while prohibitive costs may prevent poor people from accessing such mechanisms. Nonetheless, public and private insurance systems have been proposed by the World Bank and UNFCCC as an adaptation strategy to reduce, share, and spread climate change-induced risk and smooth consumption, especially among poor households (Mechler et al., 2006; Hertel and Rosch, 2010; Akter et al., 2011; Benson et al., 2012). Formal insurance schemes can potentially provide a way out of poverty traps (Barnett et al., 2008) caused by a household’s process to rebuild assets after climate shocks over years (Dercon, 2006; Hertel and Rosch, 2010). Poor people tend not to be insured via formal institutions, though strategies such as risk spreading, social networks, local credit, asset markets, and dividing herds between kin act as informal risk management mechanisms (Barnett et al., 2008; Pierro and Desai, 2008; Giné et al., 2008; Hertel and Rosch, 2010; De Jode, 2010). Unable to access insurance, they often invest in low-risk, low-return livelihood activities, which makes asset accumulation to escape chronic poverty very difficult (Elbers et al., 2007; Barnett et al., 2008). As a response, new insurance mechanisms such as micro-insurance directed at low-income people and weather index insurance for crops and livestock (see also Chapter 10) have emerged, showing mixed results (Barnett et al., 2008; Mahul et al., 2009; Akter et al., 2011; Matsaert et al., 2011; Biener and Eling, 2012). Experiences from South Asia and several African countries illustrate positive effects of micro-insurance on investment, production, and income under drought and flood risk, including possible longer-term impacts on future income- earning activities and health, although affordability may limit the potential for the poorest (Yamauchi et al., 2009; Hochrainer-Stigler et al., 2012; Karlan et al., 2012; Tadesse and Brans, 2012). There is emerging evidence that weather index insurance can be specifically designed to reach the people usually uninsurable for example by premium-for-work arrangements. In such arrangements farmers provide labor and in return get an insurance certificate against rain failure in a crucial growth period for their staple crops (Brans et al., 2011). Slow uptake of insurance among poor people may be related to farmers not fully understanding the schemes’ merits and function or not trusting that payouts will come (Giné and Yang, 2009; Patt et al., 2010). Subject to Final Copyedit 21 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 13 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 13.4. Implications of Climate Change for Poverty Alleviation Efforts This section assesses how climate change may affect efforts to alleviate poverty. Evidence from observed impacts and projections highlight both challenges and opportunities. The section builds on the findings from 13.1 to 13.3 and stresses the need to take into account the complexity of livelihood dynamics, multidimensional poverty, and intersecting inequalities to successfully navigate climate-resilient development pathways (see Glossary). Observed impacts of weather events and climate on livelihoods and poverty and impacts projected from the subnational to the global level suggest that livelihood well-being, poverty alleviation, and development are already undermined and will continue to be eroded into the future (high confidence). Climate change will slow down the pace of poverty reduction, jeopardize sustainable development, and undermine food security (high confidence) (Stern, 2009; Hope, 2009; Thurlow et al., 2009; Iglesias et al., 2011; Skoufias et al., 2011b). Currently poor and food-insecure regions will continue to be disproportionately affected into the future (high agreement) (Challinor et al., 2007; Lobell et al., 2008; Assuncao and Cheres, 2008; Liu et al., 2008; Thornton et al., 2008; Menon, 2009; Jones and Thornton, 2009; Nordhaus, 2010; Jacoby et al., 2011; Burke et al., 2011; Skoufias et al., 2011a; Adano et al., 2012). Poorer countries will experience declining adaptive capacity, which will hamper development (high confidence). Posey (2009) flags lower adaptive capacities in communities with concentrations of racial minorities and low-income households than in more affluent areas, due to marginalization and multidimensional inequality. Iglesias et al. (2011) project continental disparities in agricultural productivity under progressively severe climate change scenarios with highest risks for Africa and Southeast Asia. Although there is high agreement about the heterogeneity of future impacts on poverty, few studies consider more diverse climate change scenarios (Skoufias et al., 2011b) or the potential of four degrees and beyond (New et al., 2011). The World Bank (2012b, p.65) states that “climate change in a four degree world could seriously undermine poverty alleviation in many regions.” 13.4.1. Lessons from Climate-Development Efforts Two key models have attempted to integrate climate and poverty concerns into development efforts: mainstreaming adaptation into development priorities and pro-poor adaptation (see Chapters 14-16, 20). Lessons from “adaptation as development,” in which development is seen as the basis for adaptation, and “adaptation plus development,” in which development interventions address future climate threats (Ayers and Dodman, 2010), typify the disagreement in policy spheres about what sustainability constitutes (Le Blanc et al., 2012) and the practical gulf between climate change policy and development spheres (Ayers and Dodman, 2010). To date, observed and projected climate change impacts are not systematically integrated into poverty reduction programs, although such integration could result in substantial resilience to covariate and idiosyncratic shocks and stresses (Brans et al., 2011; Béné et al., 2012). At the same time, science and policy emphasis on rapid-onset events, sectoral impacts, and poverty statistics has diverted attention from threats to sustainability and resilient pathways. Even where legal reforms to secure the rights of poor people exist, as in Mexico’s Climate Law, inequalities persist (MacLennan and Perch, 2012). Without addressing the climatic, social, and environmental stressors that shape livelihood trajectories, including poverty traps (see Figure 13-2), and the underlying causes of poverty, persistent inequalities, and uneven resource access and institutional support, adaption efforts and policies will be nothing more than temporary fixes. Poverty alleviation alone will not necessarily lead to more equality (Pogge, 2009; Milanovic, 2012). Box 13-2 provides insight into three examples. _____ START BOX 13-2 HERE _____ Box 13-2. Lessons from Social Protection, Disaster Risk Reduction, and Energy Access Social protection (SP): Considerable challenges emerge at the intersection of climate change adaptation, disaster risk reduction, and social protection. SP programs include public and private initiatives that transfer income or assets to poor people, protect against livelihood risks, and raise the social status and rights of the marginalized (see Glossary). Cash transfer programs are among the principal instruments used by governments for poverty alleviation (Barrientos and Hulme, 2009; Niño-Zarazúa, 2011; Barrientos, 2011). There is medium agreement among scholars Subject to Final Copyedit 22 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 13 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 and practitioners that SP helps people in chronic poverty reduce risk and protect assets during crises (Devereux et al., 2010; Barrientos, 2011; Dercon, 2011; Devereux et al., 2011). At the regional and municipal level, SP often fails to address local government capacity to ensure risk reduction by providing water, sanitation, drainage, health care, and emergency services. Also, SP does not intentionally strengthen local collective capacity to proactively address climate change risks and take action (Satterthwaite and Mitlin, 2013). SP that supports pro-poor climate change adaptation and disaster risk reduction by strengthening the resilience of vulnerable populations to shocks is labeled “adaptive social protection” (ASP) (Davies et al., 2009). ASP should be understood as a framework rather than a package of specific measures. ASP has almost exclusively focused on LICs and some MICs with very little attention to poor people in HICs. Few studies exist on the effectiveness of ASP for addressing incremental climatic changes and rapid-onset events, and the changing nature of climate risks as part of dynamic livelihood trajectories (Heltberg et al., 2009; Arnall et al., 2010; Bee et al., 2013). The Productive Safety Net Program in Ethiopia, for instance, had positive effects on household food consumption and asset protection (Devereux et al., 2006; Slater et al., 2006). Yet, this and programs such as Brazil’s Bolsa Familia and Bolsa Verde (UNDP, 2012) offer few concrete pathways to tackling systemic vulnerabilities and inequalities that inhibit effective responses to severe shocks, though they stress the role of local governments in addressing long-term livelihood security and well-being in addition to short-term disaster relief (Gilligan et al., 2009; Conway and Schipper, 2011; Béné et al., 2012; UNDP, 2012). Local governments in urban contexts have limited capacities to address livelihood security, but more scope to increase resilience through risk-reducing infrastructure (Satterthwaite and Mitlin, 2013). Disaster risk reduction (DRR): The development and application of DRR (see Glossary) has been among the most important routes for highlighting risks of extreme weather among local governments and civil society, and came to the fore as the concentration of disaster deaths from extreme weather in LICs and MICs became evident (UNISDR, 2009; UNISDR, 2011). However, the accumulated effect of several small-scale events is often more damaging than large-scale ones (Aryal, 2012). DRR is now increasingly employed as an adaptation measure, for example through community-based climate risk reduction (Tompkins et al., 2008; Meenawat and Sovacool, 2011; McSweeney and Coomes, 2011; Field et al., 2012b) and has helped identify DRR roles for local governments (IFRC, 2010). Yet, sometimes disaster management-oriented adaptation can favor property and investments of the relatively richer and divert attention and funding from measures that address disadvantaged people, as suggested in a case study of Vietnam (Buch Hansen, 2013). The effectiveness of DRR in supporting pro-poor climate change adaptation will depend on governance structures to address changing risk contexts in policies and investments while responding to the needs and priorities of their low-income population. Lessons learned from Hurricane Katrina and the Tōhoku earthquake and tsunami showcase the multiplier effect of a disaster on top of underlying structural inequalities. Their persistence years later, as witnessed with Katrina (Schwartz, 2007; Zottarelli, 2008; Fussell et al., 2010) further stresses the need for expanded analyses beyond disaster events themselves and the recognition of the many factors that perpetuate the vicious cycle of poverty, multidimensional deprivation, and inequality. Energy access: Energy is critical for rural development (Barnes et al., 2010; Kaygusuz, 2011; Kaygusuz, 2012) and for alleviation of urban poverty (Parikh et al., 2012). One proposed climate-resilient pathway is to boost renewable energy use, which could increase energy access for billions of people currently without access to safe and efficient energy while cutting GHG emissions from rising non-renewable energy consumption (Casillas and Kammen, 2010; Edenhofer et al., 2011). Benefits include better health (see also Chapter 11), employment, and cost savings relative to fossil fuels (Edenhofer et al., 2011; Jerneck and Olsson, 2012). _____ END BOX 13-2 HERE _____ 13.4.2. Toward Climate-Resilient Development Pathways Given the multiple challenges at the climate-poverty-development nexus, debates increasingly focus on transforming the development pathways themselves toward greater social and environmental sustainability, equity, resilience, and justice, calling for a fundamental shift toward near- and long-term climate-resilient development pathways (see Chapter 20). This perspective acknowledges the shortcomings in dominant global development pathways, above all Subject to Final Copyedit 23 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 13 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 rising levels of consumption and emissions, privatization of resources, and limited capacities of local governments and civil society to counter these trends (Pelling, 2010; Eriksen et al., 2011; O’Brien, 2012; UN, 2012a). At Rio+20 in 2012, an Open Working Group was created by the UN General Assembly to develop Sustainable Development Goals (SDGs) building on the Millennium Development Goals (MDGs), which are criticized for not explicitly addressing the root causes of poverty, inequality, or climate change (Melamed, 2012; UN, 2012b) and the anticipated failure to reach MDG 1 (eradicate extreme poverty and hunger by 2015), with or without climate change (Tubiello et al., 2008). Early SDG debates reveal a stronger focus on eradicating extreme poverty and environmental problems facing poor people (UN, 2012a). This framing of development acknowledges shared global futures that require collective action from the richest, not merely promoting welfare for the poorest, to address both climate change and poverty (Ayers and Dodman, 2010; UN, 2012a; UN, 2012b). Little information exists to date to project how these SDGs will support climate-resilient development pathways. Formulating goals, however, will not suffice unless the global institutional framework for sustainable development is radically reformed (Biermann et al., 2012) Paying attention to dynamic livelihoods and multidimensional poverty and the multifaceted impacts of climate change and climate change responses is central to achieving climate-resilient development pathways (see Chapter 20). Evidence from sections 13.2 and 13.3 suggests that increasing global inequality, new poverty in MICs and HICs, and more people shifting from transient to chronic poverty overlaid with business-as-usual development and climate policies will bring poor and marginalized people precariously close to the two most undesirable future scenarios as conceptualized in the shared socio-economic pathways (SSPs) (see Chapter 1): social fragmentation (fragmented world) and inequality (unequal world). At the community level, inadequate governance structures and elite capture often propel less affluent households into deeper poverty. There is high agreement among scholars of global governance that fragmentation also exists at the level of the global climate regime (Biermann, 2010; Roberts, 2011; Mol, 2012), rooted in entrenched inequalities (Parks and Roberts, 2010). The extent to which fragmentation promotes positive or negative outcomes of climate and development goals is contested, ranging from polycentric governance modes (Ostrom, 2010) to conflictive fragmentation (Biermann et al., 2009; Mittelman, 2013). Evidence from this chapter suggests that, in order to move toward the mid- and long-term SSP1 (sustainability), a fundamental rethinking of poverty and development will need to emphasize equity among poor and non-poor people to collectively address GHG emissions and vulnerabilities while striving toward a joint, just, and desirable future. 13.5. Synthesis and Research Gaps Previous IPCC reports have stated that climate change would cause disproportionally adverse effects for the world’s poor people. However, they presented a rather generalized view that all poor people were vulnerable, in contrast to earlier scientific studies highlighting vulnerability as contextual with variation over time and space. This chapter is devoted to exploring poverty in relation to climate change, a new theme in the IPCC. It uses a livelihood lens to assess the interactions between climate change and the multiple dimensions of poverty, not just income poverty. This lens also reveals how inequalities perpetuate poverty, and how they shape differential vulnerabilities and in turn the differentiated impacts of climate change on individuals and societies. This chapter illustrates that climate change adds an additional burden to poor people and their livelihoods, acting as a threat multiplier. Moreover, it emphasizes that climate change may create new groups of poor people, not only in low-income countries but also in middle- and high-income countries. Neither alleviating poverty nor decreasing vulnerabilities to climate change can be achieved unless entrenched inequalities are reduced. This chapter concludes that climate change policy responses reviewed in this chapter often do not benefit poor people, and highlights lessons for climate-resilient development pathways. Eight major research gaps are identified with respect to the observed and projected impacts of climate change and climate change responses: • Poverty dynamics are not sufficiently accounted for in current climate change research. Most research as well as poverty measurements remain focused on only one or two dimensions of poverty. Insufficient work assesses the distribution of poverty at the level of households, spatial and temporal shifts, critical thresholds that plunge some transient poor into chronic poverty, and poverty traps, in the context of climatic and nonclimatic stressors. Many of these dynamics remain hidden, incompletely captured in poverty statistics and disaster and development discourses. Key assumptions in many economic models (e.g., constant within- Subject to Final Copyedit 24 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 13 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 • • • • • • • country distribution of per-capita income over time, linear relationship between economic growth and poverty headcounts) are ill-suited to capture local and sub-national poverty dynamics, confounding projections of future poverty levels. Though an abundance of studies exists that explore climate change impacts on livelihoods, the majority does not focus on continuous struggles and trajectories but only offers snapshots. An explicit analysis of livelihood dynamics would more clearly reveal how people respond to a series of climatic stressors and shocks over time. Few studies examine how structural inequalities, power imbalances, and intersecting axes of privilege and marginalization shape differential vulnerabilities to climate change. Although there is growing literature on climate change and gender as well as on indigeneity, other axes such as age, class, race, caste, and (dis)ability, remain underexplored. Understanding how simultaneous and intersecting inequalities determine climate change impacts shows which particular drivers of vulnerability are at play in one context, while absent in another. Very limited research examines climate change impacts on poor people and livelihoods in middle- to highincome countries. Despite mounting evidence of observed impacts of climatic events on the poor in MICs and HICs, as documented for the European heat wave, Hurricane Katrina in the U.S., and the ten-year drought in Australia, the majority of research on the poverty-climate nexus remains focused on the poorest countries. There remains a lack of rigorous data collection and analysis regarding small-scale disasters, i.e. those that go unnoticed because of their limited extent, but whose accumulated effect may exceed large-scale disasters. This gap leads to significant underestimation of lived experiences with climate change, in which particular loss and harm remain largely undetected. There is a need for more climatology research informed by the needs of poor people and vulnerable livelihoods, for instance on the effects of changing winds as a combined result of climate and land cover change, and their effects on increasing evaporation and water availability. Not enough consideration is given to extreme stressors and shocks, e.g., under potential global mean warming of +4°C and beyond, underestimating impacts on poor and marginalized people and limits to adaptation. There is a lack of in-depth research on the direct and indirect effects of mitigation and adaptation climaterelated policies such as CDM, REDD+, biofuels, and insurance, on livelihoods, poverty, and inequality. More in-depth research has the potential to improve the capacity of these policies to benefit poor people. Limited understanding exists of how poverty alleviation and more equality between the poor and the nonpoor are best built into climate-resilient development pathways to strive toward a just and desirable future for all. Frequently Asked Questions FAQ 13.1: What are multiple stressors and how do they intersect with inequalities to influence livelihood trajectories? [to be placed in Section 13.1.1.2] Multiple stressors are simultaneous or subsequent conditions or events that provoke/require changes in livelihoods. Stressors include climatic (e.g. shifts in seasons), socio-economic (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 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 Subject to Final Copyedit 25 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 13 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 shifts in the monsoon season (climatic), limited road linkages (socio-economic), and high elevation (environmental). Women from low castes have adapted their livelihoods by seeking more day-labor employment, whereas men from low castes ventured into trading on the Nepal-China border, previously an exclusively upper caste livelihood. FAQ 13.2: How important are climate change-driven impacts on poverty compared to other drivers of poverty? [to be placed in Section 13.1.4] Climate change-driven impacts are one of many important causes of poverty. They often act as a threat multiplier, meaning that the impacts of climate change compound other drivers of poverty. Poverty is a complex social and political problem, intertwined with processes of socioeconomic, cultural, institutional, and political marginalization, inequality, and deprivation, in low-, middle-, and even high-income countries. Climate change intersects with many causes and aspects of poverty to worsen not only income poverty but also undermine well-being, agency, and a sense of belonging. This complexity makes detecting and measuring attribution to climate change exceedingly difficult. Even modest changes in seasonality of rainfall, temperature, and wind patterns can push transient poor and marginalized people into chronic poverty as they lack access to credit, climate forecasts, insurance, government support, and effective response options, such as diversifying their assets. Such shifts have been observed among climate-sensitive livelihoods in high mountain environments, drylands, and the Arctic, and in informal settlements and urban slums. Extreme events, such as floods, droughts, and heat waves, especially when occurring in a series, can significantly erode poor people’s assets and further undermine their livelihoods in terms of labor productivity, housing, infrastructure, and social networks. Indirect impacts, such as increases in food prices due to climate-related disasters and/or policies, can also harm both rural and urban poor people who are net buyers of food. FAQ 13.3: Are there unintended negative consequences of climate change policies for people who are poor? [to be placed in Section 13.3.1] Climate change mitigation and adaptation policies may have unintended and potentially detrimental effects on poor people and their livelihoods (the set of capabilities, assets, and activities required to make a living). Here is just one example. In part as a result of climate change mitigation policies to promote biofuels and growing concern about food insecurity in middle and high income countries, large-scale land acquisition in Africa, Southeast Asia, and Latin America has displaced small landholders and contributed to food price increases. Poor urban residents are particularly vulnerable to food price increases as they use a large share of their income to purchase food. At the same time, higher food prices may benefit some agricultural self-employed groups. Besides negative impacts on food security, biofuel schemes may also harm poor and marginalized people through declining biodiversity, reduced grazing land, competition for water, and unfavorable shifts in access to and control over resources. However, employment in the biofuel industry may create opportunities for some people to improve their livelihoods. Cross-Chapter Box Box CC-HS. Heat Stress and Heat Waves [Lennart Olsson (Sweden), Dave Chadee (Trinidad and Tobago), Ove Hoegh-Guldberg (Australia), John Porter (Denmark), Hans-O. Pörtner (Germany), Kirk Smith (USA), Maria Isabel Travasso (Argentina), Petra Tschakert (USA)] Heat waves are periods of abnormally and uncomfortably hot weather during which the risk of heat stress on people and ecosystems is high. The number and intensity of hot days have increased markedly in the last three decades (Coumou et al., 2013) (high confidence). According to WG I, it is likely that the occurrence of heat waves has more than doubled in some locations due to human influence and it is virtually certain that there will be more frequent hot extremes over most land areas in the latter half of the 21st century. Coumou et al. (2013) predicted that, under a medium warming scenario, the number of monthly heat records will be over 12 times more common by the 2040s compared to a non-warming world. In a longer time perspective, if the global mean temperature increases to +10C or more, the habitability of large parts of the tropics and mid-latitudes will be at risk (Sherwood and Huber, 2010). Heat waves affect natural and human systems directly, often with severe losses of lives and assets as a result, and they may act as triggers for tipping points (Hughes et al., 2013). Consequently, heat waves play an important role in several key risks noted in Chapter 19 and CC-KR. Subject to Final Copyedit 26 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 13 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 Economy and Society [Ch 10, 11, 12, 13] Environmental heat stress has already reduced the global labor capacity to 90% in peak months with a further predicted reduction to 80% in peak months by 2050. Under a high warming scenario (RCP8.5), labor capacity is expected to be less than 40% of present day conditions in peak months by 2200 (Dunne et al., 2013). Adaptation costs for securing cooling capacities and emergency shelters during heat waves will be substantial. Heat waves are associated with social predicaments such as increasing violence (Anderson, 2012) as well as overall health and psychological distress and low life satisfaction (Tawatsupa et al., 2012). Impacts are highly differential with disproportional burdens on poor people, elderly people, and those who are marginalized (Wilhelmi et al., 2012). Urban areas are expected to suffer more due to the combined effect of climate and the urban heat island effect (Fischer et al., 2012). In LICs and MICs, adaptation to heat stress is severely restricted for most people in poverty and particularly those who are dependent on working outdoors in agriculture, fisheries, and construction. In smallscale agriculture, women and children are particularly at risk due to the gendered division of labor (Croppenstedt et al., 2013). The expected increase in wildfires as a result of heat waves (Pechony and Shindell, 2010) is a concern for human security, health, and ecosystems. Air pollution from wildfires already causes an estimated 339,000 premature deaths per year worldwide (Johnston et al., 2012). Human Health [Ch 11] Morbidity and mortality due to heat stress is now common all over the world (Barriopedro et al., 2011; Rahmstorf and Coumou, 2011; Nitschke et al., 2011; Diboulo et al., 2012; Hansen et al., 2012). People in physical work are at particular risk as such work produces substantial heat within the body, which cannot be released if the outside temperature and humidity is above certain limits (Kjellstrom et al., 2009). The risk of non-melanoma skin cancer from exposure to UV radiation during summer months increases with temperature (van der Leun, Jan C et al., 2008). Increase in ozone concentrations due to high temperatures affects health (Smith et al., 2010), leading to premature mortality, e.g. cardiopulmonary mortality (Smith et al., 2010). High temperatures are also associated with an increase in air-borne allergens acting as a trigger for respiratory illnesses such as asthma, allergic rhinitis, conjunctivitis, and dermatitis (Beggs, 2010). Ecosystems [Ch 4, 5, 6, 30] Tree mortality is increasing globally (Williams et al., 2012) and can be linked to climate impacts, especially heat and drought (Reichstein et al., 2013), even though attribution to climate change is difficult due to lack of time series and confounding factors. In the Mediterranean region, higher fire risk, longer fire season, and more frequent large, severe fires are expected as a result of increasing heat waves in combination with drought (Duguy et al., 2013), Box 4.2. Marine ecosystem shifts attributed to climate change are often caused by temperature extremes rather than changes in the average (Pörtner and Knust, 2007). During heat exposure near biogeographical limits, even small (<0.5°C) shifts in temperature extremes can have large effects, often exacerbated by concomitant exposures to hypoxia and/or elevated CO2 levels and associated acidification (Hoegh-Guldberg et al., 2007), Figure 6-5, (medium confidence) [Ch 6.3.1, 6.3.5; 30.4; 30.5; CC-MB] Most coral reefs have experienced heat stress sufficient to cause frequent mass coral bleaching events in the last 30 years, sometimes followed by mass mortality (Baker et al., 2008). The interaction of acidification and warming exacerbates coral bleaching and mortality (very high confidence).Temperate seagrass and kelp ecosystems will decline with the increased frequency of heat waves and through the impact of invasive subtropical species (high confidence). [Ch 5, 6, 30.4-30.5, CC-CR, CC-MB] Agriculture [Ch 7] Excessive heat interacts with key physiological processes in crops. Negative yield impacts for all crops past +3C of local warming without adaptation, even with benefits of higher CO2 and rainfall, are expected even in cool environments (Teixeira et al., 2011). For tropical systems where moisture availability or extreme heat limits the length of the growing season, there is a high potential for a decline in the length of the growing season and Subject to Final Copyedit 27 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 13 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 suitability for crops (medium evidence, medium agreement) (Jones and Thornton, 2009). For example, half of the wheat-growing area of the Indo-Gangetic Plains could become significantly heat-stressed by the 2050s. There is high confidence that high temperatures reduce animal feeding and growth rates (Thornton et al., 2009). Heat stress reduces reproductive rates of livestock (Hansen, 2009), weakens their overall performance (Henry et al., 2012), and may cause mass mortality of animals in feedlots during heat waves (Polley et al., 2013). In the U.S., current economic losses due to heat stress of livestock are estimated at several billion USD annually (St-Pierre et al., 2003). Box CC-HS References Anderson, C.A., 2012: Climate Change and Violence. In: The Encyclopedia of Peace Psychology. [Christie, D.J. (ed.)]. Wiley Online Library Baker, A.C., P.W. Glynn, and B. Riegl, 2008: Climate change and coral reef bleaching: An ecological assessment of long-term impacts, recovery trends and future outlook. Estuarine, Coastal and Shelf Science, 80(4), 435-471. Barriopedro, D., E.M. Fischer, J. Luterbacher, R.M. Trigo, and R. García-Herrera, 2011: The hot summer of 2010: redrawing the temperature record map of Europe. Science, 332(6026), 220-224. Beggs, P.J., 2010: Adaptation to impacts of climate change on aeroallergens and allergic respiratory diseases. International Journal of Environmental Research and Public Health, 7(8), 3006-3021. Coumou, D., A. Robinson, and S. Rahmstorf, 2013: Global increase in record-breaking monthly-mean temperatures. Climatic Change, 118(3-4), 771-782. Croppenstedt, A., M. Goldstein, and N. Rosas, 2013: Gender and agriculture: inefficiencies, segregation, and low productivity traps. The World Bank Research Observer, 28(1), 79-109. Diboulo, E., A. Sie, J. Rocklöv, L. Niamba, M. Ye, C. Bagagnan, and R. Sauerborn, 2012: Weather and mortality: a 10 year retrospective analysis of the Nouna Health and Demographic Surveillance System, Burkina Faso. Global Health Action, 5(19078). Duguy, B., S. Paula, J.G. Pausas, J.A. Alloza, T. Gimeno, and R.V. Vallejo, 2013: Effects of climate and extreme events on wildfire regime and their ecological impacts. In: Regional Assessment of Climate Change in the Mediterranean. Springer, pp. 101-134. Dunne, J.P., R.J. Stouffer, and J.G. John, 2013: Reductions in labour capacity from heat stress under climate warming. Nature Climate Change, published on-line 24 February 2013, 1-4. Fischer, E., K. Oleson, and D. Lawrence, 2012: Contrasting urban and rural heat stress responses to climate change. Geophysical Research Letters, 39(3), L03705. Hansen, J., M. Sato, and R. Ruedy, 2012: Perception of climate change. Proceedings of the National Academy of Sciences, 109(37), E2415E2423. Hansen, P.J., 2009: Effects of heat stress on mammalian reproduction. Philosophical Transactions of the Royal Society B: Biological Sciences, 364(1534), 3341-3350. Henry, B., R. Eckard, J.B. Gaughan, and R. Hegarty, 2012: Livestock production in a changing climate: adaptation and mitigation research in Australia. Crop and Pasture Science, 63(3), 191-202. Hoegh-Guldberg, O., P. Mumby, A. Hooten, R. Steneck, P. Greenfield, E. Gomez, C. Harvell, P. Sale, A. Edwards, and K. Caldeira, 2007: Coral reefs under rapid climate change and ocean acidification. Science, 318(5857), 1737-1742. Hughes, T.P., S. Carpenter, J. Rockström, M. Scheffer, and B. Walker, 2013: Multiscale regime shifts and planetary boundaries. Trends in Ecology & Evolution, 28(7), 389-395. Johnston, F.H., S.B. Henderson, Y. Chen, J.T. Randerson, M. Marlier, R.S. DeFries, P. Kinney, D.M. Bowman, and M. Brauer, 2012: Estimated global mortality attributable to smoke from landscape fires. Environmental Health Perspectives, 120(5), 695. Jones, P.G. and P.K. Thornton, 2009: Croppers to livestock keepers: livelihood transitions to 2050 in Africa due to climate change. Environmental Science & Policy, 12(4), 427-437. Kjellstrom, T., R. Kovats, S. Lloyd, T. Holt, and R. Tol, 2009: The direct impact of climate change on regional labor productivity. Archives of Environmental & Occupational Health, 64(4), 217-227. Nitschke, M., G.R. Tucker, A.L. Hansen, S. Williams, Y. Zhang, and P. Bi, 2011: Impact of two recent extreme heat episodes on morbidity and mortality in Adelaide, South Australia: a case-series analysis. Environ Health, 10, 42. Pechony, O. and D. Shindell, 2010: Driving forces of global wildfires over the past millennium and the forthcoming century. Proceedings of the National Academy of Sciences, 107(45), 19167-19170. Polley, H.W., D.D. Briske, J.A. Morgan, K. Wolter, D.W. Bailey, and J.R. Brown, 2013: Climate Change and North American Rangelands: Trends, Projections, and Implications. Rangeland Ecology & Management, 66(5), 493-511. Subject to Final Copyedit 28 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 13 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 Pörtner, H.O. and R. Knust, 2007: Climate change affects marine fishes through the oxygen limitation of thermal tolerance. Science, 315(5808), 95-97. Rahmstorf, S. and D. Coumou, 2011: Increase of extreme events in a warming world. Proceedings of the National Academy of Sciences, 108(44), 17905-17909. Reichstein, M., M. Bahn, P. Ciais, D. Frank, M.D. Mahecha, S.I. Seneviratne, J. Zscheischler, C. Beer, N. Buchmann, and D.C. Frank, 2013: Climate extremes and the carbon cycle. Nature, 500(7462), 287-295. Sherwood, S.C. and M. Huber, 2010: An adaptability limit to climate change due to heat stress. Proceedings of the National Academy of Sciences, 107(21), 9552-9555. Smith, K.R., M. Jerrett, H.R. Anderson, R.T. Burnett, V. Stone, R. Derwent, R.W. Atkinson, A. Cohen, S.B. Shonkoff, and D. Krewski, 2010: Public health benefits of strategies to reduce greenhouse-gas emissions: health implications of short-lived greenhouse pollutants. The Lancet, 374(9707), 2091-2103. St-Pierre, N., B. Cobanov, and G. Schnitkey, 2003: Economic losses from heat stress by US livestock industries. Journal of Dairy Science, 86, E52-E77. Tawatsupa, B., V. Yiengprugsawan, T. Kjellstrom, and A. Sleigh, 2012: Heat stress, health and well-being: findings from a large national cohort of Thai adults. BMJ Open, 2(6). Teixeira, E.I., G. Fischer, H. van Velthuizen, C. Walter, and F. Ewert, 2011: Global hot-spots of heat stress on agricultural crops due to climate change. Agricultural and Forest Meteorology, 170, 206-215. Thornton, P., J. Van de Steeg, A. Notenbaert, and M. Herrero, 2009: The impacts of climate change on livestock and livestock systems in developing countries: A review of what we know and what we need to know. Agricultural Systems, 101(3), 113-127. van der Leun, Jan C, R.D. Piacentini, and F.R. de Gruijl, 2008: Climate change and human skin cancer. Photochemical & Photobiological Sciences, 7(6), 730-733. Wilhelmi, O., A. de Sherbinin, and M. Hayden, 2012: 12 Exposure to heat stress in urban environments. Ecologies and Politics of Health, 41, 219. Williams, A.P., C.D. Allen, A.K. Macalady, D. Griffin, C.A. Woodhouse, D.M. Meko, T.W. Swetnam, S.A. Rauscher, R. Seager, and H.D. Grissino-Mayer, 2012: Temperature as a potent driver of regional forest drought stress and tree mortality. Nature Climate Change, 3, 292297. References Abam, T., C. Ofoegbu, C. Osadebe, and A. Gobo, 2000: Impact of hydrology on the Port-Harcourt–Patani-Warri Road. Environmental Geology, 40(1), 153-162. Ackerman, F., E.A. Stanton, C. Hope, S. Alberth, J. Fisher, and B. Biewald, 2008: The cost of climate change. Natural Resources Defense Council, New York, NY, USA. Adano, W.R., T. Dietz, K. Witsenburg, and F. Zaal, 2012: Climate change, violent conflict and local institutions in Kenya’s drylands. Journal of Peace Research, 49(1), 65-80. Adelekan, I.O., 2010: Vulnerability of poor urban coastal communities to flooding in Lagos, Nigeria. Environment and Urbanization, 22(2), 433-450. Adger, W.N., S. Huq, K. Brown, D. Conway, and M. Hulme, 2003: Adaptation to climate change in the developing world. Progress in Development Studies, 3(3), 179-195. Adger, W.N., S. Agrawala, M.M.Q. Mirza, C. Conde, K. O’Brien, J. Pulhin, R. Pulwarty, B. Smit, and K. Takahashi, 2007: Chapter 17: Assessment of adaptation practices, options, constraints and capacity. In: Climate Change 2007: Synthesis Report. Contribution of Working Groups I, II and III to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. [IPCC (ed.)]. IPCC, Geneva, Switzerland, pp. 719-743. Adger, W.N., 2010: Climate change, human well-being and insecurity. New Political Economy, 15(2), 275-292. Adrian, R., C.M. O’Reilly, H. Zagarese, S.B. Baines, D.O. Hessen, W. Keller, D.M. Livingstone, R. Sommaruga, D. Straile, and E. Van Donk, 2009: Lakes as sentinels of climate change. Limnology and Oceanography, 54(6), 2283-2297. Agrawal, A. and N. Perrin, 2009: Climate adaptation, local institutions and rural livelihoods. In: Adapting to Climate Change. Thesholds, Values, Governance. [Adger, W.N., I. Lorenzoni, and K.L. O'Brien(eds.)]. Cambridge University Press, Cambridge, pp. 350-367. Agrawal, A., D. Nepstad, and A. Chhatre, 2011: Reducing emissions from deforestation and forest degradation. Annual Review of Environment and Resources, 36(1), 373-396. Subject to Final Copyedit 29 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 13 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 Ahearn, L.M., 2001: Invitations to love: Literacy, love letters, and social change in Nepal. University of Michigan Press, Ann Arbor, MI, USA, . Ahmed, A.U., S.R. Hassan, B. Etzold, and S. Neelormi, 2012: Rainfall, Food Security and Human Mobility, Bangladesh Case Study. Care; United Nations University (UNU), Bonn, pp. 1-158. Ahmed, S.A., N.S. Diffenbaugh, and T.W. Hertel, 2009: Climate volatility deepens poverty vulnerability in developing countries. Environmental Research Letters, 4(3), 034004. Ahmed, S.A., N.S. Diffenbaugh, T.W. Hertel, D.B. Lobell, N. Ramankutty, A.R. Rios, and P. Rowhani, 2011: Climate volatility and poverty vulnerability in Tanzania. Global Environmental Change, 21(1), 46-55. Ajanovic, A., 2011: Biofuels versus food production: Does biofuels production increase food prices? Energy, 36(4), 2070-2076. Aksoy, A. and A. Isik-Dikmelik, 2008: Are low food prices pro-poor? Net food buyers and sellers in low-income countries. World Bank, Washington DC, USA, pp. 1-32. Akter, S., R. Brouwer, P.J.H. van Beukering, L. French, E. Silver, S. Choudhury, and S.S. Aziz, 2011: Exploring the feasibility of private micro flood insurance provision in Bangladesh. Disasters, 35(2), 287-307. Alderman, H., 2010: Safety nets can help address the risks to nutrition from increasing climate variability. The Journal of Nutrition, 140(1), 148S-152S. Alkire, S., 2005: Valuing freedoms: Sen's capability approach and poverty reduction. Oxford University Press, Oxford, UK and New York, USA, pp. 300. Alkire, S. and M.E. Santos, 2010: Acute Multidimensional Poverty: A New Index for Developing Countries. Human Development Research Paper 2010/11. United Nations Development Programme (UNDP), New York, NY, USA, pp. 1-142. Alkire, S. and J. Foster, 2011: Understandings and misunderstandings of multidimensional poverty measurement. Journal of Economic Inequality, 9(2), 289-314. Alston, M. and K. Whittenbury, 2013: Research, Action and Policy: Addressing the Gendered Impacts of Climate Change. Springer, . Alston, M., 2011: Gender and climate change in Australia. Journal of Sociology, 47(1), 53-70. Anastario, M., N. Shebab, and L. Lawry, 2009: Increased gender-based violence among women internally displaced in Mississippi 2 years post-Hurricane Katrina. Disaster Medicine and Public Health Preparedness, 3(1), 18-26. Andersen, L. and D. Verner, 2009: Social impacts of climate change in Bolivia: a municipal level analysis of the effects of recent climate change on life expectancy, consumption, poverty and inequality. Policy Research Working Paper 5092. World Bank, Washington DC, USA, pp. 1-26. Anderson, D.M. and V. Broch-Due, 2000: The Poor are not Us: Poverty and Pastoralism in Eastern Africa. James Currey Ltd, Woodbridge, UK, pp. 276. Anderson, D., 2009: Enduring drought then coping with climate change: Lived experience and local resolve in rural mental health. Rural Society, 19(4), 340-352. Anderson, S., J. Morton, and C. Toulmin, 2009: Climate change for agrarian societies in drylands: implications and future pathways. In: Social Dimensions of Climate Change: Equity and Vulnerability in a Warming World. [Mearns, R. and A. Morton(eds.)]. World Bank, Washington D.C., USA, pp. 199-230. Andersson, E. and S. Gabrielsson, 2012: 'Because of poverty, we had to come together’: collective action for improved food security in rural Kenya and Uganda. International Journal of Agricultural Sustainability, 10(3), 245-262. Angelsen, A., M. Brockhaus, and M. Kanninen (eds.), 2009: Realizing REDD+: National strategy and policy options. Center for International Forestry Research, Copenhagen, Denmark, . Anseeuw, W., L.A. Wily, L. Cotula, and M. Taylor, 2012: Land Rights and the Rush for Land: Findings of the Global Commercial Pressures on Land Research Project. International Land Coalition, Rome, pp. 74. Antle, J.M. and J.J. Stoorvogel, 2009: Payments for ecosystem services, poverty and sustainability: The case of agricultural soil carbon sequestration. Natural Resource Management and Policy, 31, 133-161. Apata, T.G., K. Samuel, and A. Adeola, 2009: Contributed Paper prepared for presentation at the International Association of Agricultural Economists’ 2009 Conference, Beijing, China, August 16. In: Analysis of Climate Change Perception and Adaptation among Arable Food Crop Farmers in South Western Nigeria pp. 1-15. Ariza-Montobbio, P., S. Lele, G. Kallis, and J. Martinez-Alier, 2010: The political ecology of Jatropha plantations for biodiesel in Tamil Nadu, India. The Journal of Peasant Studies, 37(4), 875-897. Subject to Final Copyedit 30 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 13 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 Armah, F.A., J.O. Odoi, G.T. Yengoh, S. Obiri, D.O. Yawson, and E.K.A. Afrifa, 2011: Food security and climate change in drought-sensitive savanna zones of Ghana. Mitigation and Adaptation Strategies for Global Change, 16(3), 291-306. Arnall, A., K. Oswald, M. Davies, T. Mitchell, and C. Coirolo, 2010: Adaptive social protection: mapping the evidence and policy context in the agriculture sector in South Asia. Working Paper, Volume 2010 Number 345. Centre for Social Protection; Institute of Development Studies (IDS), Brighton, UK, pp. 1-92. Arndt, C., R. Benfica, F. Tarp, J. Thurlow, and R. Uaiene, 2009: Biofuels, poverty, and growth: a computable general equilibrium analysis of Mozambique. Environment and Development Economics, 15(1), 81-105. Arndt, C., R. Benfica, and J. Thurlow, 2011: Gender implications of biofuels expansion in Africa: The case of Mozambique. World Development, 39(9), 1649-1662. Arora-Jonsson, S., 2011: Virtue and vulnerability: Discourses on women, gender and climate change. Global Environmental Change, 21(2), 744-751. Aryal, K.R., 2012: The history of disaster incidents and impacts in Nepal 1900–2005. International Journal of Disaster Risk Science, 3(3), 147-154. Assuncao, J.J. and F.F. Cheres, 2008: Climate Change, Agricultural Productivity and Poverty. In: Background Paper for De La Torre, A., P.Fajnzylber, and J.Nash (2009), Low Carbon, High Growth—Latin American Responses to Climate Change: An Overview. World Bank, Washington DC, USA. Ayers, J. and S. Huq, 2009: Community-based adaptation to climate change: an update. International Institute for Environment and Development (IIED), London, UK, pp. 1-4. Ayers, J. and D. Dodman, 2010: Climate change adaptation and development I the state of the debate. Progress in Development Studies, 10(2), 161-168. Azhar-Hewitt, F. and K. Hewitt, 2012: Technocratic Approaches and Community Contexts: Viewpoints of Those Most at Risk from Environmental Disasters in Mountain Areas, Northern Pakistan. In: Climate Change Modeling For Local Adaptation In The Hindu Kush-Himalayan Region. [Lamadrid, A. and I. Kelman(eds.)]. Emerald Group Publishing Limited, UK, pp. 53-73. Babugura, A., 2010: Gender and Climate Change: South Africa Case Study. Heinrich Böll Foundation Southern Africa, Cape Town, South Africa. Baccini, M., A. Biggeri, G. Accetta, T. Kosatsky, K. Katsouyanni, A. Analitis, H.R. Anderson, L. Bisanti, D. D'Ippoliti, and J. Danova, 2008: Heat effects on mortality in 15 European cities. Epidemiology, 19(5), 711-719. Baffes, J. and T. Haniotis, 2010: Placing the 2006/08 commodity price boom into perspective. In: . Policy Research Working Paper. World Bank, Washington DC, USA, pp. 1-40. Balbus, J.M. and C. Malina, 2009: Identifying Vulnerable Subpopulations for Climate Change Health Effects in the United States. 51(1), 33-37. Balk, D., M. Montgomery, G. McGranahan, and M. Todd, 2009: Understanding the impacts of climate change: Linking satellite and other spatial data with population data. In: Population Dynamics and Climate Change. [Guzmán, J.M., G. Martine, G. McGranahan, D. Schensul, and C. Tacoli(eds.)]. UNFPA; IIED, New York, NY, USA, pp. 206-217. Bandiera, O., I. Barankay, and I. Rasul, 2005: Cooperation in collective action*. Economics of Transition, 13(3), 473-498. Banik, D., 2009: Legal empowerment as a conceptual and operational tool in poverty eradication. Hague Journal on the Rule of Law, 1(01), 117-131. Barnes, D., S. Khandker, and H.A. Samad, 2010: Energy access, efficiency, and poverty: how many households are energy poor in Bangladesh?. In: Policy Research Paper. World Bank, Washington DC, USA, pp. 1-50. Barnett, B.J., C.B. Barrett, and J.R. Skees, 2008: Poverty traps and index-based risk transfer products. World Development, 36(10), 1766-1785. Barnett, J. and S. O’Neill, 2010: Maladaptation. Global Environmental Change, 20(2), 211-213. Barrett, C. and J. McPeak, 2006: Poverty traps and safety nets. In: Poverty, Inequality and Development. [Thorbecke, E., A. De Janvry, and S.M. Ravi Kanbur(eds.)]. Springer, New York, NY, USA, pp. 131-154. Barrientos, A. and D. Hulme, 2009: Social Protection for the Poor and Poorest in Developing Countries: Reflections on a quiet revolution. Oxford Development Studies, 37(4), 439-456. Barrientos, A., 2011: Social protection and poverty. International Journal of Social Welfare, 20(3), 240-249. Barron, J., J. Rockström, F. Gichuki, and N. Hatibu, 2003: Dry spell analysis and maize yields for two semi-arid locations in east Africa. Agricultural and Forest Meteorology, 117(1–2), 23-37. Subject to Final Copyedit 31 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 13 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 Bartlett, S., 2008: Climate Change and Urban Children: Impacts and implications for adaptation in low-and middleincome countries. Environment and Urbanization, 20(2), 501-519. Bastos Lima, M.G., 2012: An Institutional Analysis of Biofuel Policies and their Social Implications: Lessons from Brazil, India and Indonesia. Occasional Paper n.9. In: Social Dimensions of Green Economy and Sustainable Development. United Nations Research Institute for Social Development (UNRISD), Geneva, Switzerland, pp. 1-22. Basu, R. and J.M. Samet, 2002: Relation between elevated ambient temperature and mortality: a review of the epidemiologic evidence. Epidemiologic Reviews, 24(2), 190-202. Batterbury, S., 2001: Landscapes of diversity: a local political ecology of livelihood diversification in south-western Niger. Cultural Geographies, 8(4), 437-464. Bebbington, A., 1999: Capitals and capabilities: A framework for analyzing peasant viability, rural livelihoods and poverty. World Development, 27(12), 2021-2044. Bee, B., M. Biermann, and P. Tschakert, 2013: Gender, development, and rights-based approaches: Lessons for climate change adaptation and adaptive social protection. In: Research, Action and Policy: Addressing the Gendered Impacts of Climate Change. [Alston, M. and K. Whittenbury(eds.)]. Springer, Netherlands, pp. 95108. Behrman, J., R. Meinzen-Dick, and A. Quisumbing, 2012: The gender implications of large-scale land deals. Journal of Peasant Studies, 39(1), 49-79. Bele, M.Y., A.M. Tiani, O.A. Somorin, and D.J. Sonwa, 2013: Exploring vulnerability and adaptation to climate change of communities in the forest zone of Cameroon. Climatic Change, 119(3-4), 1-15. Bell, J., M. Brubaker, K. Graves, and J. Berner, 2010: Climate change and mental health: uncertainty and vulnerability for Alaska natives. CCH Bulletin, 3, 1-10. Béné, C., S. Devereux, and R. Sabates‐Wheeler, 2012: Shocks and social protection in the Horn of Africa: analysis from the Productive Safety Net programme in Ethiopia. IDS Working Papers, 2012(395), 1-120. Beniston, M., 2003: Climatic change in mountain regions: a review of possible impacts. Climatic Change, 59(1), 531. Benson, C., M. Arnold, A. de la Fuente, and R. Mearns, 2012: Financial innovations for social and climate resilience: Establishing an evidence base. In: Social Resilience & Climate Change. World Bank, Washington D.C., USA, pp. 1-2. Bhattamishra, R. and C.B. Barrett, 2010: Community-based risk management arrangements: A review. World Development, 38(7), 923-932. Bibi, S., J. Cockburn, M. Coulibaly, and L. Tiberti, 2010: The impact of the increase in food prices on child poverty and the policy response in Mali. In: Child Welfare in Developing Countries. [Cockburn, J. and J. KabuboMariara(eds.)]. Springer, New York, NY, USA, pp. 247-296. Biener, C. and M. Eling, 2012: Insurability in Microinsurance Markets: An Analysis of Problems and Potential Solutions. The Geneva Papers on Risk and Insurance-Issues and Practice, 37(1), 77-107. Biermann, F., P. Pattberg, H. Van Asselt, and F. Zelli, 2009: The fragmentation of global governance architectures: A framework for analysis. Global Environmental Politics, 9(4), 14-40. Biermann, F., 2010: Beyond the intergovernmental regime: recent trends in global carbon governance. Current Opinion in Environmental Sustainability, 2(4), 284-288. Biermann, F., K. Abbott, S. Andresen, K. Bäckstrand, S. Bernstein, M. Betsill, H. Bulkeley, B. Cashore, J. Clapp, and C. Folke, 2012: Navigating the Anthropocene: Improving Earth System Governance. Science, 335(6074), 1306-1307. Blackden, C.M. and Q. Wodon, 2006: Gender, time use, and poverty in sub-Saharan Africa. World Bank Publications, Washington D.C., USA, . Boetto, H. and J. McKinnon, 2013: Rural women and climate change: A gender-inclusive perspective. Australian Social Work, 66(2), 234-247. Böhm, S., 2009: Upsetting the offset: the political economy of carbon markets. MayFlyBooks, London, UK, pp. 384. Boko, M., I. Niang, A. Nyong, C. Vogel, A. Githeko, M. Medany, B. Osman-Elasha, R. Tabo, and P. Yanda, 2007: Africa. In: Climate Change 2007: Impacts, Adaptation and Vulnerability. Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. [Parry, M.L., O.F. Canziani, J.P. Palutikof, van der Linden, P. J., and C.E. Hanson(eds.)]. Cambridge University Press, . Subject to Final Copyedit 32 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 13 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 Borges da Cunha, K., A. Walter, and F. Rei, 2007: CDM implementation in Brazil’s rural and isolated regions: the Amazonian case. Climatic Change, 84(1), 111-129. Börner, J., S. Wunder, S. Wertz-Kanounnikoff, G. Hyman, and N. Nascimento, 2011: REDD sticks and carrots in the Brazilian Amazon: Assessing costs and livelihood implications.Proceedings of Colorado Conference on Earth System Governance, pp. 17-20. Borras Jr, S.M., R. Hall, I. Scoones, B. White, and W. Wolford, 2011: Towards a better understanding of global land grabbing: an editorial introduction. The Journal of Peasant Studies, 38(2), 209-216. Borras, S., J. Franco, C. Kay, and M. Spoor, 2011: Land grabbing in Latin America and the Caribbean in broader international perspectives. A paper prepared for and presented at the Latin America and Caribbean seminar: ‘Dinámicas en el mercado de la tierra en América Latina y el Caribe’, 14-15 November, FAO Regional Office, Santiago, Chile.pp. 1-54. Boyd, E. and S. Juhola, 2009: Stepping up to the climate change: Opportunities in re‐conceptualising development futures. Journal of International Development, 21(6), 792-804. Boyd, E. and M.K. Goodman, 2011: The Clean Development Mechanism As Ethical Development?: Reconciling Emissions Trading And Local Development. Journal of International Development, 23(6), 836-854. Boyd, E., N. Hultman, J. Timmons Roberts, E. Corbera, J. Cole, A. Bozmoski, J. Ebeling, R. Tippman, P. Mann, and K. Brown, 2009: Reforming the CDM for sustainable development: lessons learned and policy futures. Environmental Science & Policy, 12(7), 820-831. Bradshaw, S., 2010: Women, poverty, and disasters: Exploring the links through hurricane Mitch in Nicaragua. In: The international handbook of gender and poverty: concepts, research, policy. [Chant, S. (ed.)]. Edward Elgar Pub, Cheltenham, UK, pp. 627. Brans, M.V., M. Tadesse, and T. Takama, 2011: Community-based solutions to the climate crisis in Ethiopia. In: Climate Change Adaptation and International Development: Making Development Cooperation More Effective. [Fujikura, R. and M. Kawanishi(eds.)]. Earthscan, London, UK, pp. 217-238. Brockhaus, M. and H. Djoudi, 2008: Adaptation at the interface of forest ecosystem goods and services and livestock production systems in Northern Mali. Center for International Foresty Research (CIFOR) Information Brief.Bogor, Indonesia., 19, 2010. Brockhaus, M., H. Djoudi, and B. Locatelli, 2013: Envisioning the future and learning from the past: Adapting to a changing environment in northern Mali. Environmental Science & Policy, 25, 94-106. Brouwer, R., S. Akter, L. Brander, and E. Haque, 2007: Socioeconomic vulnerability and adaptation to environmental risk: a case study of climate change and flooding in Bangladesh. Risk Analysis, 27(2), 313-326. Bryan, E., C. Ringler, B. Okoba, C. Roncoli, S. Silvestri, and M. Herrero, 2013: Adapting agriculture to climate change in Kenya: Household strategies and determinants. Journal of Environmental Management, 114, 26-35. Buch Hansen, M., 2013: Different approaches to adaptation to increasing climate variability and extremes. A case study from Mid-Vietnam. In: Social Adaptation to Climate Change in Developing Countries: “Development as usual is not enough”. [Inderberg, T.H., S. Eriksen, K. O’Brien, and L. Sygna(eds.)]. Buechler, S., 2009: Gender, water, and climate change in Sonora, Mexico: implications for policies and programmes on agricultural income-generation. Gender & Development, 17(1), 51-66. Bunce, M., S. Rosendo, and K. Brown, 2010a: Perceptions of climate change, multiple stressors and livelihoods on marginal African coasts. Environment, Development and Sustainability, 12(3), 407-440. Bunce, M., K. Brown, and S. Rosendo, 2010b: Policy misfits, climate change and cross-scale vulnerability in coastal Africa: how development projects undermine resilience. Environmental Science & Policy, 13(6), 485-497. Burke, M., J. Dykema, D. Lobell, E. Miguel, and S. Satyanath, 2011: Incorporating climate uncertainty into estimates of climate change impacts, with applications to US and African agriculture. Working Paper 17092. National Bureau of Economic Research (NBER), Cambridge, MA., USA, pp. 1-28. Burkett, M., 2011: The Nation Ex-Situ: On climate change, deterritorialized nationhood and the post-climate era. Climate Law, 2(3), 345-374. Byg, A. and J. Salick, 2009: Local perspectives on a global phenomenon--Climate change in Eastern Tibetan villages. Global Environmental Change, 19(2), 156-166. Caldwell, T.M., A.F. Jorm, and K.B.G. Dear, 2004: Suicide and mental health in rural, remote and metropolitan areas in Australia. Medical Journal of Australia, 181(7), 10. Campbell, B., S. Mitchell, and M. Blackett, 2009: Responding to Climate Change in Vietnam. Opportunities for Improving Gender Equality. Oxfam; UNDP, Hanoi, Vietnam, pp. 1-63. Subject to Final Copyedit 33 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 13 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 Caplow, S., P. Jagger, K. Lawlor, and E. Sills, 2011: Evaluating land use and livelihood impacts of early forest carbon projects: Lessons for learning about REDD. Environmental Science & Policy, 14(2), 152-167. Carr, E.R., 2008: Between structure and agency: Livelihoods and adaptation in Ghana's Central Region. Global Environmental Change, 18(4), 689-699. Carr, E.R., 2013: Livelihoods as Intimate Government: Reframing the logic of livelihoods for development. Third World Quarterly, 34(1), 77-108. Carter, M.R., P.D. Little, T. Mogues, and W. Negatu, 2007: Poverty traps and natural disasters in Ethiopia and Honduras. World Development, 35(5), 835-856. Cashman, A., L. Nurse, and C. John, 2010: Climate change in the Caribbean: the water management implications. The Journal of Environment & Development, 19(1), 42-67. Casillas, C.E. and D.M. Kammen, 2010: The energy-poverty-climate nexus. Science, 330(6008), 1181-1182. Challinor, A., T. Wheeler, C. Garforth, P. Craufurd, and A. Kassam, 2007: Assessing the vulnerability of food crop systems in Africa to climate change. Climatic Change, 83(3), 381-399. Chambers, R. and G. Conway, 1992: Sustainable rural livelihoods: practical concepts for the 21st century. Institute of Development Studies (IDS), Brighton, UK, pp. 1-33. Chronic Poverty Research Centre, 2008: The Chronic Poverty Report 2008-09: Escaping Poverty Traps. Belmont Press Limited, Northampton, U.K. Chu, J., 2011: Gender and ‘Land Grabbing’in Sub-Saharan Africa: Women's land rights and customary land tenure. Development, 54(1), 35-39. CIDA, 2002: Gender Equality And Climate Change: Why consider gender equality when taking action on climate change?. Canadian International Development Agency, Quebec, Canada, pp. 1-3. Clot, N. and J. Carter, 2009: Disaster Risk Reduction: A Gender and Livelihood Perspective. Swiss Agency for Cooperation and Development, Switzerland, pp. 1-16. Collier, P., 2007: The bottom billion. Why the Poorest Countries are Failing and What Can Be
Done About It. Oxford University Press, UK, pp. 224. Collier, P., G. Conway, and T. Venables, 2008: Climate change and Africa. Oxford Review of Economic Policy, 24(2), 337-353. Condon, N., H. Klemick, and A. Wolverton, 2013: Impacts of Ethanol Policy on Corn Prices: A Review and MetaAnalysis of Recent Evidence.Proceedings of Agricultural & Applied Economics Association’s 2013 AAEA & CAES Joint Annual Meeting, August 4-6, 2013, Washington, D.C., USA, pp. 1-48. Confalonieri, U., B. Menne, R. Akhtar, K.L. Ebi, M. Hauengue, R.S. Kovats, B. Revich, and A.J. Woodward, 2007: Human health. In: Climate Change 2007: Impacts, Adaptation and Vulnerability. Contribution of Working Group {II} to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, {UK}, pp. 391-431. Conway, D. and E.L.F. Schipper, 2011: Adaptation to climate change in Africa: Challenges and opportunities identified from Ethiopia. Global Environmental Change, 21(1), 227-237. Corbera, E. and N. Jover, 2012: The undelivered promises of the Clean Development Mechanism: insights from three projects in Mexico. Carbon, 3(1), 39-54. Cordona, O.D., M.K. van Aalst, J. Birkmann, M. Fordham, G. McGregor, R. Perez, R.S. Pulwarty, E.L.F. Schipper, and B.T. Sinh, 2012: Determinants of Risk: Exposure and Vulnerability. In: Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation: A Special Report of Working Groups I and II of the Intergovernmental Panel on Climate Change. [Field, C., V. Barros, T.F. Stocker, D. Qin, D.J. Dokken, K.L. Ebi et al.(eds.)]. Cambridge University Press, Cambride, U.K. and New York, N.Y, USA, pp. 65-108. Cordova, R., M. Gelobter, A. Hoerner, J. Love, A. Miller, C. Saenger, and D. Zaidi, 2006: Climate change in California: Health, Economic and Equity Impacts. . Redefining Progress, Oakland, CA, USA, pp. 109. Cotula, L., S. Vermeulen, R. Leonard, and J. Keeley, 2009: Land grab or development opportunity? Agricultural investment and international land deals in Africa. International Institute for Environment and Development (IIED), London, UK, pp. 1-145. Coulthard, S., 2008: Adapting to environmental change in artisanal fisheries—insights from a South Indian Lagoon. Global Environmental Change, 18(3), 479-489. Cranfield, J.A.L., P.V. Preckel, and T.W. Hertel, 2007: Poverty analysis using an international cross-country demand system. World Bank, Washington DC, USA, pp. 1-56. Crate, S.A., 2013: Climate Change and Human Mobility in Indigenous Communities of the Russian North. Bookings-LSE, George Mason University, USA, pp. 1-58. Subject to Final Copyedit 34 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 13 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 CRED, 2012: The International Disaster Database. UNDP, New York, NY, USA, pp. 1-8. Crowe, T.L., 2013: The potential of the CDM to deliver pro-poor benefits. Climate Policy, 13(1), 58-79. Cudjoe, G., C. Breisinger, and X. Diao, 2010: Local impacts of a global crisis: Food price transmission, consumer welfare and poverty in Ghana. Food Policy, 35(4), 294-302. Cutter, S., B. Osman-Elasha, J. Campbell, S.-. Cheong, McCormick S., R. Pulwarty, S. Supratid, and G. Ziervogel, 2012: Managing the risks from climate extremes at the local level. In: Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation: A Special Report of Working Groups I and {II} of the Intergovernmental Panel on Climate Change {(IPCC)}. [Field, {.B.}., V. Barros, {.F.}. Stocker, D. Qin, {.J.}. Dokken, {.L.}. Ebi et al.(eds.)]. Cambridge University Press, Cambridge, {UK} and New York, {NY {USA}, pp. 291-338. D’Agostino, A.L. and B.K. Sovacool, 2011: Sewing climate-resilient seeds: implementing climate change adaptation best practices in rural Cambodia. Mitigation and Adaptation Strategies for Global Change, 16(6), 699-720. Daley, E. and B. Englert, 2010: Securing land rights for women. Journal of Eastern African Studies, 4(1), 91-113. Daniel, S., 2011: Land Grabbing and Potential Implications for World Food Security. In: Sustainable Agricultural Development. [Behnassi, M., S.A. Shahid, and J. D'Silva(eds.)]. Springer, Netherlands, pp. 25-42. Danielsen, F., M. Skutsch, N.D. Burgess, P.M. Jensen, H. Andrianandrasana, B. Karky, R. Lewis, J.C. Lovett, J. Massao, and Y. Ngaga, 2011: At the heart of REDD : a role for local people in monitoring forests? Conservation Letters, 4(2), 158-167. Dankelman, I., 2010: Introduction: Exploring gender, environment, and climate change. In: Gender and climate change: An introduction. [Dankelman, I. (ed.)]. Earthscan, London, UK, Sterling, VA, USA, pp. 1-20. Dauvergne, P. and K.J. Neville, 2009: The changing north–south and south–south political economy of biofuels. Third World Quarterly, 30(6), 1087-1102. Davies, M., B. Guenther, J. Leavy, T. Mitchell, and T. Tanner, 2009: Climate change adaptation, disaster risk reduction and social protection: complementary roles in agriculture and rural growth? IDS Working Papers, 2009(320), 01-37. De Jode, H., 2010: Modern and Mobile: The Future of Livestock Production in Africa's Drylands. International Institute for Environment and Development (IIED), London, pp. 1-92. De Schutter, O., 2011: How not to think of land-grabbing: three critiques of large-scale investments in farmland. The Journal of Peasant Studies, 38(2), 249-279. de Sherbinin, A., M. Castro, F. Gemenne, M. Cernea, S. Adamo, P. Fearnside, G. Krieger, S. Lahmani, A. OliverSmith, and A. Pankhurst, 2011: Preparing for Resettlement Associated with Climate Change. Science, 334(6055), 456-457. Deininger, K.W., D. Byerlee, J.C.O.N. Lindsay, A.C.O.N. Norton, and H.C.O.N. Selod, 2011: Rising global interest in farmland: can it yield sustainable and equitable benefits? World Bank, Washington DC, USA, pp. 264. Demetriades, J. and E. Esplen, 2008: The gender dimensions of poverty and climate change adaptation. Ids Bulletin, 39(4), 24-31. Denton, F., 2002: Climate change vulnerability, impacts, and adaptation: why does gender matter? Gender and Development, 10(2), 10-20. Dercon, S., 2006: Vulnerability: a micro perspective. World Bank, Washington DC, USA, pp. 117-146. Dercon, S., 2011: Social Protection, Efficiency and Growth. Centre for the Study of African Economies (CSAE), University of Oxford, UK, pp. 1-29. Devereux, S., R. Sabates-Wheeler, M. Tefera, and H. Taye, 2006: Ethiopia’s Productive Safety Net Programme (PSNP): Trends in PSNP transfers within targeted households. Institute of Development Studies (IDS), Sussex, UK, pp. 1-72. Devereux, S., M. Davies, A. McCord, R. Slater, N. Freeland, F. Ellis, and P. White, 2010: Social protection in Africa: where next?. Institute of Development Studies (IDS), Brighton, UK, pp. 1-9. Devereux, S., J.A. McGregor, and R. Sabates-Wheeler, 2011: Introduction: Social Protection for Social Justice. IDS Bulletin, 42(6), 1-9. Devitt, C. and R.S.J. Tol, 2012: Civil war, climate change, and development: A scenario study for sub-Saharan Africa. Journal of Peace Research, 49(1), 129-145. Dollar, D., T. Kleineberg, and A. Kraay, 2013: Growth still is good for the poor. In: World Bank Policy Research Working Paper No. 6568. World Bank, Washington DC, USA, pp. 1-35. Subject to Final Copyedit 35 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 13 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 Dossou, K.M.R. and B. Glehouenou-Dossou, 2007: The vulnerability to climate change of Cotonou (Benin) the rise in sea level. Environment and Urbanization, 19(1), 65-79. Douglas, I., K. Alam, M.A. Maghenda, Y. Mcdonnell, L. McLean, and J. Campbell, 2008: Unjust waters: climate change, flooding and the urban poor in Africa. Environment and Urbanization, 20(1), 187-205. Dunne, J.P., R.J. Stouffer, and J.G. John, 2013: Reductions in labour capacity from heat stress under climate warming. Nature Climate Change, published on-line 24 February 2013, 1-4. Dyer, J.C., L.C. Stringer, and A.J. Dougill, 2012: Jatropha curcas: Sowing local seeds of success in Malawi?: In response to Achten et al. (2010). Journal of Arid Environments, 79(0), 107-110. Eakin, H., K. Benessaiah, J.F. Barrera, G.M. Cruz-Bello, and H. Morales, 2012: Livelihoods and landscapes at the threshold of change: disaster and resilience in a Chiapas coffee community. Regional Environmental Change, 12(3), 475-488. Eakin, H.C. and M.B. Wehbe, 2009: Linking local vulnerability to system sustainability in a resilience framework: two cases from Latin America. Climatic Change, 93(3), 355-377. Easterling, W.E., P.K. Aggarwal, P. Batima, K.M. Brander, L. Erda, S.M. Howden, A. Kirilenko, J. Morton, J. Schmidhuber, and F.N. Tubiello, 2007: Food, fibre and forest products. In: Contribution of Working Group {II} to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. [Parry, {.L.}., O.F. Canziani, {.P.}. Palutikof, {.J.}. van der Linden, and {.E.}. Hanson(eds.)]. Cambridge, Cambridge, {UK}, pp. 273-313. Eastham, J., F. Mpelasoka, M. Mainuddin, C. Ticehurst, P. Dyce, G. Hodgson, R. Ali, and M. Kirby, 2008: Mekong river basin water resources assessment: Impacts of climate change. CSIRO, Canberra, Australia, pp. 1-153. Edenhofer, O., R. Pichs-Madruga, Y. Sokona, K. Seyboth, P. Matschoss, S. Kadner, T. Zwickel, P. Eickemeier, G. Hansen, and S. Schlömer, 2011: The IPCC Special Report on Renewable Energy Sources and Climate Change Mitigation Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, . Edward, P. and A. Sumner, 2013a: The Future of Global Poverty in a Multi-Speed World: New Estimates of Scale and Location, 2010–2030. In: Centre for Global Development (CGD) Working Paper. Centre for Global Development, Washington, DC, USA, pp. 1-107. Edward, P. and A. Sumner, 2013b: The Geography of Inequality. In: Centre for Global Development (CGD) Working Paper. Centre for Global Development, Washington, DC, USA. Elbers, C., J.W. Gunning, and B. Kinsey, 2007: Growth and Risk: Methodology and Micro Evidence. World Bank Economic Review, 21(1), 1-20. Elliott, J.R. and J. Pais, 2006: Race, class, and Hurricane Katrina: Social differences in human responses to disaster. Social Science Research, 35(2), 295-321. Ellis, F. and S. Biggs, 2001: Evolving Themes in Rural Development 1950s‐2000s. Development Policy Review, 19(4), 437-448. Ellis, F., M. Kutengule, and A. Nyasulu, 2003: Livelihoods and rural poverty reduction in Malawi. World Development, 31(9), 1495-1510. Elobeid, A. and C. Hart, 2008: Ethanol Expansion in the Food versus Fuel Debate: How Will Developing Countries Fare? Journal of Agricultural & Food Industrial Organization, 5(2), 1-21. El-Raey, M., K. Dewidar, and M. El-Hattab, 1999: Adaptation to the impacts of sea level rise in Egypt. Mitigation and Adaptation Strategies for Global Change, 4(3), 343-361. Eriksen, C., N. Gill, and L. Head, 2010: The gendered dimensions of bushfire in changing rural landscapes in Australia. Journal of Rural Studies, 26(4), 332-342. Eriksen, S. and J. Lind, 2009: Adaptation as a political process: Adjusting to drought and conflict in Kenya’s drylands. Environmental Management, 43(5), 817-835. Eriksen, S. and J.A. Silva, 2009: The vulnerability context of a savanna area in Mozambique: household drought coping strategies and responses to economic change. Environmental Science & Policy, 12(1), 33-52. Eriksen, S. and A. Marin, 2011: Pastoral pathways. Climate change adaptation lessons from Ethiopia. Department of International Environment and Development Studies, Norwegian University of Life Sciences, Aas, Norway. Eriksen, S.H. and K. O'Brien, 2007: Vulnerability, poverty and the need for sustainable adaptation measures. Climate Policy, 7(4), 337-352. Eriksen, S., P. Aldunce, C. Bahinipati, Sekhar, M., D. Rafael, J. Molefe, C. Nhemachena, K. O'Brien, F. Olorunfemi, J. Park, L. Sygna, and K. Ulsrud, 2011: When not every response to climate change is a good one: Identifying principles for sustainable adaptation. Climate and Development, 3(1), 7-20. Subject to Final Copyedit 36 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 13 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 Estrada, M. and E. Corbera, 2012: The Potential of Carbon Offsetting Projects in the Forestry Sector for Poverty Reduction in Developing Countries: The Application of Ecology in Development Solutions. In: Integrating Ecology and Poverty Reduction. [Carter Ingram, J., F. DeClerck, and C. Rumbaitis del Rio(eds.)]. Springer, New York, NY, USA, pp. 137-147. Fankhauser, S. and G. Schmidt-Traub, 2011: From adaptation to climate-resilient development: the costs of climateproofing the Millennium Development Goals in Africa. Climate and Development, 3(2), 94-113. Fashae, O.A. and O.D. Onafeso, 2011: Impact of climate change on sea level rise in Lagos, Nigeria. International Journal of Remote Sensing, 32(24), 9811-9819. Ferreira, V.R.S. and C.S. Passador, 2011: Potentials and limits to generate employment and income by the National Programme for Production and Use of Biodiesel. Organizações Rurais & Agroindustriais, 12(1), 20-33. Field, C.B., V. Barros, T.F. Stocker, D. Qin, D.J. Dokken, K.L. Ebi, M.D. Mastrandrea, K.J. Mach, G.-. Plattner, S.K. Allen, M. Tignor, and P.M. Midgley, 2012a: Summary for Policymakers. In: Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation. A Special Report of Working Groups I and II of the Intergovernmental Panel on Climate Change. IPCC, Cambridge University Press, Cambridge, U.K. and New York, N.Y., USA. Field, C.B., V. Barros, T.F. Stocker, D. Qin, D. Dokken, K. Ebi, M. Mastrandrea, K. Mach, G. Plattner, and S. Allen, 2012b: Managing the risks of extreme events and disasters to advance climate change adaptation. A Special Report of Working Groups I and II of the Intergovernmental Panel on Climate Change Cambridge University Press, Cambridge, UK, and New York, NY, USA, . Field, C.B., L.D. Mortsch, M. Brklacich, D.L. Forbes, P. Kovacs, S.W. Running, and M.J. Scott, 2007: North America. In: Climate Change 2007: Impacts, Adaptation and Vulnerability. Contribution of Working Group {II} to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. [Parry, {.L.}., O.F. Canziani, {.P.}. Palutikof, {.J.}. van der Linden, and {.E.}. Hanson(eds.)]. Cambridge University Press, Cambridge, {UK}, pp. 617-652. Fisher, M., M. Chaudhury, and B. McCusker, 2010: Do Forests Help Rural Households Adapt to Climate Variability? Evidence from Southern Malawi. World Development, 38(9), 1241-1250. Ford, J.D., 2009: Vulnerability of Inuit food systems to food insecurity as a consequence of climate change: a case study from Igloolik, Nunavut. Regional Environmental Change, 9(2), 83-100. Fordham, M., S. Gupta, S. Akerkar, and M. Scharf, 2011: Leading Resilient Development: Grassroots Women’s Priorities, Practices and Innovations. . UNDP, New York, NY, USA, pp. 1-84. Fortin, E., 2011: Multi-stakeholder initiatives to regulate biofuels: the Roundtable for Sustainable Biofuels. Paper presented at the International Conference on Global Land Grabbing, 6-8 April 2011. Land Deal Politics Initiative (LDPI), Brighton, UK, pp. 1-15. Frumkin, H., J. Hess, G. Luber, J. Malilay, and M. McGeehin, 2008: Climate change: the public health response. American Journal of Public Health, 98(3), 435-445. Funk, C., M.D. Dettinger, J.C. Michaelsen, J.P. Verdin, M.E. Brown, M. Barlow, and A. Hoell, 2008: Warming of the Indian Ocean threatens eastern and southern African food security but could be mitigated by agricultural development. Proceedings of the National Academy of Sciences, 105(32), 11081. Fussell, E., N. Sastry, and M. VanLandingham, 2010: Race, socioeconomic status, and return migration to New Orleans after Hurricane Katrina. Population & Environment, 31(1), 20-42. Gabrielsson, S., S. Brogaard, and A. Jerneck, 2012: Living without buffers: Illustrating climate vulnerability in the Lake Victoria basin. Sustainability Science, October 2012, 1-15. Gabrielsson, S. and V. Ramasar, 2012: Widows: agents of change in a climate of water uncertainty. Journal of Cleaner Production, In press, 1-9. Gagnon-Lebrun, F. and S. Agrawala, 2006: Progress on Adaptation to Climate Change in Developed Countries: An Analysis of Broad Trends. OECD, Paris, France, pp. 1-62. Gaiha, R. and A.B. Deolalikar, 1993: Persistent, Expected and Innate Poverty: estimates for semi-arid rural South India, 1975-1984. Cambridge Journal of Economics, 17(4), 409-421. Galaz, V., F. Moberg, T.E. Downing, F. Thomalla, and K. Warner, 2008: Ecosystem under Pressure. Commission on Climate Change and Development, Stockholm, Sweden, pp. 1-6. García-Pina, R., A. Tobías Garcés, J. Sanz Navarro, C. Navarro Sánchez, and A. García-Fulgueiras, 2008: Efecto del calor sobre el número de urgencias hospitalarias en la Región de Murcia durante los veranos del período 20002005 y su uso en la vigilancia epidemiológica. Revista Española De Salud Pública, 82(2), 153-166. Subject to Final Copyedit 37 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 13 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 Gasper, D.R., A.V. Portocarrero, and A. Lera St Clair, 2013: Climate Change and Development Framings: A Comparative Analysis of the Human Development Report 2007/8 an the World Development Report 2010. Global Environmental Change, 23(1), 28-39. Gentle, P. and T.N. Maraseni, 2012: Climate change, poverty and livelihoods: adaptation practices by rural mountain communities in Nepal. Environmental Science & Policy, 21, 24-34. Gerlitz, J., K. Hunzai, and B. Hoermann, 2012: Mountain poverty in the Hindu-Kush Himalayas. Canadian Journal of Development Studies/Revue Canadienne D'Études Du Développement, 33(2), 250-265. Ghazoul, J., R.A. Butler, J. Mateo-Vega, and L.P. Koh, 2010: REDD: a reckoning of environment and development implications. Trends in Ecology & Evolution, 25(7), 396-402. Ghosh, J., 2010: The unnatural coupling: Food and global finance. Journal of Agrarian Change, 10(1), 72-86. Gigli, S. and S. Agrawala, 2007: Stocktaking of progress on integrating adaptation to climate change into development co-operation activities. OECD, Paris, France, pp. 1-85. Gilligan, D.O., J. Hoddinott, and A.S. Taffesse, 2009: The impact of Ethiopia's Productive Safety Net Programme and its linkages. The Journal of Development Studies, 45(10), 1684-1706. Giné, X., R. Townsend, and J. Vickery, 2008: Patterns of rainfall insurance participation in rural India. The World Bank Economic Review, 22(3), 539-566. Giné, X. and D. Yang, 2009: Insurance, credit, and technology adoption: Field experimental evidencefrom Malawi. Journal of Development Economics, 89(1), 1-11. Glenna, L. and D.R. Cahoy, 2009: Agribusiness concentration, intellectual property, and the prospects for rural economic benefits from the emerging biofuel economy. Southern Rural Sociology, 24(2), 111-129. Goh, A.H.X., 2012: A literature review of the gender-differentiated impacts of climate change on women’s and men’s assets and well-being in developing countries. IFPRI (International Food Policy Research Institute), Washington DC, USA, pp. 1-44. Gong, Y., 2010: Integrating Social Capital into Institutional Analysis of the Guangxi CDM Forest-based Carbon Sequestration Project. Economy and Environment Program for Southeast Asia, Singapore, pp. 1-32. Gopinathan, M.C. and R. Sudhakaran, 2011: Biofuels: opportunities and challenges in India. In: Biofuels: Global Impact on Renewable Energy, Production Agriculture, and Technological Advancements. [Tomes, D., P. Lakshmanan, and D. Songstad(eds.)]. Springer, New York, NY, USA, pp. 173-209. Gough, I., 2010: Economic crisis, climate change and the future of welfare states. Twenty-First Century Society, 5(1), 51-64. Green, D., L. Alexander, K. Mclnnes, J. Church, N. Nicholls, and N. White, 2010: An assessment of climate change impacts and adaptation for the Torres Strait Islands, Australia. Climatic Change, 102(3), 405-433. Gupta, A., E. Lövbrand, E. Turnhout, and M.J. Vijge, 2012: In pursuit of carbon accountability: the politics of REDD measuring, reporting and verification systems. Current Opinion in Environmental Sustainability, 4(6), 726-731. Hahn, G., 1997: Dynamic responses of cattle to thermal heat loads. Journal of Animal Science, 77, 10-20. Hall, J., S. Matos, L. Severino, and N. Beltrão, 2009: Brazilian biofuels and social exclusion: established and concentrated ethanol versus emerging and dispersed biodiesel. Journal of Cleaner Production, 17, S77-S85. Halstead, P. and J. O'Shea, 2004: Bad year economics: Cultural Responses to Risk and Uncertainty. Cambridge University Press, Cambridge, MA, USA, pp. 160. Hanff, E., M. Dabat, and J. Blin, 2011: Are biofuels an efficient technology for generating sustainable development in oil-dependent African nations? A macroeconomic assessment of the opportunities and impacts in Burkina Faso. Renewable and Sustainable Energy Reviews, 15(5), 2199-2209. Hardoy, J. and G. Pandiella, 2009: Urban poverty and vulnerability to climate change in Latin America. Environment and Urbanization, 21(1), 203-224. Hardoy, J., G. Pandiella, and L.S.V. Barrero, 2011: Local disaster risk reduction in Latin American urban areas. Environment and Urbanization, 23(2), 401-413. Hargreaves, D., 2013: Gender and Climate Change: Implications for Responding to the Needs of Those Affected by Natural Disasters and Other Severe Weather Events. In: Research, Action and Policy: Addressing the Gendered Impacts of Climate Change. [Alston, M. and K. Whittenbury(eds.)]. Springer, Netherlands, pp. 277-281. Hassan, R. and C. Nhemachena, 2008: Determinants of African farmers’ strategies for adapting to climate change: Multinomial choice analysis. African Journal of Agricultural and Resource Economics, 2(1), 83-104. Hayes, T. and L. Persha, 2010: Nesting local forestry initiatives: Revisiting community forest management in a REDD+ world. Forest Policy and Economics, 12(8), 545-553. Subject to Final Copyedit 38 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 13 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 Hazeleger, T., 2013: Gender and disaster recovery: Strategic issues and action in Australia. Australian Journal of Emergency Management, The, 28(2), 40. Heckenberg, D. and I. Johnston, 2012: Climate Change, Gender and Natural Disasters: Social Differences and Environment-Related Victimisation. In: Climate Change from a Criminological Perspective. Springer, pp. 149171. Hellmuth, M.E. and IRI, 2007: Climate risk management in Africa: Learning from practice. International Research Institute for Climate and Society, the Earth Institute, Columbia University, New York, NY, USA, pp. 1-88. Heltberg, R., P.B. Siegel, and S.L. Jorgensen, 2009: Addressing human vulnerability to climate change: Toward a ‘no-regrets’ approach. Global Environmental Change, 19(1), 89-99. Hertel, T.W., M.B. Burke, and D.B. Lobell, 2010: The poverty implications of climate-induced crop yield changes by 2030. Global Environmental Change, 20(4), 577-585. Hertel, T.W. and S.D. Rosch, 2010: Climate change, agriculture, and poverty. Applied Economic Perspectives and Policy, 32(3), 355-385. Hett, C., A. Heinimann, M.l. Epprecht, P. Messerli, and K. Hurni, 2012: Carbon Pools and Poverty Peaks in Lao PDR: Spatial Data Inform Policy-making for REDD at the National Level. Mountain Research and Development, 32(4), 390-399. Hewitt, K. and M. Mehta, 2012: Rethinking Risk and Disasters in Mountain Areas. Revue De Géographie Alpine.Journal of Alpine Research, (100-1), 1-12. Hochrainer-Stigler, S., R.B. Sharma, and R. Mechler, 2012: Disaster Microinsurance for Pro-Poor Risk Management: Evidence from South Asia. IDRiM Journal, 2(2). Hollander, G., 2010: Power is sweet: sugarcane in the global ethanol assemblage. The Journal of Peasant Studies, 37(4), 699-721. Homewood, K., 2009: Ecology of African Pastoralist Societies. James Currey, Oxford, UK, pp. 320. Hope, K.R., 2009: climate change and poverty in Africa. International Journal of Sustainable Development & World Ecology, 16(6), 451-461. Horton, G., L. Hanna, and B. Kelly, 2010: Drought, drying and climate change: Emerging health issues for ageing Australians in rural areas. Australasian Journal on Ageing, 29(1), 2-7. Houghton, R., 2009: ‘Everything became a struggle, absolute struggle’ Post- flood increases in domestic violence in New Zealand. In: Women, Gender and Disaster: Global Issues and Initiatives. [Enarson, E. and P.G.D. Chakrabarti(eds.)]. Sage Publications, India Pvt Ltd., New Delhi, India, pp. 99-111. Howden, S.M., J.F. Soussana, F.N. Tubiello, N. Chhetri, M. Dunlop, and H. Meinke, 2007: Adapting agriculture to climate change. Proceedings of the National Academy of Sciences, 104(50), 19691-19696. Huang, C., A.G. Barnett, X. Wang, P. Vaneckova, G. FitzGerald, and S. Tong, 2011: Projecting future heat-related mortality under climate change scenarios: a systematic review. Environmental Health Perspectives, 119(12), 1681-1690. Hulme, D. and A. Shepherd, 2003: Conceptualizing chronic poverty. World Development, 31(3), 403-423. Huq, S., F. Yamin, A. Rahman, A. Chatterjee, X. Yang, S. Wade, V. Orindi, and J. Chigwada, 2005: Linking climate adaptation and development: A synthesis of six case studies from Asia and Africa. IDS Bulletin, 36(4), 117-122. IEG, 2012: Adapting to Climate Change: Assessing the World Bank Group Experience Phase III. Independent Evaluation Group of the World Bank, Washington DC, USA, pp. 1-193. IFAD, 2011: Rural Poverty Report 2011. New realities, new challenges: New opportunities for tomorrow's generation. International Fund for Agricultural Development, Rome, Italy, pp. 1-322. IFRC, 2010: World Disasters Report 2010: Focus on Urban Risk. International Federation of Red Cross and Red Crescent Societies, Geneva, pp. 1-220. Iglesias, A., S. Quiroga, and A. Diz, 2011: Looking into the future of agriculture in a changing climate. European Review of Agricultural Economics, 38(3), 427-447. IPCC, 2007: Climate Change 2007: Synthesis Report. Contribution of Working Groups I, II and III to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change [. IPCC, Geneva, Switzerland, pp. 104. Iwasaki, S., B.H.N. Razafindrabe, and R. Shaw, 2009: Fishery livelihoods and adaptation to climate change: a case study of Chilika lagoon, India. Mitigation and Adaptation Strategies for Global Change, 14(4), 339-355. Jabeen, H., C. Johnson, and A. Allen, 2010: Built-in resilience: learning from grassroots coping strategies for climate variability. Environment and Urbanization, 22(2), 415-431. Subject to Final Copyedit 39 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 13 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 Jacoby, H., M. Rabassa, and E. Skouas, 2011: Distributional implications of climate change in India. World Bank, Washington DC, USA, pp. 1-56. Jalan, J. and M. Ravallion, 1998: Transient poverty in postreform rural China. Journal of Comparative Economics, 26(2), 338-357. Jalan, J. and M. Ravallion, 2000: Is transient poverty different? Evidence for rural China. The Journal of Development Studies, 36(6), 82-99. Jankowska, M., D. Lopez-Carr, C. Funk, G. Husak, and Z. Chafe, 2012: Climate change and human health: Spatial modeling of water availability, malnutrition, and livelihoods in Mali, Africa. Applied Geography, 33, 4-15. Jarosz, L., 2012: Growing inequality: agricultural revolutions and the political ecology of rural development. International Journal of Agricultural Sustainability, 10(2), 192-199. Jenkins, P. and B. Phillips, 2008: Battered Women, Catastrophe, and the Context of Safety after Hurricane Katrina. NWSA, 20(3), 49-68. Jerneck, A. and L. Olsson, 2012: A smoke-free kitchen: initiating community based co-production for cleaner cooking and cuts in carbon emissions. Journal of Cleaner Production, In Press. Jindal, R., B. Swallow, and J. Kerr, 2008: Forestry‐based carbon sequestration projects in Africa: Potential benefits and challenges. Natural Resources Forum, 32(2), 116-130. Jindal, R., 2010: Livelihood impacts of payments for forest carbon services: field evidence from Mozambique. In: Payments for Environmental Services, Forest Conservation and Climate Change: Livelihoods in the REDD? [Tacconi, L., S. Mahanty, and H. Suich(eds.)]. Edward Elgar, Cheltenham, UK; Northampton, MA, USA, pp. 185-211. Jones, P.G. and P.K. Thornton, 2009: Croppers to livestock keepers: livelihood transitions to 2050 in Africa due to climate change. Environmental Science & Policy, 12(4), 427-437. Julia and B. White, 2012: Gendered experiences of dispossession: oil palm expansion in a Dayak Hibun community in West Kalimantan. Journal of Peasant Studies, 39(3-4), 995-1016. Kabubo‐Mariara, J., 2008: Climate change adaptation and livestock activity choices in Kenya: An economic analysis. Natural Resources Forum, 32(2), 131-141. Kaijser, A. and A. Kronsell, 2013: Climate change through the lens of intersectionality. Environmental Politics, In press. Kakota, T., D. Nyariki, D. Mkwambisi, and W. Kogi-Makau, 2011: Gender vulnerability to climate variability and household food insecurity. Climate and Development, 3(4), 298-309. Kanowski, P.J., C.L. McDermott, and B.W. Cashore, 2011: Implementing REDD : lessons from analysis of forest governance. Environmental Science & Policy, 14(2), 111-117. Karambiri, H., S. García Galiano, J. Giraldo, H. Yacouba, B. Ibrahim, B. Barbier, and J. Polcher, 2011: Assessing the impact of climate variability and climate change on runoff in West Africa: the case of Senegal and Nakambe River basins. Atmospheric Science Letters, 12(1), 109-115. Karavai, M. and M. Hinostroza, 2013: Conceptualizations of sustainability in carbon markets. Climate and Development, (ahead-of-print), 1-13. Karlan, D., R.D. Osei, I. Osei-Akoto, and C. Udry, 2012: Agricultural Decisions After Relaxing Credit and Risk Constraints, . Karver, J., C. Kenny, and A. Sumner, 2012: MDGs 2.0: What Goals, Targets, and Timeframe?. In: Working paper 297. Center for Global Development, Washington, DC: USA, pp. 1-57. Kates, R.W., 2000: Cautionary tales: adaptation and the global poor. Climatic Change, 45(1), 5-17. Kaygusuz, K., 2011: Energy services and energy poverty for sustainable rural development. Renewable and Sustainable Energy Reviews, 15(2), 936-947. Kaygusuz, K., 2012: Energy for sustainable development: A case of developing countries. Renewable and Sustainable Energy Reviews, 16(2), 1116-1126. Keshavarz, M., E. Karami, and F. Vanclay, 2013: The social experience of drought in rural Iran. Land use Policy, 30(1), 120-129. Klein, R.J.T., E.L.F. Schipper, and S. Dessai, 2005: Integrating mitigation and adaptation into climate and development policy: three research questions. Environmental Science & Policy, 8(6), 579-588. Kovats, R.S. and S. Hajat, 2008: Heat stress and public health: a critical review. Annu.Rev.Public Health, 29, 41-55. Krause, T. and L. Loft, 2013: Benefit Distribution and Equity in Ecuador's Socio Bosque Program. Society and Natural Resources, (in press). Subject to Final Copyedit 40 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 13 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 Kumar, S., A. Chaube, and S.K. Jain, 2011: Critical review of jatropha biodiesel promotion policies in India. Energy Policy, 41(February 2012), 775-781. Kurukulasuriya, P. and R. Mendelsohn, 2007: Crop selection: adapting to climage change in Africa. World Bank Policy Research Working Paper No. 4307. World Bank, Washington DC, USA, pp. 1-29. Lacombe, G., M. McCartney, and G. Forkuor, 2012: Drying climate in Ghana over the period 1960–2005: evidence from the resampling-based Mann-Kendall test at local and regional levels. Hydrological Sciences Journal, 57(8), 1594-1609. Laderach, P., M. Lundy, A. Jarvis, J. Ramirez, E.P. Portilla, K. Schepp, and A. Eitzinger, 2011: Predicted impact of climate change on coffee supply chains. Climate Change Management, (4), 703-723. Laderchi, C.R., R. Saith, and F. Stewart, 2003: Does it matter that we do not agree on the definition of poverty? A comparison of four approaches. Oxford Development Studies, 31(3), 243-274. Lambrou, Y. and G. Paina, 2006: Gender: the missing component of the response to climate change. Food and agriculture organization of the United Nations (FAO), Rome, Italy, pp. 45. Lambrou, Y. and S. Nelson, 2013: Gender Issues in Climate Change Adaptation: Farmers’ Food Security in Andhra Pradesh. In: Research, Action and Policy: Addressing the Gendered Impacts of Climate Change. Springer, pp. 189-206. Larson, A.M., 2011: Forest tenure reform in the age of climate change: Lessons for REDD. Global Environmental Change, 21(2), 540-549. Le Blanc, D., W. Liu, O'Conner, D. D., and I. Zubcevic, 2012: Issue 1: Development Cooperation in the Light of Sustainable Development and the SDGs: Preliminary Explorations of the Issues. In: Rio+20 Working Papers. United Nations Division of Sustainable Development. (UNDESA), New York, NY, USA, pp. 1-25. Leach, M., R. Mearns, and I. Scoones, 1999: Environmental entitlements: dynamics and institutions in communitybased natural resource management. World Development, 27(2), 225-247. Leary, N., J. Adejuwon, V. Barros, I. Burton, J. Kulkarni, and R. Lasco, 2008: Climate change and adaptation. Earthscan/James & James, London, UK; Sterling, VA, USA, pp. 376. Leichenko, R.M. and K.L. O'Brien, 2008: Environmental change and globalization: Double exposures. Oxford University Press, New York, USA, pp. 192. Lemos, M.C., E. Boyd, E.L. Tompkins, H. Osbahr, and D. Liverman, 2007: Developing adaptation and adapting development. Ecology and Society, 12(2), 1-4. Li, Y., D. Conway, Y. Wu, Q. Gao, S. Rothausen, W. Xiong, H. Ju, and E. Lin, 2013: Rural livelihoods and climate variability in Ningxia, Northwest China. Climatic Change, 119(3-4), 1-14. Linnerooth-Bayer, J. and R. Mechler, 2006: Insurance for assisting adaptation to climate change in developing countries: a proposed strategy. Climate Policy, 6(6), 621-636. Little, P.D., M.P. Stone, T. Mogues, A.P. Castro, and W. Negatu, 2006: ‘Moving in place’: Drought and poverty dynamics in South Wollo, Ethiopia. The Journal of Development Studies, 42(2), 200-225. Little, P.D., J. McPeak, C.B. Barrett, and P. Kristjanson, 2008: Challenging orthodoxies: understanding poverty in pastoral areas of East Africa. Development and Change, 39(4), 587-611. Liu, J., S. Fritz, C. Van Wesenbeeck, M. Fuchs, L. You, M. Obersteiner, and H. Yang, 2008: A spatially explicit assessment of current and future hotspots of hunger in Sub-Saharan Africa in the context of global change. Global and Planetary Change, 64(3-4), 222-235. Liverman, D.M., 2009: Conventions of climate change: constructions of danger and the dispossession of the atmosphere. Journal of Historical Geography, 35(2), 279-296. Lobell, D.B., M.B. Burke, C. Tebaldi, M.D. Mastrandrea, W.P. Falcon, and R.L. Naylor, 2008: Prioritizing climate change adaptation needs for food security in 2030. Science, 319(5863), 607-610. Lohmann, L., 2010: Uncertainty markets and carbon markets: Variations on Polanyian themes. New Political Economy, 15(2), 225-254. Lund, E., 2010: Dysfunctional delegation: why the design of the CDM's supervisory system is fundamentally flawed. Climate Policy, 10(3), 277-288. Lynn, K., K. MacKendrick, and E.M. Donoghue, 2011: Social vulnerability and climate change: synthesis of literature. US Department of Agriculture, Forest Service, Pacific Northwest Research Station, Washington DC, USA, pp. 1-76. MacGregor, S., 2010: ‘Gender and climate change’: from impacts to discourses. Journal of the Indian Ocean Region, 6(2), 223-238. Subject to Final Copyedit 41 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 13 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 MacKerron, G.J., C. Egerton, C. Gaskell, A. Parpia, and S. Mourato, 2009: Willingness to pay for carbon offset certification and co-benefits among (high-) flying young adults in the UK. Energy Policy, 37(4), 1372-1381. MacLennan, M. and L. Perch, 2012: Environmental justice in Latin America and the Caribbean: Legal empowerment of the poor in the context of climate change. Climate Law, 3(3), 283-309. Mader, T.L., 2012: Heat Stress-contributing factors, effects and management. In: Proceedings of the Plains Council Spring Conference 2012 Proceedings of Plains Nutrition Council Spring Conference, San Antonio, Texas, 1213 April, 2012, pp. 22-29. Mahanty, S., H. Suich, and L. Tacconi, 2012: Access and benefits in payments for environmental services and implications for REDD : Lessons from seven PES schemes. Land use Policy, 31(March 2013), 38-47. Mahul, O., N. Belete, and A. Goodland, 2009: Index-based livestock insurance in Mongolia. International Food Policy Research Institute (IFPRI), Washington DC, USA. Manik, Y., J. Leahy, and A. Halog, 2013: Social life cycle assessment of palm oil biodiesel: a case study in Jambi Province of Indonesia. The International Journal of Life Cycle Assessment, , 1-7. Manzo, K., 2010: Imaging vulnerability: the iconography of climate change. Area, 42(1), 96-107. Mapfumo, P., F. Mtambanengwe, and R. Chikowo, 2010: Mobilizing local safety nets for enhanced adaptive capacity to climate change and variability in Zimbabwe. In: Adaptation Insights November 2010. No 1. IDRC, Canada, pp. 1-4. Matsaert, H., J. Kariuki, and A. Mude, 2011: Index-based livestock insurance for Kenyan pastoralists: An innovation systems perspective. Development in Practice, 21(3), 343-356. McCright, A.M. and R.E. Dunlap, 2000: Challenging global warming as a social problem: An analysis of the conservative movement's counter-claims. Social Problems, 47(4), 499-522. McDermott, C.L., K. Levin, and B. Cashore, 2011: Building the Forest-Climate Bandwagon: REDD and the Logic of Problem Amelioration. Global Environmental Politics, 11(3), 85-103. McDowell, J. and J. Hess, 2012: Accessing adaptation: Multiple stressors on livelihoods in the Bolivian highlands under a changing climate. Global Environmental Change, 22(2), 342-352. McGranahan, G., D. Balk, and B. Anderson, 2007: The rising tide: assessing the risks of climate change and human settlements in low elevation coastal zones. Environment and Urbanization, 19(1), 17-37. McGregor, G., M. Cox, Y. Cui, Z. Cui, M. Davey, R. Graham, and A. Brookshaw, 2006: Winter-season climate prediction for the UK health sector. Journal of Applied Meteorology and Climatology, 45(12), 1782-1792. McLaughlin, P. and T. Dietz, 2008: Structure, agency and environment: Toward an integrated perspective on vulnerability. Global Environmental Change, 18(1), 99-111. McLeman, R. and B. Smit, 2006: Migration as an adaptation to climate change. Climatic Change, 76(1), 31-53. McSweeney, K. and O.T. Coomes, 2011: Climate-related disaster opens a window of opportunity for rural poor in northeastern Honduras. Proceedings of the National Academy of Sciences, 108(13), 5203. Mearns, R. and A. Norton, 2010: Social dimensions of climate change: equity and vulnerability in a warming world. World Bank Publications, Washington DC, USA, pp. 322. Mechler, R., J. Linnerooth-Bayer, and D. Peppiatt, 2006: Microinsurance for Natural Disaster Risks in Developing Countries. ProVention/IIASA, Austria, pp. 1-31. Meenawat, H. and B.K. Sovacool, 2011: Improving adaptive capacity and resilience in Bhutan. Mitigation and Adaptation Strategies for Global Change, 16(5), 515-533. Melamed, C., 2012: After 2015: contexts, politics and processes for a post-2015 global agreement on development. Overseas Development Institute (ODI), UK, pp. 1-63. Mendelsohn, R., A. Dinar, and L. Williams, 2006: The distributional impact of climate change on rich and poor countries. Environment and Development Economics, 11(02), 159-178. Menon, N., 2009: Rainfall Uncertainty and Occupational Choice in Agricultural Households of Rural Nepal. The Journal of Development Studies, 45(6), 864-888. Mertz, O., K. Halsnæs, J.E. Olesen, and K. Rasmussen, 2009: Adaptation to climate change in developing countries. Environmental Management, 43(5), 743-752. Michaelowa, A. and K. Michaelowa, 2011: Climate business for poverty reduction? The role of the World Bank. The Review of International Organizations, 6(3), 259-286. Michaelowa, A., 2011: Failures of global carbon markets and CDM? 11(1), 839-841. Michaelowa, A., J. Buen, and A. Michaelowa, 2012: The CDM gold rush. In: Carbon markets or climate finance. [Michaelowa, J. and A. Michaelowa(eds.)]. Routledge, Abingdon,UK, pp. 1-38. Subject to Final Copyedit 42 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 13 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 Midgley, G.F. and W. Thuiller, 2011: Potential responses of terrestrial biodiversity in Southern Africa to anthropogenic climate change. Regional Environmental Change, 11, 127-135. Milanovic, B., 2012: Global inequality recalculated and updated: the effect of new PPP estimates on global inequality and 2005 estimates. Journal of Economic Inequality, 10(1), 1-18. Minang, P.A., M.K. McCall, and H.T.A. Bressers, 2007: Community capacity for implementing Clean Development Mechanism projects within community forests in Cameroon. Environmental Management, 39(5), 615-630. Misselhorn, A.A., 2005: What drives food insecurity in southern Africa? A meta-analysis of household economy studies. Global Environmental Change Part A, 15(1), 33-43. Mitchell, D., 2008: A Note on Rising Food Prices. The World Bank Development Prospects Group, Washington DC, USA, pp. 1-21. Mitlin, D. and D. Satterthwaite, 2013: Urban Poverty in the Global South: Scale and Nature. Routledge, London, pp. 354. Mittelman, J.H., 2013: Global Bricolage: emerging market powers and polycentric governance. Third World Quarterly, 34(1), 23-37. Mol, A.P.J., 2012: Carbon flows, financial markets and climate change mitigation. Environmental Development, 1(1), 10-24. Mol, A.P.J., 2010: Environmental authorities and biofuel controversies. Environmental Politics, 19(1), 61-79. Molony, T., 2011: Bioenergy policies in Africa: mainstreaming gender amid an increasing focus on biofuels. Biofuels, Bioproducts and Biorefining, 5(3), 330-341. Montefrio, M.J.F., 2012: Privileged Biofuels, Marginalized Indigenous Peoples The Coevolution of Biofuels Development in the Tropics. Bulletin of Science, Technology & Society, 32(1), 41-55. Montefrio, M.J.F. and D.A. Sonnenfeld, 2013: Global–Local Tensions in Contract Farming of Biofuel Crops Involving Indigenous Communities in the Philippines. Society & Natural Resources, 26(3), 239-253. Morello-Frosch, R., M. Pastor, J. Sadd, and S. Shonkoff, 2009: The climate gap: inequalities in how climate change hurts Americans & how to close the gap. The Program for Environmental and Regional Equity (PERE), University of Southern California, pp. 1-32. Morton, J.F., 2007: The impact of climate change on smallholder and subsistence agriculture. Proceedings of the National Academy of Sciences, 104(50), 19680-19685. Mosse, D., 2010: A relational approach to durable poverty, inequality and power. The Journal of Development Studies, 46(7), 1156-1178. Müller, C., W. Cramer, W.L. Hare, and H. Lotze-Campen, 2011: Climate change risks for African agriculture. Proceedings of the National Academy of Sciences, 108(11), 4313-4315. Murray, C., 2002: Livelihoods research: transcending boundaries of time and space. Journal of Southern African Studies, 28(3), 489-509. Mustalahti, I., A. Bolin, E. Boyd, and J. Paavola, 2012: Can REDD reconcile local priorities and needs with global mitigation benefits? Lessons from Angai Forest, Tanzania. Ecology and Society, 17(1), 16. Muthoni, J.W. and E.E. Wangui, 2013: Women and Climate Change: Strategies for Adaptive Capacity in Mwanga District, Tanzania. African Geographical Review, 32(1), 59-71. Neelormi, S., N. Adri, and A. Uddin Ahmed, 2008: Gender perspectives of increased socio-economic risks of waterlogging in Bangladesh due to climate change

International Ocean Institute, USA, pp. 1-11. Nellemann, C., R. Verma, and L. Hislop, 2011: Women at the frontline of climate change : gender risks and hopes : a rapid response assessment. United Nations Environment Programme; GRID-Arendal, Arendal, Norway, pp. 68. Nelson, V. and T. Stathers, 2009: Resilience, power, culture, and climate: a case study from semi-arid Tanzania, and new research directions. Gender & Development, 17(1), 81-94. Nesamvuni, E., R. Lekalakala, D. Norris, and J. Ngambi, 2012: Effects of climate change on dairy cattle, South Africa. African Journal of Agricultural Research, 7(26), 3867-3872. Neumayer, E. and T. Plümper, 2007: The gendered nature of natural disasters: The impact of catastrophic events on the gender gap in life expectancy, 1981–2002. Annals of the Association of American Geographers, 97(3), 551566. Neupane, S. and K. Shrestha, 2012: Sustainable Forest Governance in a Changing Climate: Impacts of REDD Program on the Livelihood of Poor Communities in Nepalese Community Forestry. OIDA International Journal of Sustainable Development, 4(1), 71-82. Neville, K.J. and P. Dauvergne, 2012: Biofuels and the politics of mapmaking. Political Geography, 31(5), 279-289. Subject to Final Copyedit 43 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 13 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 New, M., D. Liverman, H. Schroder, and K. Anderson, 2011: Four degrees and beyond: the potential for a global temperature increase of four degrees and its implications. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 369(1934), 6-19. Newell, P. and A. Bumpus, 2012: The Global Political Ecology of the Clean Development Mechanism. Global Environmental Politics, 12(4), 49-67. Nightingale, A., 2009: Warming up the climate change debate: A challenge to policy based on adaptation. Journal of Forest and Livelihood, 8(1). Nightingale, A., 2011: Bounding difference: Intersectionality and the material production of gender, caste, class and environment in Nepal. Geoforum, 42(2), 153-162. Niño-Zarazúa, M., 2011: Mexico’s Progresa-Oportunidades and the emergence of social assistance in Latin America. BWPI Working Paper No. 142. Brooks World Poverty Institute, University of Manchester, Manchester, UK, pp. 1-25. Nkem, J., R. Munang, and B.P. Jallow, 2011: Lessons for adaptation in sub-Saharan Africa. Climate change adaptation & development programme (CC Dare). UNEP/UNDP, Nairobi, pp. 1-98. Nkem, J.N., O.A. Somorin, C. Jum, M.E. Idinoba, Y.M. Bele, and D.J. Sonwa, 2012: Profiling climate change vulnerability of forest indigenous communities in the Congo Basin. Mitigation and Adaptation Strategies for Global Change, 18(5), 513-533. Nordhaus, W.D., 2010: Economic aspects of global warming in a post-Copenhagen environment. Proceedings of the National Academy of Sciences, 107(26), 11721-11726. Nussbaum, M.C., 2001: Women and human development: The capabilities approach. Cambridge University Press, Cambridge, UK; New York, NY, USA, pp. 312. Nussbaum, M.C., 2011: Creating Capabilities: The Human Development Approach. Belknap Press, USA, pp. 238. O’Brien, K., 2012: Global environmental change II From adaptation to deliberate transformation. Progress in Human Geography, 36(5), 667-676. Obidzinski, K., R. Andriani, H. Komanidin, and A. Andrianto, 2012: Environmental and social impacts of oil palm plantations and their implications for biofuel production in Indonesia. Ecology and Society, 17(1), 25. O'Brien, G., P. O'Keefe, H. Meena, J. Rose, and L. Wilson, 2008: Climate adaptation from a poverty perspective. Climate Policy, 8(2), 194-201. O'Brien, K., A.L. StClair, and B. Kristoffersen, 2010: Climate change, ethics and human security. Cambridge University Press, New York, NY, USA; Cambridge, UK, pp. 232. O'Brien, K., M. Pelling, A. Patwardhan, S. Hallegatte, A. Maskrey, T. Oki, U. Oswald-Spring, T. Wilbanks, and P.Z. Yanda, 2012: Toward a sustainable and resilient future. In: Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation: A Special Report of Working Groups I and {II} of the Intergovernmental Panel on Climate Change {(IPCC)}. [Field, {.B.}., V. Barros, {.F.}. Stocker, D. Qin, {.J.}. Dokken, {.L.}. Ebi et al.(eds.)]. Cambridge University Press, Cambridge, {UK} and New York, {NY {USA}, pp. 437-486. O'Brien, K.L. and R.M. Leichenko, 2000: Double exposure: assessing the impacts of climate change within the context of economic globalization. Global Environmental Change, 10(3), 221-232. O'Brien, K.L. and R.M. Leichenko, 2003: Winners and losers in the context of global change. Annals of the Association of American Geographers, 93(1), 89-103. O'Connor, A., 2002: Poverty Knowledge: Social Science, Social Policy, and the Poor in Twentieth-Century US History. Princeton University Press, Princeton, NJ, USA, pp. 377. OECD, 2011: Divided We Stand: Why Inequality Keeps Rising. OECD, Paris, France, pp. 1-400. O'Laughlin, B., 2002: Proletarianisation, agency and changing rural livelihoods: forced labour and resistance in colonial Mozambique. Journal of Southern African Studies, 28(3), 511-530. Olsen, K.H., 2007: The clean development mechanism’s contribution to sustainable development: a review of the literature. Climatic Change, 84(1), 59-73. Onta, N. and B.P. Resurreccion, 2011: The Role of Gender and Caste in Climate Adaptation Strategies in Nepal. Mountain Research and Development, 31(4), 351-356. O'Reilly, C.M., S.R. Alin, P.D. Plisnier, A.S. Cohen, and B.A. McKee, 2003: Climate change decreases aquatic ecosystem productivity of Lake Tanganyika, Africa. Nature, 424(6950), 766-768. Orlove, B., 2009: The past, the present and some possible futures of adaptation. In: Adapting to Climate Change: Thresholds, Values, Governance. [Adger, N., I. Lorenzoni, and K. O'Brien(eds.)]. Cambridge University Press, Cambridge, UK, pp. 131-163. Subject to Final Copyedit 44 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 13 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 Orr, Y., R. Schimmer, R. Geerken, A. Castro, D. Taylor, and D. Brokensha, 2012: Ethno-ecology in the shadow of rain and the light of experience: local perceptions of drought and climate change in east Sumba, Indonesia. In: Climate Change and Threatened Communities. [Castro, A.P., D. Taylor, and D.W. Brokensha(eds.)]. Practical Action Publishing, Rugby, UK, pp. 175-184. Ortiz, I. and M. Cummins, 2011: Global inequality: Beyond the bottom billion. A rapid review of income distribution in 141 countries. UNICEF, New York, NY, USA, pp. 1-65. Ortiz, I. and M. Cummins, 2013: The Age of Austerity: A Review of Public Expenditures and Adjustment Measures in 181 Countries. Initiative for Policy Dialogue and the South Centre, New York, NY, USA, pp. 1-60. Osbahr, H., C. Twyman, W. Neil Adger, and D.S.G. Thomas, 2008: Effective livelihood adaptation to climate change disturbance: scale dimensions of practice in Mozambique. Geoforum, 39(6), 1951-1964. Osbahr, H., C. Twyman, W.N. Adger, and D.S.G. Thomas, 2010: Evaluating successful livelihood adaptation to climate variability and change in southern Africa. Ecology and Society, 15(2), 27. Ostfeld, R.S., 2009: Climate change and the distribution and intensity of infectious diseases. Ecology, 90(4), 903905. Ostrom, E., 2010: Polycentric systems for coping with collective action and global environmental change. Global Environmental Change, 20(4), 550-557. Paavola, J. and W.N. Adger, 2006: Fair adaptation to climate change. Ecological Economics, 56(4), 594-609. Paavola, J., 2008: Livelihoods, vulnerability and adaptation to climate change in Morogoro, Tanzania. Environmental Science & Policy, 11(7), 642-654. Pagán Motta, M., 2013: Detecting vulnerable groups in DHHS aspr's EMR data during response: A snapshot of superstorm sandy.Proceedings of 141st APHA Annual Meeting (November 2-November 6, 2013), . Parikh, P., S. Chaturvedi, and G. George, 2012: Empowering change: The effects of energy provision on individual aspirations in slum communities. Energy Policy, 50(November 2012), 477-485. Parkinson, D., C. Lancaster, and A. Stewart, 2011: A numbers game: lack of gendered data impedes prevention of disaster-related family violence. Health Promotion Journal of Australia, 22, 42-45. Parks, B.C. and J.T. Roberts, 2010: Climate change, social theory and justice. Theory, Culture & Society, 27(2-3), 134-166. Patricola, C.M. and K.H. Cook, 2010: Northern African climate at the end of the twenty-first century: an integrated application of regional and global climate models. Climate Dynamics, 35(1), 193-212. Patt, A., P. Suarez, and U. Hess, 2010: How do small-holder farmers understand insurance, and how much do they want it? Evidence from Africa. Global Environmental Change, 20(1), 153-161. Patz, J.A., D. Campbell-Lendrum, T. Holloway, and J.A. Foley, 2005: Impact of regional climate change on human health. Nature, 438(17 November), 310-317. Peach Brown, H., 2011: Gender, climate change and REDD in the Congo Basin forests of Central Africa. International Forestry Review, 13(2), 163-176. Pelling, M., 2010: Adaptation to Climate Change: From Resilience to Transformation. Taylor & Francis, USA, pp. 224. Peralta, A., 2008: Gender and Climate Change Finance: A Case Study from the Philippines. WEDO, New York, NY, USA, pp. 1-22. Peraza, S., C. Wesseling, A. Aragon, R. Leiva, R.A. García-Trabanino, C. Torres, K. Jakobsson, C.G. Elinder, and C. Hogstedt, 2012: Decreased kidney function among agricultural workers in El Salvador. American Journal of Kidney Diseases, 59(4), 531-540. Perch, L. and R. Roy, 2010: Social Policy in the Post-Crisis Context of Small Island Developing States: A Synthesis. United Nations Development Programme (UNDP); International Policy Centre for Inclusive Growth (IPC-IG), Brasilia, Brazil, pp. 40. Perch, L., 2011: Mitigation of What and by What? Adaptation by Whom and for Whom? Dilemmas in elivering for the Poor and the Vulnerable in International Climate Policy. In: Working Paper 79, Brasilia, International Policy Centre for Inclusive Growth. International Policy Centre for Inclusive Growth (IPC-IG), Brasilia, pp. 154. Perch, L., C. Watson, and B. Barry, 2012: Resource inequality: Moving inequalities from the periphery to the centre of the post-2015 agenda. UNDP; International Policy Centre for Inclusive Growth (IPC-IG), Brasilia, Brazil, pp. 1-25. Pereira, R.B. and R. Pereira, 2008: Population health needs beyond ratifying the Kyoto Protocol: a look at occupational deprivation. Rural and Remote Health, 8(927), 1-5. Subject to Final Copyedit 45 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 13 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 Peskett, L., 2007: Biofuels, agriculture and poverty reduction. Overseas Development Institute, London, UK, pp. 16. Peters, P.E., 2013: Conflicts over land and threats to customary tenure in Africa. African Affairs, 112(449), 543-562. Peters-Stanley, M. and K. Hamilton, 2012: Developing Dimension: State of the Voluntary Carbon Markets 2012. Forest Trends Association, Washington DC, USA, pp. 1-110. Petheram, L., K. Zander, B. Campbell, C. High, and N. Stacey, 2010: 'Strange changes': Indigenous perspectives of climate change and adaptation in NE Arnhem Land (Australia). Global Environmental Change, 20(4), 681-692. Petrie, B., 2010: Gender and Climate change: Regional Report. Executive Summary. Heinrich Boll Foundation, Cape Town, South Africa, pp. 1-5. Phelps, J., E.L. Webb, and A. Agrawal, 2010: Does REDD threaten to recentralize forest governance? Science, 328(5976), 312-313. Piao, S., P. Ciais, Y. Huang, Z. Shen, S. Peng, J. Li, L. Zhou, H. Liu, Y. Ma, and Y. Ding, 2010: The impacts of climate change on water resources and agriculture in China. Nature, 467(7311), 43-51. Pielke Jr, R., G. Prins, S. Rayner, and D. Sarewitz, 2007: Lifting the taboo on adaptation. Nature, 445, 597-598. Pierro, R. and B. Desai, 2008: Climate Insurance for the Poor: Challenges for Targeting and Participation. IDS Bulletin, 39(4), 123-129. Pogge, T.W., 2009: Politics as usual: what lies behind the pro-poor rhetoric. Polity, Cambridge, UK; Malden, MA, USA, pp. 224. Pokorny, B., I. Scholz, and W. de Jong, 2013: REDD for the poor or the poor for REDD ? About the limitations of environmental policies in the Amazon and the potential of achieving environmental goals through pro-poor policies. Ecology and Society, 18(2), 3. Polain, J.D., H.L. Berry, and J.O. Hoskin, 2011: Rapid change, climate adversity and the next ‘big dry’: Older farmers' mental health. Australian Journal of Rural Health, 19(5), 239-243. Posey, J., 2009: The determinants of vulnerability and adaptive capacity at the municipal level: Evidence from floodplain management programs in the United States. Global Environmental Change, 19(4), 482-493. Pouliotte, J., B. Smit, and L. Westerhoff, 2009: Adaptation and development: Livelihoods and climate change in Subarnabad, Bangladesh. Climate and Development, 1(1), 31-46. Pradhan, E.K., K.P. West Jr, J. Katz, S.C. LeClerq, S.K. Khatry, and S.R. Shrestha, 2007: Risk of flood‐related mortality in Nepal. Disasters, 31(1), 57-70. Quinn, C.H., G. Ziervogel, A. Taylor, T. Takama, and F. Thomalla, 2011: Coping with multiple stresses in rural South Africa. Ecology and Society, 16(3), 2. Quisumbing, A.R., N. Kumar, and J. Behrman, 2011: Do shocks affect men’s and women’s assets differently? A review of literature and new evidence from Bangladesh and Uganda. IFPRI (International Food Policy Research Institute), Washington DC, USA, pp. 1-48. Rahlao, S., B. Mantlana, H. Winkler, and T. Knowles, 2012: South Africa's national REDD initiative: assessing the potential of the forestry sector on climate change mitigation. Environmental Science & Policy, 17, 24-32. Rahman, M., 2013: Climate Change, Disaster and Gender Vulnerability: A Study on Two Divisions of Bangladesh. American Journal of Human Ecology, 2(2), 72-82. Ravallion, M. and S. Chen, 2012: Monitoring Inequality. . World Bank, Washington, DC., USA. Ray-Bennett, N.S., 2009: Multiple disasters and policy responses in pre‐and post‐independence Orissa, India. Disasters, 33(2), 274-290. Reason, J., 2000: Human error: models and management. BMJ: British Medical Journal, 320(7237), 768. Reed, M.S., G. Podesta, I. Fazey, N. Geeson, R. Hessel, K. Hubacek, D. Letson, D. Nainggolan, C. Prell, and M.G. Rickenbach, 2013: Combining analytical frameworks to assess livelihood vulnerability to climate change and analyse adaptation options. Ecological Economics, 94, 66-77. Reid, P. and C. Vogel, 2006: Living and responding to multiple stressors in South Africa--Glimpses from KwaZuluNatal. Global Environmental Change, 16(2), 195-206. Renton, A., 2009: Suffering the Science: Climate change, people, and poverty. Oxfam International, Boston, MA, USA, pp. 1-61. Resurreccion, B.P., 2011: The Gender and Climate Debate: More of the Same or New Pathways of Thinking and Doing?. In: Asia Security Initiative Policy Series. RSIS Centre for Non-Traditional Security (NTS) Studies, Singapore, pp. 1-22. Subject to Final Copyedit 46 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 13 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 Ribot, J., 2010: Vulnerability Does Not Fall from the Sky: Toward Multiscale, Pro-Poor Climate Policy. In: Social dimensions of climate change: equity and vulnerability in a warming world
. [Mearns, R. and A. Norton(eds.)]. The World Bank, Washington DC, USA, pp. 47-74. Roberts, J.T., 2011: Multipolarity and the new world (dis) order: US hegemonic decline and the fragmentation of the global climate regime. Global Environmental Change, 21(3), 776-784. Robertson, B. and P. Pinstrup-Andersen, 2010: Global land acquisition: neo-colonialism or development opportunity? Food Security, 2(3), 271-283. Rodima-Taylor, D., 2011: Social innovation and climate adaptation: Local collective action in diversifying Tanzania. Applied Geography, 33, 128-134. Röhr, U., 2006: Gender and climate change. Tiempo, 59, 3-7. Rosset, P., 2011: Food sovereignty and alternative paradigms to confront land grabbing and the food and climate crises. Development, 54(1), 21-30. Ruel, M.T., J.L. Garrett, C. Hawkes, and M.J. Cohen, 2010: The food, fuel, and financial crises affect the urban and rural poor disproportionately: a review of the evidence. The Journal of Nutrition, 140(1), 170S-176S. Rulli, M.C., A. Saviori, and P. D’Odorico, 2013: Global land and water grabbing. Proceedings of the National Academy of Sciences, 110(3), 892-897. Runge, C.F. and B. Senauer, 2007: How biofuels could starve the poor. Foreign Affairs, 86:3(3). Sabates-Wheeler, R., T. Mitchell, and F. Ellis, 2008: Avoiding repetition: Time for CBA to engage with the livelihoods literature? IDS Bulletin, 39(4), 53-59. Sachs, J., 2006: The end of poverty: economic possibilities for our time. Penguin Group, New York, NY, USA, pp. 416. Saito, Y., 2009: Gender mainstreaming into community-based disaster management in the context of regional development
. Regional Development Dialogue, 30(1), 37-46. Salack, S., B. Muller, A.T. Gaye, F. Hourdin, and N. Cisse, 2012: Multi-scale analyses of dry spells across Niger and Senegal. Science Et Changements Planétaires/Sécheresse, 23(1), 3-13. Sallu, S.M., C. Twyman, and L.C. Stringer, 2010: Resilient or vulnerable livelihoods? Assessing livelihood dynamics and trajectories in rural Botswana. Ecology and Society, 15(4), 3. Satterthwaite, D. and D. Mitlin, 2013: Reducing Urban Poverty in the Global South. Routledge, New York, NY, USA, pp. 301. Satterthwaite, D., 2011: How can urban centers adapt to climate change with ineffective or unrepresentative local governments? Wiley Interdisciplinary Reviews: Climate Change, 2(5), 767-776. Savaresi, A., 2013: REDD and Human Rights: Addressing Synergies between International Regimes. Ecology and Society, 18(3), 5. Schipper, E.L.F., 2007: Climate change adaptation and development: Exploring the linkages. Working Paper 107. Tyndall Centre for Climate Change Research; South East Asia START Regional Centre, Norwich, UK, pp. 120. Schipper, L. and M. Pelling, 2006: Disaster risk, climate change and international development: scope for, and challenges to, integration. Disasters, 30(1), 19-38. Schlenker, W. and D.B. Lobell, 2010: Robust negative impacts of climate change on African agriculture. Environmental Research Letters, 5, 014010. Schmidhuber, J. and F.N. Tubiello, 2007: Climate Change and Food Security Special Feature: Global food security under climate change. Proceedings of the National Academy of Sciences, 104(50), 19703-19708. Schwartz, J., 2007: A Billion Dollars Later, New Orleans Still at Risk. The New York Times, August 17, 2007. Scoones, I., 1998: Sustainable rural livelihoods: a framework for analysis. Institute of Development Studies Working Paper 72. University of Sussex, Brighton, UK, pp. 1-22. Scoones, I., 2009: Livelihoods perspectives and rural development. The Journal of Peasant Studies, 36(1), 171-196. Scott-Joseph, A., 2010: Financing Recovery: Implications of Natural Disaster Expenditure on the Fiscal Sustainability of the Eastern Caribbean Currency Unit (ECCU) States. Centre for Research on the Epidemiology of Disasters (CRED). Université catholique de Louvain, pp. 1-43. Semenza, J.C., J.E. McCullough, W.D. Flanders, M.A. McGeehin, and J.R. Lumpkin, 1999: Excess hospital admissions during the July 1995 heat wave in Chicago. American Journal of Preventive Medicine, 16(4), 269277. Sen, A.K., 1976: Poverty: an ordinal approach to measurement. Econometrica: Journal of the Econometric Society, 44(2), 219-231. Subject to Final Copyedit 47 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 13 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 Sen, A.K., 1981: Ingredients of famine analysis: availability and entitlements. The Quarterly Journal of Economics, 96(3), 433-464. Sen, A.K., 1985: Commodities and Capabilities. Oxford University Press, Oxford, UK, pp. 104. Sen, A.K., 1999: Development as freedom. Oxford University Press, Oxford, UK, pp. 384. Seo, S.N., R. Mendelsohn, A. Dinar, R. Hassan, and P. Kurukulasuriya, 2009: A Ricardian analysis of the distribution of climate change impacts on agriculture across agro-ecological zones in Africa. Environmental and Resource Economics, 43(3), 313-332. Seo, S.N., 2010: Is an integrated farm more resilient against climate change? A micro-econometric analysis of portfolio diversification in African agriculture. Food Policy, 35(1), 32-40. Shackleton, C.M., S.E. Shackleton, E. Buiten, and N. Bird, 2007: The importance of dry woodlands and forests in rural livelihoods and poverty alleviation in South Africa. Forest Policy and Economics, 9(5), 558-577. Shah, K.U., H.B. Dulal, C. Johnson, and A. Baptiste, 2013: Understanding livelihood vulnerability to climate change: Applying the livelihood vulnerability index in Trinidad and Tobago. Geoforum, 47, 125-137. Shankland, A. and L. Hasenclever, 2011: Indigenous Peoples and the Regulation of REDD in Brazil: Beyond the War of the Worlds? IDS Bulletin, 42(3), 80-88. Sherman, A. and I. Shapiro, 2005: Essential facts about the victims of Hurricane Katrina. Center on Budget and Policy Priorities, Washington DC, USA, pp. 1-3. Sherwood, S.C. and M. Huber, 2010: An adaptability limit to climate change due to heat stress. Proceedings of the National Academy of Sciences, 107(21), 9552-9555. Shin, S., 2010: The domestic side of the clean development mechanism: the case of China. Environmental Politics, 19(2), 237-254. Shonkoff, S., R. Morello-Frosch, M. Pastor, and J. Sadd, 2011: The climate gap: environmental health and equity implications of climate change and mitigation policies in California—a review of the literature. Climatic Change, 109(1), 485-503. Sietz, D., M. Lüdeke, and C. Walther, 2011: Categorisation of typical vulnerability patterns in global drylands. Global Environmental Change, 21(2), 431-440. Sietz, D., S.E. Mamani Choque, and M.K.B. Lüdeke, 2012: Typical patterns of smallholder vulnerability to weather extremes with regard to food security in the Peruvian Altiplano. Regional Environmental Change, 12(3), 489505. Silalertruksa, T., S.H. Gheewala, K. Hünecke, and U.R. Fritsche, 2012: Biofuels and employment effects: Implications for socio-economic development in Thailand. Biomass and Bioenergy, 46(November 2012), 409418. Sissoko, K., H. van Keulen, J. Verhagen, V. Tekken, and A. Battaglini, 2011: Agriculture, livelihoods and climate change in the West African Sahel. Regional Environmental Change, 11, 119-125. Skoufias, E., B. Essama-Nssah, and R.S. Katayama, 2011a: Too little too late: welfare impacts of rainfall shocks in rural Indonesia. World Bank, Washington DC, USA, pp. 22. Skoufias, E., M. Rabassa, S. Olivieri, and M. Brahmbhatt, 2011b: The poverty impacts of climate change. Economic Premise, (51), 1-5. Skoufias, E., K. Vinha, and H. Conroy, 2011c: The impacts of climate variability on welfare in rural Mexico. World Bank, Washington, DC, USA, pp. 1-59. Slater, R., J. Farrington, and R. and Holmes, 2006: Linking agricultural growth and social protection. Inception report. Overseas Development Institute, London, pp. 1-30. Slater, R., L. Peskett, E. Ludi, and D. Brown, 2007: Climate change, agricultural policy and poverty reduction–how much do we know? Natural Resource Perspectives, 109(September 2007), 1-6. Small, L.A., 2007: The sustainable rural livelihoods approach: A critical review. Canadian Journal of Development Studies/Revue Canadienne D'Études Du Développement, 28(1), 27-38. Smit, B. and M.W. Skinner, 2002: Adaptation options in agriculture to climate change: a typology. Mitigation and Adaptation Strategies for Global Change, 7(1), 85-114. Smith, B., I. Burton, R.J.T. Klein, and J. Wandel, 2000: An anatomy of adaptation to climate change and variability. Climatic Change, 45(1), 223-251. Smithers, J. and A. Blay-Palmer, 2001: Technology innovation as a strategy for climate adaptation in agriculture. Applied Geography, 21(2), 175-197. Solomon, S., G.K. Plattner, R. Knutti, and P. Friedlingstein, 2009: Irreversible climate change due to carbon dioxide emissions. Proceedings of the National Academy of Sciences, 106(6), 1704. Subject to Final Copyedit 48 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 13 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 Somorin, O.A., I.J. Visseren-Hamakers, B. Arts, D.J. Sonwa, and A.M. Tiani, 2013: REDD policy strategy in Cameroon: Actors, institutions and governance. Environmental Science & Policy, . Son, J., J. Lee, G.B. Anderson, and M.L. Bell, 2012: The Impact of Heat Waves on Mortality in Seven Major Cities in Korea. 120(4), 566-571. Sowers, J., A. Vengosh, and E. Weinthal, 2011: Climate change, water resources, and the politics of adaptation in the Middle East and North Africa. Climatic Change, 104(3), 599-627. Springate-Baginski, O., O.W. Springate-Baginski, and E. Wollenberg, 2010: REDD, forest governance and rural livelihoods: the emerging agenda. Cifor, Bogor, Indonesia, pp. 289. St.Clair, A.L. and V. Lawson, 2013: From poverty to prosperity: Addressing growth, equity and ethics in a changing environment. In: A Changing Environment for Human Security: Transformative Approaches to Research, Policy and Action. [Sygna, L., K. O'Brien, and J. Wolf(eds.)]. Routledge, London, UK, pp. 1-480. Stern, N., 2009: Managing climate change and overcoming poverty: facing the realities and building a global agreement. Centre for Climate Change Economics and Policy Grantham Research Institute on Climate Change and the Environment, U.K., pp. 1-28. Stringer, L.C., J.C. Dyer, M.S. Reed, A.J. Dougill, C. Twyman, and D. Mkwambisi, 2009: Adaptations to climate change, drought and desertification: local insights to enhance policy in southern Africa. Environmental Science & Policy, 12(7), 748-765. Stringer, L.C., A.J. Dougill, D.D. Mkwambisi, J.C. Dyer, F.K. Kalaba, and M. Mngoli, 2012: Challenges and opportunities for carbon management in Malawi and Zambia. Carbon, 3(2), 159-173. Stringer, L.C., C. Twyman, and D.S.G. Thomas, 2007: Learning to reduce degradation on Swaziland's arable land: enhancing understandings of Striga asiatica. Land Degradation and Development, 18(2), 163-177. Subbarao, S. and B. Lloyd, 2011: Can the clean development mechanism (CDM) deliver? Energy Policy, 39(3), 1600-1611. Sudmeier-Rieux, K., J.C. Gaillard, S. Sharma, J. Dubois, and M. Jaboyedoff, 2012: Floods, Landslides, and Adapting to Climate Change in Nepal: What Role for Climate Change Models? In: Climate Change Modeling For Local Adaptation In The Hindu Kush-Himalayan Region (Community, Environment and Disaster Risk Management , Volume 11). [Lamadrid, A. and I. Kelman(eds.)]. Emerald Group Publishing Limited, pp. 119140. Sulser, T.B., B. Nestorova, M.W. Rosegrant, and T. van Rheenen, 2011: The future role of agriculture in the Arab region’s food security. Food Security, 3, 23-48. Sumner, A., 2010: Global Poverty and the New Bottom Billion: What if Three‐quarters of the World's Poor Live in Middle‐income Countries?. Institute of Development Studies, Brighton, UK, pp. 1-43. Sumner, A., 2012a: Where do the Poor live? World Development, 40(5), 865-877. Sumner, A., 2012b: Where Will the World's Poor Live? An Update on Global Poverty and the New Bottom Billion. Center for Global Development, Washington DC, USA, pp. 1-33. Sumner, A., A. Suryahadi, and N. Thang, 2012: Poverty and inequalities in middle-income Southeast Asia. Institute of Development Studies (IDS), Brighton, UK, pp. 1-20. Sutter, C. and J.C. Parreño, 2007: Does the current Clean Development Mechanism (CDM) deliver its sustainable development claim? An analysis of officially registered CDM projects. Climatic Change, 84(1), 75-90. Swallow, B. and R. Meinzen-Dick, 2009: Payment for Environmental Services: Interactions with Property Rights and Collective Action. In: Institutions and Sustainability: Political Economy of Agriculture and the Environment. [Beckmann, V. and M. Padmanabhan(eds.)]. Springer, Netherlands, pp. 243-265. Syvitski, J.P.M., A.J. Kettner, I. Overeem, E.W.H. Hutton, M.T. Hannon, G.R. Brakenridge, J. Day, C. Vörösmarty, Y. Saito, and L. Giosan, 2009: Sinking deltas due to human activities. Nature Geoscience, 2(10), 681-686. Tacoli, C., 2009: Crisis or adaptation? Migration and climate change in a context of high mobility. Environment and Urbanization, 21(2), 513-525. Tadesse, M. and M.V. Brans, 2012: Risk, coping mechanisms, and factors in the demand for micro-insurance in Ethiopia. Journal of Economics and International Finance, 4(4), 79-91. Tanner, T. and T. Mitchell, 2008: Entrenchment or enhancement: could climate change adaptation help to reduce chronic poverty? IDS Bulletin, 39(4), 6-15. Taylor, J.G. and L. Xiaoyun, 2012: China's Changing Poverty: A Middle Income Country Case Study. Journal of International Development, 24(6), 696-713. Tekken, V. and J.P. Kropp, 2012: Climate-driven or human-induced: Indicating severe water scarcity in the Moulouya River Basin (Morocco). Water, 4(4), 959-982. Subject to Final Copyedit 49 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 13 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 Tennant, W.J. and B.C. Hewitson, 2002: Intra‐seasonal rainfall characteristics and their importance to the seasonal prediction problem. International Journal of Climatology, 22(9), 1033-1048. Teperman, S., 2013: Hurricane Sandy and the greater New York health care system. The Journal of Trauma and Acute Care Surgery, 74(6), 1401-1410. Terry, G., 2009: No climate justice without gender justice: an overview of the issues. Gender & Development, 17(1), 5-18. Thomas, D.S.G., C. Twyman, H. Osbahr, and B. Hewitson, 2007: Adaptation to climate change and variability: farmer responses to intra-seasonal precipitation trends in South Africa. Climatic Change, 83(3), 301-322. Thornton, P.K., P.G. Jones, T. Owiyo, R.L. Kruska, M. Herrero, V. Orindi, S. Bhadwal, P. Kristjanson, A. Notenbaert, and N. Bekele, 2008: Climate change and poverty in Africa: Mapping hotspots of vulnerability. African Journal of Agriculture and Resource Economics, 2(1), 24-44. Thornton, P., M. Herrero, A. Freeman, O. Mwai, E. Rege, P. Jones, and J. McDermott, 2007: Vulnerability, climate change and livestock–research opportunities and challenges for poverty alleviation. Journal of Semi-Arid Tropical Agricultural Research, 4(1), 1-23. Thurlow, J., T. Zhu, and X. Diao, 2009: The impact of climate variability and change on economic growth and poverty in Zambia. International Food Policy Research Institute (IFPRI), Washington DC, USA, pp. 1-72. Tierney, J.E., M.T. Mayes, N. Meyer, C. Johnson, P.W. Swarzenski, A.S. Cohen, and J.M. Russell, 2010: Latetwentieth-century warming in Lake Tanganyika unprecedented since AD 500. Nature Geoscience, 3(6), 422425. Tompkins, E.L., M.C. Lemos, and E. Boyd, 2008: A less disastrous disaster: Managing response to climate-driven hazards in the Cayman Islands and NE Brazil. Global Environmental Change, 18(4), 736-745. Trostle, R., D. Marti, S. Rosen, and P. Wescott, 2011: Why Have Food Commodity Prices Risen Again?. United States Department of Agriculture, Washinton DC, USA, pp. 1-29. Tschakert, P., 2007: Views from the vulnerable: understanding climatic and other stressors in the Sahel. Global Environmental Change, 17(3-4), 381-396. Tschakert, P., R. Tutu, and A. Alcaro, 2011: Embodied experiences of environmental and climatic changes in landscapes of everyday life in Ghana. Emotion, Space and Society, In press. Tubiello, F., J. Schmidhuber, M. Howden, P.G. Neofotis, S. Park, E. Fernandes, and D. Thapa, 2008: Climate Change Response Strategies for Agriculture: Challenges and Opportunities for the 21st Century. Agriculture and Rural Development Discussion Paper. World Bank, Washington DC, USA, pp. 1-75. UN, 2012a: United Nations Conference on Sustainable Development Outcome Document: The Future We Want. UN, pp. 1-49. UN, 2012b: Realizing the Future We Want for All. In: Report to the Secretary General, pp. 1-58. UN ECLAC, 2005: Grenada: A Gender Impact Assessment of Hurricane Ivan - Making the Invisible Visible. UN ECLAC, pp. 1-41. UNCCD, 2011: Desertification: A visual Synthesis. United Nations Convention to Combat Desertification, Bonn, Germany, pp. 1-48. UNDP, 1990: Human Development Report 1990. United Nations Development Program, New York, NY, USA. UNDP, 1994: Human Development Report 1994: New Dimensions of Human Security. UNDP, New York, NY, USA, pp. 1-226. UNDP, 2007: Human Development Report 2007/8. Fighting climate change: Human solidarity in a divided world. United Nations Development Programme (UNDP), New York, NY, USA, pp. 1-399. UNDP, 2011a: Towards an 'Energy Plus' Approach for the Poor: A review of good practices and lessons learned. United Nations Development Programme (UNDP), New York, NY, USA, pp. 1-112. UNDP, 2011b: Human Development Report 2011. Sustainability and Equity: A Better Future for All. United Nations Development Programme (UNDP), New York, NY, USA, pp. 1-185. UNDP, 2011c: An Analysis of the Impact of the Floods On MDGs in Pakistan. UNDP, New York, NY, USA, pp. 1125. UNDP, 2012: Triple Wins for Sustainable Development UNDP (United Nations Development Programme), New York, NY, USA, pp. 1-67. UNECA, 2011: Climate Change and Water Resources of Africa: Challenges, Opportunities and Impacts. Working paper 5. United Nations Economic Commission for Africa (UNECA); African Climate Policy Centre, Addis Abeba, Ethiopia, pp. 1-33. UNFCCC, 2011: Benefits of the Clean Development Mechanism
. UNFCCC, Bonn. Subject to Final Copyedit 50 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 13 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 UNFCCC, 2013: Clean Development Mechanism cdm.unfccc.int/about/ccb/index.html, . UNFPA, 2009: State of World Population, 2009. Facing a Changing World: Women, Population, and Climate. United Nations Population Fund (UNFPA), New York, NY, pp. 1-104. UNISDR, 2009: Global Assessment Report on Disaster Risk Reduction: Risk and Poverty in a Changing Climate
. United Nations International Strategy for Disaster Reduction, Geneva, pp. 1-207. UNISDR, 2011: Revealing Risk, Redefining Development: The 2011 Global Assessment Report on Disaster Risk Reduction. United Nations International Strategy for Disaster Reduction, Geneva, pp. 1-178. UN-REDD, 2011: The Business Case for Mainstreaming Gender in REDD+. UN-REDD, Geneva, Switzerland, pp. 1-44. UNRISD, 2010: Combating Poverty and Inequality: Structural Change, Social Policy and Politics. UNRISD/UN Publications, Geneva, pp. 1-380. Uppal, A., L. Evans, N. Chitkara, P. Patrawalla, M.A. Mooney, D. Addrizzo-Harris, E. Leibert, J. Reibman, L. Rogers, and K.I. Berger, 2013: In Search of the Silver Lining: The Impact of Superstorm Sandy on Bellevue Hospital. Annals of the American Thoracic Society, 10(2), 135-142. Ürge-Vorsatz, D. and S. Tirado Herrero, 2012: Building synergies between climate change mitigation and energy poverty alleviation. Energy Policy, 49(October 2012), 83-90. Urwin, K. and A. Jordan, 2008: Does public policy support or undermine climate change adaptation? Exploring policy interplay across different scales of governance. Global Environmental Change, 18(1), 180-191. Usman, M.T. and C. Reason, 2004: Dry spell frequencies and their variability over southern Africa. Climate Research, 26(3), 199-211. Valdivia, C., A. Seth, J.L. Gilles, M. García, E. Jiménez, J. Cusicanqui, F. Navia, and E. Yucra, 2010: Adapting to climate change in Andean ecosystems: Landscapes, capitals, and perceptions shaping rural livelihood strategies and linking knowledge systems. Annals of the Association of American Geographers, 100(4), 818-834. Van Dam, C., 2011: Indigenous territories and REDD in Latin America: Opportunity or threat? Forests, 2(1), 394414. Van Dijk, T., 2011: Livelihoods, capitals and livelihood trajectories a more sociological conceptualisation. Progress in Development Studies, 11(2), 101-117. Van Noordwijk, M., 2010: Climate change, biodiversity, livelihoods and sustainagility in Southeast Asia. In: Moving Forward: Southeast Asian Perspectives on Climate Change and Biodiversity. [Sajise, P.E., M.V. Ticsay, and J.J.C. Saguiguit(eds.)]. ISEAS / SEARCA, Singapore, pp. 55-83. Verburg, P. and R.E. Hecky, 2009: The physics of the warming of Lake Tanganyika by climate change. Limnology and Oceanography, 54(6), 2418. Von Braun, J. and A. Ahmed, 2008: High food prices: The what, who, and how of proposed policy actions. International Food Policy Research Institute (IFPRI), Washington, DC, pp. 1-12. Von Braun, J., R.S. Meinzen-Dick, and I.F.P.R. Institute, 2009: "Land Grabbing" by Foreign Investors in Developing Countries: Risks and Opportunities. International Food Policy Research Institute (IFPRI), Washington DC, pp. 9. Wassmann, R., S. Jagadish, K. Sumfleth, H. Pathak, G. Howell, A. Ismail, R. Serraj, E. Redona, R. Singh, and S. Heuer, 2009: Regional vulnerability of climate change impacts on Asian rice production and scope for adaptation. Advances in Agronomy, 102, 91-133. Weinzettel, J., E.G. Hertwich, G.P. Peters, K. Steen-Olsen, and A. Galli, 2013: Affluence drives the global displacement of land use. Global Environmental Change, In press. Wheeler, D., 2011: Quantifying vulnerability to climate change: implications for adaptation assistance. Center for Global Development, Washington, D.C., USA. Whittenbury, K., 2013: Climate Change, Women's Health, Wellbeing and Experiences of Gender-Based Violence in Australia. In: Research, Action and Policy: Addressing the Gendered Impacts of Climate Change. [Alston, M. and K. Whittenbury(eds.)]. Springer, Australia, pp. 207-222. Williams, M., 2010: Paper prepared for the Ninth Commonwealth Women’s Affairs Ministers Meeting on Gender Issues in Economic Crisis, Recovery and Beyond: Women as Agents of Transformation. In: Economic Development and the Triple Crisis—Gender Equality Betwixt and Between: The impact of the Economic, Climate and Food Crises on Women’s Empowerment and Wellbeing. Commonwealth Secretariat, Bridgetown, Barbados, pp. 1-36. Subject to Final Copyedit 51 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 13 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 Willox, A.C., S.L. Harper, J.D. Ford, K. Landman, K. Houle, and V. Edge, 2012: “From this place and of this place:” Climate change, sense of place, and health in Nunatsiavut, Canada. Social Science & Medicine, 75(3), 538-547. Wittman, H.K. and C. Caron, 2009: Carbon offsets and inequality: social costs and co-benefits in Guatemala and Sri Lanka. Society and Natural Resources, 22(8), 710-726. Wolf, J., W.N. Adger, I. Lorenzoni, V. Abrahamson, and R. Raine, 2010: Social capital, individual responses to heat waves and climate change adaptation: An empirical study of two UK cities. Global Environmental Change, 20(1), 44-52. World Bank, 2001: The World Development Report, 2000-01: Attacking Poverty. World Bank., Washington DC, USA, pp. 1-352. World Bank, 2010: World Development Report 2010: Development and Climate Change. World Bank, Washington DC, USA, pp. 1-300. World Bank, 2012a: World Development Report 2012: Gender Equality and Development. World Bank, Washington DC, USA, pp. 1-458. World Bank, 2012b: Turn Down the Heat: Why a 4 Degrees Warmer World Must be Avoided. World Bank, Washington DC, USA, pp. 1-106. Xu, J., R.E. Grumbine, A. Shrestha, M. Eriksson, X. Yang, Y. Wang, and A. Wilkes, 2009: The melting Himalayas: cascading effects of climate change on water, biodiversity, and livelihoods. Conservation Biology, 23(3), 520530. Yamauchi, F., Y. Yohannes, and A. Quisumbing, 2009: Natural disasters, self-insurance and human capital investment: evidence from Bangladesh, Ethiopia and Malawi. In: World Bank Policy Research Working Paper. World Bank, Washington DC, USA, pp. 1-28. Yengoh, G.T., F.A. Armah, E.E. Onumah, and J.O. Odoi, 2010a: Trends in Agriculturally-Relevant Rainfall Characteristics for Small-scale Agriculture in Northern Ghana. Journal of Agricultural Science, 2(3), P3. Yengoh, G.T., A. Tchuinte, F.A. Armah, and J.O. Odoi, 2010b: Impact of prolonged rainy seasons on food crop production in Cameroon. Mitigation and Adaptation Strategies for Global Change, 15(8), 825-841. Yohe, G.W., R.D. Lasco, Q.K. Ahmad, N.W. Arnell, S.J. Cohen, C. Hope, A.C. Janetos, and R.T. Perez, 2007: Perspectives on climate change and sustainability. Climate Change 2007: Impacts, Adaptation and Vulnerability. Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. In: [Parry, M.L., O.F. Canziani, J.P. Palutikof, P.J. van der Linden, and C.E. Hanson(eds.)]. IPCC, Geneva, Switzerland, pp. 811-841. Zambian Government, 2011: Strategic Programme for Climate Resilience. Ministry of Finance, Zambia, Zambia, pp. 1-201. Ziervogel, G., S. Bharwani, and T.E. Downing, 2006: Adapting to climate variability: pumpkins, people and policy. Natural Resources Forum, 30(4), 294-305. Ziervogel, G., M. Shale, and M. Du, 2010: Climate change adaptation in a developing country context: The case of urban water supply in Cape Town. Climate and Development, 2(2), 94-110. Zoomers, A., 2010: Globalisation and the foreignisation of space: seven processes driving the current global land grab. The Journal of Peasant Studies, 37(2), 429-447. Zottarelli, L.K., 2008: Post‐Hurricane Katrina Employment Recovery: The Interaction of Race and Place*. Social Science Quarterly, 89(3), 592-607. Zotti, M.E., V.T. Tong, L. Kieltyka, and R. Brown-Bryant, 2012: Factors Influencing Evacuation Decisions Among High-Risk Pregnant And Postpartum Women. In: The Women of Katrina: How Gender, Race, and Class Matter in an American Disaster. [Emmanuel, D. and E. Enarson(eds.)]. Vanderbilt University Press, Nashville, TN, pp. 90-104. Subject to Final Copyedit 52 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 13 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 Table 13-1: Examples of gendered climate experiences* Experiences Increased workload Male farmers Demanding tasks such as feeding livestock, carting water, destroying frail animals (A) Increased migration for wage labor, typically farther away from home (I) Locked into farms, loss of political power (A) Exploitation by labor contractors when migrating (I) Feel demonized (farmers seen as responsible for crisis), increased stress, social isolation, depression, and high suicide levels (A) Increased anxiety to provide food and access loans and escape trap of indebtedness, increase in domestic fights, sometimes suicide (I) Female farmers Assistance with farm tasks and working off the farm for additional income (A) Increased collection of firewood and uptake of wage labor (esp. lower castes) in neighboring villages (I) Increased interactions and caregiving work, taking care of others’ health at the expense of their own (A) Disadvantage in accessing institutional support and climate information (I) Working lives appear indefinite, resulting in increased stress (A) Increased pressure to provide food and save some more from sale for consumption, less food intake, increase in domestic fights (I) Community interactions, isolation, and exploitation Physical and psychological toll *A = Australia (ten-year drought, 2003-2012), based on Alston, 2011; I = India (climate variability and changing climatic trends), based on Lambrou and Nelson, 2013. Subject to Final Copyedit 53 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 13 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 Table 13-2: Key risks from climate change for poor people and their livelihoods and the potential for risk reduction through adaptation. Key risks are identified based on assessment of the literature and expert judgment by chapter authors, with evaluation of evidence and agreement in the supporting chapter sections. Each key risk is characterized as very low, low, medium, high, or very high. Risk levels are presented in three timeframes: present, near-term (2030-2040), and long-term (2080-2100). Near-term indicates that projected levels of global mean temperature do not diverge substantially across emissions scenarios. Long-term differentiates between a global mean temperature increase of 2°C and 4°C above preindustrial levels. For each timeframe, risk levels are estimated for a continuation of current adaptation and for a hypothetical highly adaptive state. Bars that only show the latter indicate a limit to adaptation (see Chapter 16). Relevant climate variables are indicated by symbols. This table should not be used as a basis for ranking severity of risks. Subject to Final Copyedit 54 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 13 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 Figure 13-1: Multiple stressors related to climate change, globalizations, and technological change interact with national and regional institutions to create shocks to place-based livelihoods, inspired by Reason (2000). Figure 13-2: A) Multidimensional poverty and income-based poverty using the International Poverty Line $1.25/day (in Purchasing Power Parity terms), with linear regression relationship (dotted line) based on 96 countries (UNDP, 2011b). The position of the countries relative to the dotted line illustrates the extent to which these two poverty measures are similar or divergent (e.g., Niger). B) The map insets show the intensity of poverty in two countries, based on the Poverty Gap Index at district level (per capita measure of the shortfall in welfare of the poor from the poverty line, expressed as a ratio of the poverty line). The darker the purple shading, the larger the shortfall. Subject to Final Copyedit 55 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 13 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 Figure 13-3: Illustrative depiction of livelihood dynamics under simultaneous climatic, environmental, and socioeconomic stressors and shocks leading to differential livelihood trajectories over time, based on four case studies. The red boxes indicate specific critical moments when stressors converge, threatening livelihoods and well-being. Key variables and impacts numbered in the illustrations correspond to the developments described in the captions. Subject to Final Copyedit 56 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 13 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 Figure 13-4: Seasonal sensitivity of livelihoods to climatic and non-climatic stressors for one calendar year, based on experiences of smallholder farmers in the Lake Victoria Basin in Kenya and Tanzania (Gabrielsson et al., 2012). Figure 13-5: Multidimensional vulnerability driven by intersections dimensions of inequality. Subject to Final Copyedit 57 28 October 2013