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Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014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
13.2. Assessment of Climate Change Impacts on Livelihoods and Poverty
13.2.1. Evidence of Observed Climate Change Impacts on Livelihoods and Poverty
13.2.1.1. 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
13.3. 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
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Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014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
13.5. Synthesis and Research Gaps
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 rain-
fed 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 market-
based 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 socio-
economic 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 non-
climatic stressors and changing trends disrupt informal social networks of the poorest, elderly, women, and women-
headed 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 house-
holds (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 climate-
related 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; Arora-
Jonsson, 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 infra-
structure (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 2008-
2015 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 multi-
dimensional 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 climate-
sensitive 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 sub-
Saharan 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 crop-
livestock 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 2071-
2100 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 deep-
rooted 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 pro-
poor 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 sub-
national 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 non-
climatic 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 high-
income 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 climate-
related 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 non-
poor 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 small-
scale 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), E2415-
E2423.
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, 292-
297.
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 middle-
income 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. 95-
108.
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), 5-
31.
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. Kabubo-
Mariara(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 Meta-
Analysis 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. Oliver-
Smith, 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 climate-
proofing 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 2000-
2005 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. 149-
171.
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 community-
based 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, 12-
13 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), 551-
566.
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), 903-
905.
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. 1-
54.
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. 1-
6.
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 KwaZulu-
Natal. 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. 1-
20.
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), 269-
277.
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), 489-
505.
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), 409-
418.
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. 119-
140.
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: Late-
twentieth-century warming in Lake Tanganyika unprecedented since AD 500. Nature Geoscience, 3(6), 422-
425.
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. 1-
125.
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), 394-
414.
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), 520-
530.
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 Male farmers Female farmers
Increased Demanding tasks such as feeding livestock, carting Assistance with farm tasks and working off the farm
workload water, destroying frail animals (A) for additional income (A)
Increased migration for wage labor, typically farther Increased collection of firewood and uptake of wage
away from home (I) labor (esp. lower castes) in neighboring villages (I)
Community Locked into farms, loss of political power (A) Increased interactions and caregiving work, taking
interactions, care of others’ health at the expense of their own (A)
isolation, and Exploitation by labor contractors when migrating (I) Disadvantage in accessing institutional support and
exploitation climate information (I)
Physical and Feel demonized (farmers seen as responsible for Working lives appear indefinite, resulting in increased
psychological crisis), increased stress, social isolation, depression, stress (A)
toll and high suicide levels (A)
Increased anxiety to provide food and access loans Increased pressure to provide food and save some
and escape trap of indebtedness, increase in domestic more from sale for consumption, less food intake,
fights, sometimes suicide (I) increase in domestic fights (I)
*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 socio-
economic 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