793
13
Livelihoods and Poverty
Coordinating Lead Authors:
Lennart Olsson (Sweden), Maggie Opondo (Kenya), Petra Tschakert (USA)
Lead Authors:
Arun Agrawal (USA), Siri H. Eriksen (Norway), Shiming Ma (China), Leisa N. Perch (Barbados),
Sumaya A. 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)
This chapter should be cited as:
Olsson
, L., M. Opondo, P. Tschakert, A. Agrawal, S.H. Eriksen, S. Ma, L.N. Perch, and S.A. Zakieldeen, 2014:
Livelihoods and poverty. In: Climate Change 2014: Impacts, Adaptation, and Vulnerability. Part A: Global and
Sectoral Aspects. Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental
Panel on Climate Change [Field, C.B., V.R. Barros, D.J. Dokken, K.J. Mach, M.D. Mastrandrea, T.E. Bilir,
M. Chatterjee, K.L. Ebi, Y.O. Estrada, R.C. Genova, B. Girma, E.S. Kissel, A.N. Levy, S. MacCracken,
P.R. Mastrandrea, and L.L. White (eds.)]. Cambridge University Press, Cambridge, United Kingdom and
New York, NY, USA, pp. 793-832.
13
794
Executive Summary ........................................................................................................................................................... 796
13.1. Scope, Delineations, and Definitions: Livelihoods, Poverty, and Inequality ........................................................... 798
13.1.1. Livelihoods ....................................................................................................................................................................................... 798
13.1.1.1. Dynamic Livelihoods and Trajectories ................................................................................................................................ 798
13.1.1.2. Multiple Stressors .............................................................................................................................................................. 798
13.1.2. Dimensions of Poverty ...................................................................................................................................................................... 799
13.1.2.1. Framing and Measuring Multidimensional Poverty ........................................................................................................... 800
13.1.2.2. Geographic Distribution and Trends of the World’s Poor ................................................................................................... 801
13.1.2.3. Spatial and Temporal Scales of Poverty ............................................................................................................................. 801
13.1.3. Inequality and Marginalization ......................................................................................................................................................... 802
13.1.4. Interactions between Livelihoods, Poverty, Inequality, and Climate Change ..................................................................................... 802
13.2. Assessment of Climate Change Impacts on Livelihoods and Poverty .................................................................... 803
13.2.1. Evidence of Observed Climate Change Impacts on Livelihoods and Poverty .................................................................................... 803
13.2.1.1. Impacts on Livelihood Assets and Human Capabilities ...................................................................................................... 803
13.2.1.2. Impacts on Livelihood Dynamics and Trajectories .............................................................................................................. 805
13.2.1.3. Impacts on Poverty Dynamics: Transient and Chronic Poverty ........................................................................................... 805
13.2.1.4. Poverty Traps and Critical Thresholds ................................................................................................................................. 806
13.2.1.5. Multidimensional Inequality and Vulnerability .................................................................................................................. 807
Box 13-1. Climate and Gender Inequality: Complex and Intersecting Power Relations .................................................. 808
13.2.2. Understanding Future Impacts of and Risks from Climate Change on Livelihoods and Poverty ........................................................ 810
13.2.2.1. Projected Risks and Impacts by Geographic Region .......................................................................................................... 810
13.2.2.2. Anticipated Impacts on Economic Growth and Agricultural Productivity ........................................................................... 810
13.2.2.3. Implications for Livelihood Assets, Trajectories, and Poverty Dynamics .............................................................................. 812
13.2.2.4. Impacts on Transient and Chronic Poverty, Poverty Traps, and Thresholds ......................................................................... 812
13.3. Assessment of Impacts of Climate Change Responses on Livelihoods and Poverty .............................................. 813
13.3.1. Impacts of Mitigation Responses ...................................................................................................................................................... 813
13.3.1.1. The Clean Development Mechanism ................................................................................................................................. 813
13.3.1.2. Reduction of Emissions from Deforestation and Forest Degradation ................................................................................. 814
13.3.1.3. Voluntary Carbon Offsets .................................................................................................................................................. 814
13.3.1.4. Biofuel Production and Large-Scale Land Acquisitions ...................................................................................................... 814
13.3.2. Impacts of Adaptation Responses on Poverty and Livelihoods ......................................................................................................... 815
13.3.2.1. Impacts of Adaptation Responses on Livelihoods and Poverty .......................................................................................... 815
13.3.2.2. Insurance Mechanisms for Adaptation .............................................................................................................................. 816
Table of Contents
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13
13.4. Implications of Climate Change for Poverty Alleviation Efforts ............................................................................. 816
13.4.1. Lessons from Climate-Development Efforts ...................................................................................................................................... 816
Box 13-2. Lessons from Social Protection, Disaster Risk Reduction, and Energy Access ............................................................ 817
13.4.2. Toward Climate-Resilient Development Pathways ............................................................................................................................ 818
13.5. Synthesis and Research Gaps ................................................................................................................................. 818
References ......................................................................................................................................................................... 819
Frequently Asked Questions
13.1: What are multiple stressors and how do they intersect with inequalities to influence livelihood trajectories? ................................ 799
13.2: How important are climate change-driven impacts on poverty compared to other drivers of poverty? ............................................ 802
13.3: Are there unintended negative consequences of climate change policies for people who are poor? ............................................... 813
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Chapter 13 Livelihoods and Poverty
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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.
Climate-related hazards exacerbate other stressors, often with negative outcomes for livelihoods, especially for people living in
poverty (high confidence).
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). {13.2.1.3-4}
Many events that affect poor people are weather-related and remain unrecognized by standard climate observations in many low-income
countries, owing 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}
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; Figure 13-3}
Climate change will create new poor between now and 2100, in developing and developed countries, 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 2°C 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}
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Livelihoods and Poverty Chapter 13
Climate change will exacerbate multidimensional poverty in most developing countries, 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 countries with increasing
inequality, in both developed and developing countries. {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 {13.2.2.3-4}
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 Clean Development Mechanism (CDM) and Reduction of
Emissions from Deforestation and Forest Degradation (REDD+), have had limited or no effect in terms of poverty alleviation and
sustainable development. {13.3.1.1-2}
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 developing countries, 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}
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Chapter 13 Livelihoods and Poverty
13
13.1. Scope, Delineations, and Definitions:
Livelihoods, Poverty, and Inequality
Understanding the impacts of climate change on livelihoods and
p
overty 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 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 WGII
AR4 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 (Chapters
7, 8, 18, 20), no systematic assessment was undertaken. Livelihoods were
more frequently addressed in the AR4 and in the Special Report on
Managing the Risks of Extreme Events and Disasters to Advance Climate
Change Adaptation (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 on 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,
t
o improve living conditions, a prerequisite for poverty alleviation (Sen,
1981).
Livelihoods are universal. Poor and rich people both pursue livelihoods
to make a living. However, as shown in this chapter, the adverse impacts
of weather events and climate increasingly threaten and erode basic needs,
capabilities, and rights, particularly among poor and disenfranchised
people, in turn reshaping their livelihoods (UNDP, 2007; Leary et al.,
2008; Adger, 2010; Quinn et al., 2011). Some livelihoods are directly
climate sensitive, such as rainfed smallholder agriculture, seasonal
employment in agriculture (e.g., tea, coffee, sugar), fishing, pastoralism,
and tourism. Climate change also affects households dependent on
informal livelihoods or wage labor in poor urban settlements, directly
through unsafe settlement structures or indirectly through rises in food
prices or migration.
13.1.1.1. Dynamic Livelihoods and Trajectories
A livelihood lens is a grounded and multidimensional perspective that
recognizes the flexibility and constraints with which people construct
their complex lives and adapt their livelihoods in dynamic ways. By
paying attention to the wider institutional, cultural, and policy contexts
as well as shocks, seasonality, and trends, this lens reveals processes
that push people onto undesirable trajectories or toward enhanced well-
being. Better infrastructure and technology as well as diversification of
assets, activities, and social support capabilities can boost livelihoods,
spreading risks and broadening opportunities (Batterbury, 2001; Ellis
et al., 2003; Clot and Carter, 2009; Carr, 2013; Reed et al., 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 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; Easterling et al., 2007; IPCC, 2007; Morton,
2007; Tschakert, 2007; O’Brien et al., 2008; Eriksen and Silva, 2009;
Eakin and Wehbe, 2009; Ziervogel et al., 2010). “Double losers” may
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Livelihoods and Poverty Chapter 13
13
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 also
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).
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
Frequently Asked Questions
FAQ 13.1 | What are multiple stressors and how do they intersect with inequalities
to influence livelihood trajectories?
Multiple stressors are simultaneous or subsequent
conditions or events that provoke/require changes
in livelihoods. Stressors include climatic (e.g., shifts
in seasons), socioeconomic (e.g., market volatility),
and environmental (e.g., destruction of forest) factors,
that interact and reinforce each other across space
and time to affect livelihood opportunities and
decision making (see Figure 13-1). Stressors that
originate at the macro level include climate change,
globalization, and technological change. At the
regional, national, and local levels, institutional
context and policies shape possibilities and pitfalls
for lessening the effects of these stressors. Which
specific stressors ultimately result in shocks for
particular livelihoods and households is often
mediated by institutions that connect the local level
to higher levels. Moreover, inequalities in low-,
medium-, and high-income countries often amplify
the effects of these stressors. This is particularly the
case for livelihoods and households that have
limited asset flexibility and/or those that experience
disadvantages and marginalization due to gender,
age, class, race, (dis)ability, or being part of a particular
indigenous or ethnic group. Weather events and
climate compound these stressors, allowing some to benefit and enhance their well-being while others experience
severe shocks and may slide into chronic poverty. Who is affected, how, where, and for how long depends on local
contexts. For example, in the Humla district in Nepal, gender roles and caste relations influence livelihood trajectories
in the face of multiple stressors including shifts in the monsoon season (climatic), limited road linkages (socioeconomic),
and high elevation (environmental). Women from low castes have adapted their livelihoods by seeking more day-
labor employment, whereas men from low castes ventured into trading on the Nepal-China border, previously an
exclusively upper caste livelihood.
Livelihoods
Institutions such as:
Social protection
• Relief organizations
• Disaster prevention
Displacement
Destroyed
homes
Food
crisis
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).
Climate change
Globalizations
Technological change
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Chapter 13 Livelihoods and Poverty
13
i
n 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 6 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; lack
of access to health, credit, or legal services; social exclusion; and
disempowerment—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
a
ttention 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, 1999; Nussbaum,
2001, 2011; Alkire, 2005), 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 toward the MDGs. Empirical assessments of the impact of
0.00 – 0.06
0.06 – 0.11
0.11 – 0.18
0.18 – 0.30
0.30 – 0.47
no data
0.01 – 0.20
0.20 – 0.26
0.26 – 0.31
0.31 – 0.35
0.35 – 0.68
no data
10080604020
0
100
80
60
40
20
Philippines
Nicaragua
Gabon
Colombia
Thailand
Vietnam
Vietnam
Cameroon
Kenya
India
Gambia
Senegal
Uganda
Benin
Guinea
Niger
Central African
Republic
Rwanda
Malawi
Malawi
Madagascar
Poverty Gap Index
Poverty Gap Index
Uzbekistan
Laos
Haiti
Population below the international poverty line $1.25 per day (%)
Population in multidimensional poverty (%)
(a) (b)
Figure 13-2 | (a) Multidimensional poverty and income-based poverty using the International Poverty Line $1.25 per 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.
(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 shading, the larger the shortfall.
801
Livelihoods and Poverty Chapter 13
13
c
limate 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 et al., 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 per 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).
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 the remainder
of the text, we use the World Bank income-based poverty categories
for countries (low-income countries, lower-middle-income countries,
upper-middle-income countries, and high-income countries); these
categories are more precise and more accurate for describing climate
change impacts on poverty than the terminology adopted in the
Summary for Policymakers and the respective chapter Executive
Summaries (i.e., ‘developingand ‘developed’ countries). Moreover,
much of the assessed literature is based on these categories. In 1990,
most of the world’s $1.25 and $2 poor lived in low-income countries
(LICs). By 2008, the majority of the poor living on $1.25 and $2 (>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, 2012a). Estimates
suggest about 1 billion people currently living on less than $1.25 per
day in MICs and a second billion between $1.25 and $2, with an
additional 320 million and 170 million in LICs, respectively (Sumner,
2012b). About 70% of the poor subsisting on $1.25 per day 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 on less than $2 per 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
w
orld’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 directed largely toward LICs.
Less attention has been paid to poor people in MICs and HICs. In the
upper and lower MICs, the incidence of $2 per day poverty, despite
declines, remains as high as 60% and 20%, respectively (Sumner, 2012b).
Projections for 2030 suggest $2 per day 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
per day global poverty could be reduced to 300 million and 600 million
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,
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 less than $1.25
per 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, 12).
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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 affected (IPCC, 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; IPCC, 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 owing
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 UK, 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 Section 13.4; 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 (IPCC, 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 Sections 13.2 and 13.3, climate change is an
additional burden to people in poverty (very high confidence), and it
Frequently Asked Questions
FAQ 13.2 | How important are climate change-driven impacts on poverty
compared to other drivers of poverty?
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.
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ill 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 (IPCC, 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.
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 to 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 (Section 13.2.1) and then projected risks and
impacts (Section 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 (IPCC, 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;
Lacombe et al., 2012; Salack 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 to 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,b; D’Agostino and Sovacool, 2011; see also
Chapters 3, 4, 5, 6, 30). During the 20th century, water temperatures
increased and winds decreased in Lake Tanganyika (Adrian et al., 2009;
Verburg and Hecky, 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 to 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).
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, 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
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Chapter 13 Livelihoods and Poverty
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Convergence of multiple
stressors and shocks
Convergence of multiple
stressors and shocks
Convergence of multiple
stressors and shocks
Non-supportive
policy environment
Institutional &
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Current policy
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Potential policy
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Current policy
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Potential policy
responses
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Intensity of stressors
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Livelihood condition
Vulnerable Resilient
Intensity of stressors
Catastrophic
Negligible
Livelihood condition
Vulnerable Resilient
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Intensity of stressors
Catastrophic
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Livelihood condition
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1
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2
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5
6
7
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4
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6
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Convergence of multiple
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4
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Time Time
Time Time
Critical
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Climatic factors
Socioeconomic factors
Environmental factors
Some few households
Several households
Most households
Intensity of stressors
Catastrophic
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Livelihood condition
Vulnerable Resilient
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ecent past Near future Recent past Near future
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3
(a) Botswana’s drylands (Sallu et al., 2010). Over the past 30 years, rural households have
faced droughts, late onset and increased unpredictability of rainfall, and frost 1 , drying of Lake Xau,
and land degradation 2 . Households responded differently to these stressors, given their financial
and physical assets, diversification of and within livelihood activities, family relations, and
institutional and governmental support. Despite weakening of social networks and declining
livestock due to lack of water 3 , distinct livelihood trajectories emerged. Accumulators” were
often able to benefit from crises, for instance through access to salaried employment 4 or new
hunting quotas 5 , while “dependent” households showed a degenerative trajectory, losing more
and more livelihood assets, and becoming reliant on governmental support after another period of
convergent stressors 6 . “Diversifiers” had trajectories fluctuating between vulnerable and resilient
states 7 .
(b) Coastal Bangladesh (Pouliotte et al., 2010). In the Sunderbans, a combination of
environmental and socioeconomic factors, out of which climatic stressors appear to play only a
minor role, have changed livelihoods: saltwater intrusion 1 due to the construction and poor
management of the Bangladeshi Coastal Embankment Project, the construction of a dam in India,
local water diversions 2 , and sea level rise and storm surges 3 . The convergence of these stressors
caused households to cross a critical threshold from rice and vegetable cultivation to saltwater
shrimp farming 4 . A strong export market and international donor and national government
support facilitated this shift 5 . However, increasing density of shrimp farming then triggered rising
disease levels 6 . Wealth and power started to become more concentrated among a few affluent
families 7 while livelihood options for the poorer households further diminished due to lacking
resources to grow crops in salinated water, the loss of grazing areas and dung from formerly
accessible rice fields 8 , and rising disease levels 6 .
(c) Mountain environments (McDowell and Hess, 2012). Indigenous Aymara farmers in
highland Bolivia face land scarcity, pervasive poverty, climate change, and lack of infrastructure due
in part to racism and institutional marginalization. The retreat of the Mururata glacier causes water
shortages 1 , compounded by the increased water requirements of cash crops on smaller and
smaller “minifundios” and market uncertainties 2 . High temperatures amplify evaporation, and
flash floods coupled with delayed rainfall cause irrigation canals to collapse 3 . The current policy
environment makes it difficult to access loans and obtain land titles 4 , pushing many farmers onto
downward livelihood trajectories 5 while those who can afford it invest in fruit and vegetable trees
at higher altitudes 6 . Sustained access to land, technical assistance, and irrigation infrastructure
would be effective policy responses to enhance well-being 7 .
(d) Urban flooding in Lagos (Adelekan, 2010). Flooding threatens the livelihoods of people
in Lagos, Nigeria, where >70 % live in slums. Increased severity in rainstorms, sea level rise, and
storm surges 1 coupled with the destruction of mangroves and wetlands 2 , disturb people’s jobs
as traders, wharf workers, and artisans, while destroying physical and human assets. Urban
management, infrastructure for water supply, and stormwater drainage have not kept up with
urban growth 3 . Inadequate policy responses, including uncontrolled land reclamation, make these
communities highly vulnerable to flooding 4 . Only some residents can afford sand and broken
sandcrete blocks 5 . Livelihood conditions in these slums are expected to further erode for most
households 6 . Given policy priorities for the construction of high-income residential areas, current
residents fear eviction 7 .
Figure 13-3 | Illustrative representation of four case studies that describe livelihood dynamics under simultaneous climatic, environmental, and socioeconomic stressors, shocks,
and policy responses – leading to differential livelihood trajectories over time. 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.
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Livelihoods and Poverty Chapter 13
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loodplains 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 Himalay</