613
9
Rural Areas
Coordinating Lead Authors:
Purnamita Dasgupta (India), John F. Morton (UK)
Lead Authors:
David Dodman (Jamaica), Barış Karapinar (Turkey/Switzerland), Francisco Meza (Chile),
Marta G. Rivera-Ferre (Spain), Aissa Toure Sarr (Senegal), Katharine E. Vincent (South Africa)
Contributing Authors:
Ashish Aggarwal (India), Netra Chhetri (USA/Nepal), Tracy Cull (South Africa),
Jose Gustavo Feres (Brazil), Jeremy Haggar (UK), George Hutchinson (UK), Feliu López-i-Gelats
(Spain), Megan Mills-Novoa (USA), Nandan Nawn (India), Catherine Norman (USA),
Andreas Scheba (Austria), Tetsuji Tanaka (Japan)
Review Editors:
Edward R. Carr (USA), Nirivololona Raholijao (Madagascar)
Volunteer Chapter Scientist:
Hauke Broecker (Germany)
This chapter should be cited as:
Dasgupta
, P., J.F. Morton, D. Dodman, B. Karapinar, F. Meza, M.G. Rivera-Ferre, A. Toure Sarr, and K.E. Vincent,
2014: Rural areas. 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. 613-657.
9
614
Executive Summary............................................................................................................................................................ 616
9.1. Introduction ............................................................................................................................................................ 618
9.1.1. Rationale for the Chapter ................................................................................................................................................................. 618
9.1.2. Definitions of the Rural ..................................................................................................................................................................... 618
9.2. Findings of Recent Assessments ............................................................................................................................. 619
9.3. Assessing Impacts, Vulnerabilities, and Risks ......................................................................................................... 619
9.3.1. Current and Future Economic, Social, and Land Use Trends in Rural Areas ....................................................................................... 619
9.3.2. Observed Impacts ............................................................................................................................................................................. 619
9.3.3. Future Impacts .................................................................................................................................................................................. 623
9.3.3.1.Economic Base and Livelihoods ........................................................................................................................................... 623
Box 9-1. Impacts of Climate Change on Tropical Beverage Crops ................................................................................... 626
9.3.3.2.Infrastructure ....................................................................................................................................................................... 628
9.3.3.3.Spatial and Regional Interconnections ................................................................................................................................. 628
9.3.3.4.Second-Order Impacts of Climate Policy ............................................................................................................................... 629
9.3.4. Valuation of Climate Impacts ........................................................................................................................................................... 630
9.3.4.1.Agriculture ........................................................................................................................................................................... 631
9.3.4.2.Other Rural Sectors: Water, Fisheries, Livestock, Mining ....................................................................................................... 632
9.3.4.3.Extreme Weather Events, Sea Level Rise .............................................................................................................................. 633
9.3.4.4.Recreation and Tourism; Forestry .......................................................................................................................................... 633
9.3.5. Key Vulnerabilities and Risks ............................................................................................................................................................ 633
9.3.5.1.Drivers of Vulnerability and Risk ........................................................................................................................................... 633
9.3.5.2.Outcomes ............................................................................................................................................................................. 635
Box 9-2. Tourism and Rural Areas .................................................................................................................................... 636
9.4. Adaptation and Managing Risks ............................................................................................................................. 637
9.4.1. Framing Adaptation .......................................................................................................................................................................... 637
9.4.2. Decision Making for Adaptation ....................................................................................................................................................... 638
9.4.3. Practical Experiences of Adaptation in Rural Areas ........................................................................................................................... 638
9.4.3.1.Agriculture ........................................................................................................................................................................... 638
9.4.3.2.Water ................................................................................................................................................................................... 638
9.4.3.3.Forestry and Biodiversity ...................................................................................................................................................... 640
Box 9-3. Adaptation Initiatives in the Beverage Crop Sector .......................................................................................... 641
9.4.3.4.Fisheries ............................................................................................................................................................................... 642
9.4.4. Limits and Constraints to Rural Adaptation ...................................................................................................................................... 642
Box 9-4. Factors Influencing Uptake and Utility of Climate Forecasts in Rural Africa ................................................................ 643
Table of Contents
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Rural Areas Chapter 9
9
9.5. Key Conclusions and Research Gaps ....................................................................................................................... 643
9.5.1. Key Conclusions ................................................................................................................................................................................ 643
9.5.2. Research Gaps .................................................................................................................................................................................. 645
References ......................................................................................................................................................................... 645
Frequently Asked Questions
9.1: What is distinctive about rural areas in the context of climate change impacts, vulnerability, and adaptation? .............................. 618
9.2: What will be the major climate change impacts in rural areas across the world? ............................................................................ 630
9.3: What will be the major ways in which rural people adapt to climate change? ................................................................................. 642
616
Chapter 9 Rural Areas
9
Executive Summary
Rural areas still account for almost half the world’s population, and about 70% of the developing world’s poor people. {9.1.1}
There is a lack of clear definition of what constitutes rural areas, and definitions that do exist depend on definitions of the urban. {9.1.2} Across
the world, the importance of peri-urban areas and new forms of rural-urban interactions are increasing (limited evidence, high agreement).
{9.1.3} Rural areas, viewed as a dynamic, spatial category, remain important for assessing the impacts of climate change and the prospects for
adaptation. {9.1.1}
Climate change in rural areas will take place in the context of many important economic, social, and land-use trends (very high
confidence). In different regions, absolute rural populations have peaked or will peak in the next few decades. {9.3.1} The proportion of the
rural population depending on agriculture is extremely varied across regions, but declining everywhere. Poverty rates in rural areas are higher
than overall poverty rates, but also falling more sharply, and the proportions of population in extreme poverty accounted for by rural people
are also falling: in both cases with the exception of sub-Saharan Africa, where these rates are rising. {Figure 9-2} Accelerating globalization,
through migration, labor linkages, regional and international trade, and new information and communication technologies, is bringing about
economic transformation in rural areas of both developing and developed countries. {9.3.1}
Rural people in developing countries are subject to multiple non-climate stressors, including under-investment in agriculture
(though there are signs this is improving), problems with land and natural resource policy, and processes of environmental
degradation (very high confidence).
In developing countries, the levels and distribution of rural poverty are affected in complex and
interacting ways by processes of commercialization and diversification, food policies, and policies on land tenure. In developed countries, there
are important shifts toward multiple uses of rural areas, especially leisure uses, and new rural policies based on the collaboration of multiple
stakeholders, the targeting of multiple sectors, and a change from subsidy-based to investment-based policy. {9.3.1, Table 9-3}
Impacts of climate change on the rural economic base and livelihoods, land use, and regional interconnections are at the latter
stages of complex causal chains (high confidence). These flow through changing patterns of extreme events and/or effects of climate
change on biophysical processes in agriculture and less-managed ecosystems. {9.3.3} This increases both the uncertainty associated with
detection and attribution of current impacts {9.3.2}, and with projections of specific future impacts. {9.3.3}
Structural features of farm households and communities affect their vulnerability to climate change in complex ways (high
confidence).
There is low agreement on some of the key factors associated with vulnerability or resilience in rural areas {9.3.5.1}, including
rainfed as opposed to irrigated agriculture {9.3.5.1.1}, small-scale and family-managed farms, and integration into world markets. {9.3.5.1.2}
There is high agreement on the importance for resilience of access to land and natural resources, flexible local institutions {9.3.5.1.3}, and
knowledge and information {9.3.5.1.6}, and on the association of gender inequalities with vulnerability. {9.3.5.1.5} Specific livelihood niches
such as pastoralism, mountain farming systems, and artisanal fisheries are vulnerable and at high risk of adverse impacts (high confidence),
partly owing to neglect, misunderstanding, or inappropriate policy toward them on the part of governments. {9.3.5.2}
Cases in the literature of observed impacts on rural areas often suffer from methodological problems of attribution, but evidence
for observed impacts, both of extreme events and other categories, is increasing (medium confidence).
Impacts attributable to climate
change include some direct impacts of droughts, storms, and other extreme events on infrastructure and health (low confidence globally, but
medium confidence in certain regions), as well as longer-term declining yields of major crops, from which impacts on income and livelihoods
can be inferred with low confidence. There is high confidence in geographically specific impacts, such as glacier melt in the Andes. {9.3.2}
Major impacts of climate change in rural areas will be felt through impacts on water supply, food security {9.3.3.1}, and
agricultural incomes {9.3.4.1} (high confidence).
Shifts in agricultural production, of food and non-food crops, are projected for many
areas of the world (high confidence). {9.3.3.1} Price rises, which may be induced by climate shocks as well as other factors {9.3.3.3.2}, have a
disproportionate impact on the welfare of the poor in rural areas, such as female headed households and those with limited access to modern
agricultural inputs, infrastructure, and education. {9.3.3.1} The time scale for impacts varies across regions and sectors, and by the nature of the
specific climatic impact.
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Rural Areas Chapter 9
9
Climate change will impact international trade volumes in both physical and value terms (limited evidence, medium agreement).
Importing food can help countries adjust to climate change-induced domestic productivity shocks while short-term food deficits in low-income
countries may have to be met through food aid. Options exist for adaptations within international agricultural trade (medium confidence).
Deepening agricultural markets and improving the predictability and the reliability of the world trading system through trade reform, as well as
investing in additional supply capacity of small-scale farms in developing countries, could result in reduced market volatility and manage food
supply shortages caused by climate change. {9.3.3.3.2}
Migration patterns will be driven by multiple factors of which climate change is only one (high confidence). {9.3.3.3.1} Given
these multiple drivers of migration (economic, social, political, demographic, and environmental) and the complex interactions that mediate
migratory decision making by individuals or households, establishment of a relation between climate change and intra-rural and rural-to-urban
migration, observed or projected, remains a major challenge.
Climate policies, such as increasing energy supply from renewable resources, encouraging cultivation of biofuels, or payments
under Reducing Emissions from Deforestation and Forest Degradation (REDD), will have significant secondary impacts, both
positive (increasing employment opportunities) and negative (landscape changes, increasing conflicts for scarce resources), in
some rural areas (medium confidence). {9.3.3.4}
There is a need to understand how implementation of these policies will impact on rural
livelihoods. These secondary impacts, and trade-offs between mitigation and adaptation in rural areas, have implications for governance,
including the need to promote participation of rural stakeholders.
Most studies using valuation methodologies conclude that climate change impacts will be substantial, especially for developing
countries, owing to their economic dependence on agriculture and natural resources, low adaptive capacities, and geographical
locations (very high confidence). {9.3.4}
Valuation of climate impacts needs to draw on both monetary and non-monetary indicators. The
valuation of non-marketed ecosystem services {9.3.4.5} and the limitations of economic valuation models that aggregate across multiple
contexts {9.3.4} pose challenges for valuing impacts in rural areas (high confidence).
There is a growing body of literature on adaptation practices in both developed and developing country rural areas {9.4.1},
including documentation of practical experience in agriculture, water, forestry and biodiversity, and, to a lesser extent, fisheries
{9.4.3} (very high confidence).
Public policies supporting decision making for adaptation exist in developed and, increasingly, in developing
countries, and there are also examples of private adaptations led by individuals, companies, and non-governmental organizations (high
confidence). {9.4.2} Constraints on adaptation come from lack of access to credit, land, water, technology, markets, knowledge and information,
and perceptions of the need to change; and are particularly pronounced in developing countries (high confidence). {9.4.4} Gender and
institutions affect access to adaptation options and the presence of barriers to adaptation (very high confidence). {9.4.4}
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Chapter 9 Rural Areas
9
9.1. Introduction
9
.1.1. Rationale for the Chapter
T
his chapter assesses the impacts of climate change on, and the prospects
for adaptation in, rural areas. Rural areas include diverse patterns of
settlement, infrastructure, and livelihoods, and relate in complex ways
with urban areas. The chapter shows that rural areas experience specific
vulnerabilities to climate change, both through their dependence on
natural resources and weather-dependent activities and their relative
lack of access to information, decision making, investment, and services.
Adaptation strategies will need to address these vulnerabilities. Some of
the key starting points, which affect the scope and coverage of literature
assessed in this chapter, are as follows:
Rural areas, even after significant demographic shifts, still account
for 3.3 billion people, or almost half (47.9%) of the world’s total
population (UN DESA Population Division, 2013).
The overwhelming majority of the world’s rural population (3.1 billion
people, or 91.7% of the world’s rural population, or 44.0% of the
world’s total population) live in less developed or least developed
countries (UN DESA Population Division, 2013).
Rural dwellers also account for about 70% of the developing
worlds poor people. IFAD (2010) states that around 70% of the
extreme poor in developing countries lived in rural areas in 2005.
Ravallion et al. (2007), using 2002 data and poverty lines of US$1.08
or US$2.15, in each case with urban poverty lines adjusted upward
to recognize additional non-food spending, give a figure of around
75% of people, under either poverty line, being rural.
Rural areas are a spatial category, associated with certain patterns
of human activity, but with those associations being subject to
continuous change.
Rural areas are largely defined in contradistinction to urban areas,
but that distinction is increasingly seen as problematic.
Rural populations have, and will have, a variety of income sources
and occupations, within which agriculture and the exploitation of
natural resources have privileged, but not necessarily predominant,
positions.
The chapter will complement the treatment of issues also dealt with in
Chapters 4 and 7, but will primarily look at how biophysical impacts of
climate change on agriculture and on less-managed ecosystems translate
into impacts on human systems, and in this regard will complement
sections of Chapters 12 and 13 and other sectoral and regional chapters.
The important impacts of climate change on human health are covered
in Chapter 11. In accordance with the proportion of the rural population
found in developing countries, literature on these countries is given
prominence, but issues of impact, vulnerability, and adaptation in
developed countries are also assessed.
9.1.2. Definitions of the Rural
“Rural refers generally to areas of open country and small settlements,
but the definition of “rural areas” in both policy-oriented and scholarly
literature are terms often taken for granted or left undefined, in a
process of definition that is often fraught with difficulties (IFAD, 2010).
Frequently Asked Questions
FAQ 9.1 | What is distinctive about rural areas in the context of climate change
impacts, vulnerability, and adaptation?
Nearly half of the world’s population, approximately 3.3 billion people, lives in rural areas, and 90% of those people
live in developing countries. Rural areas in developing countries are characterized by a dependence on agriculture
and natural resources; high prevalence of poverty, isolation, and marginality; neglect by policymakers; and lower
human development. These features are also present to a lesser degree in rural areas of developed countries, where
there are also closer interdependencies between rural and urban areas (such as commuting), and where there are
also newer forms of land use such as tourism and recreational activities (although these also generally depend on
natural resources).
The distinctive characteristics of rural areas make them uniquely vulnerable to the impacts of climate change because:
Greater dependence on agriculture and natural resources makes them highly sensitive to climate variability,
extreme climate events, and climate change.
Existing vulnerabilities caused by poverty, lower levels of education, isolation, and neglect by policymakers can
all aggravate climate change impacts in many ways.
Conversely, rural people in many parts of the world have, over long time scales, adapted to climate variability, or
at least learned to cope with it. They have done so through farming practices and use of wild natural resources
(often referred to as indigenous knowledge or by similar terms), as well as through diversification of livelihoods and
through informal institutions for risk-sharing and risk management. Similar adaptations and coping strategies can,
given supportive policies and institutions, form the basis for adaptation to climate change, although the effectiveness
of such approaches will depend on the severity and speed of climate change impacts.
619
Rural Areas Chapter 9
9
Ultimately, in developing countries as well as developed countries, the
rural is defined as the inverse or the residual of the urban (Lerner and
Eakin, 2010). Human settlements in fact exist along a continuum from
“rural” to “urban,” with “large villages,” “small towns, and “small
urban centers” not clearly fitting into one or the other. The variations in
definitions from country to country can best be described through
several examples (from both developed and developing countries of
different sizes) shown in Table 9-1.
Researchers have increasingly recognized that the simple dichotomy
between “rural” and “urban” is extremely problematic (Simon et al.,
2006, p. 4). Additional categories such as “peri-urban areas” (Webster
2002; Bowyer-Bower, 2006; Simon et al., 2006; Simon, 2008; Lerner and
Eakin, 2010) and “desakota (McGee, 1991; Desakota Study Team, 2008;
Moench and Gyawali, 2008) allow more nuanced analysis of the permeable
boundaries of rural and urban areas and the diversified economic systems
that exist across the urban-rural spectrum; see Box CC-UR.
While remaining aware of issues of definition, this chapter in general
assesses the literature on rural areas using whatever definitions of the
rural are used in that literature. Global statistics collated by international
organizations and cited here are generally aggregations of national
statistics compiled under each national definition.
9.2. Findings of Recent Assessments
The Fourth Assessment Report (AR4) of the IPCC contains no specific
chapter on “rural areas.Material on rural areas and rural people is
found throughout the AR4, but rural areas are approached from specific
viewpoints and through specific disciplines. Table 9-2 summarizes key
findings on rural areas from AR4 (particularly Easterling et al. (2007) on
agriculture; Wilbanks et al. (2007) on industry, settlement, and society;
and Klein et al. (2007) on links between adaptation and mitigation),
and relevant findings from the International Assessment of Agricultural
Knowledge, Science and Technology for Development (McIntyre et al.,
2009). All of these sources stress uncertainty, the importance of
non-climate trends, complexity, and context-specificity in any findings
on rural areas and climate change.
9.3. Assessing Impacts,
Vulnerabilities, and Risks
9.3.1. Current and Future Economic, Social,
and Land Use Trends in Rural Areas
Climate change in rural areas will take place against the background
of the trends in demography, economics, and governance that are
shaping those areas. While there are major points of contact between
the important trends in developing and developed countries, and the
analytical approaches used to discuss them, it is easier to discuss trends
separately for the two groups of countries. In particular there is a close
association in developing countries between rural areas and poverty.
Table 9-3 summarizes and compares the most important trends across
the two groups of countries. Figures 9-1 and 9-2 and Table 9-4 focus on
two specific trends in developing countries: demographic trends and
trends in poverty indicators.
9.3.2. Observed Impacts
Documentation of observed impacts of climate change on rural areas
involves major questions of detection and attribution (see Chapter 18).
Whilst having potential, there are complications with using traditional
knowledge and farmer perceptions to detect climate trends (Rao et al.,
2011; see also Box 18-4). Implied equivalence between local perceptions
of climate change, local decadal trends, extreme events, and global
change is common, and often used without systematic discussion of
the challenges (Paavola, 2008; Ensor and Berger, 2009; Castro et al.,
2012). This is not a problem in the context of detailed social-scientific
analysis of vulnerability, adaptive capacity, and their determinants, but
becomes more problematic to use as evidence for observed impact.
Detection and attribution of extreme events to climate change is no
Country Term Defi nition Reference
Australia
M
ajor urban area Population of more than 100,000 Australian Bureau of Statistics (2013)
Other urban area Population of 1000–99,999
R
ural area Includes small towns with a population of 200–999
China
Major urban area Population of more than 10,000 Ministry of Construction (1993)
M
edium urban area Population of 3000–9999
Small urban area Population of fewer than 3000
M
ajor village Population of 1000–3000
Medium village Population of 300–1000
Small village Population of fewer than 300
India
U
rban area Population of 5000 or more; or where at least 75% of the male working population is non-agricultural; or
having a density of population of at least 400 people km
–2
. It is implied that all non-urban areas are rural.
G
overnment of India (2012)
Jamaica
U
rban place Population of more than 2000 people; and provision of a certain set of amenities and facilities that are
deemed to indicate “modern living”. It is implied that all non-urban areas are rural.
S
tatistical Institute of Jamaica (2012:iv)
United States
of America
R
ural area All territory outside of defi ned urbanized areas and urban clusters, that is, open country and settlements
with fewer than 2500 residents; with population densities as high as 386 people km
–2
.
W
omach (2005)
Table 9-1 | Indicative examples of defi nitions of the “rural” and the “urban” in selected countries.
620
Chapter 9 Rural Areas
9
l
ess challenging (Seneviratne et al., 2012). Exposure to non-climate
trends and shocks further complicates the issue (Nielsen and Reenberg,
2010; see also Section 3.2.7).
The impacts of climate change on patterns of settlement, livelihoods,
and incomes in rural areas will be the result of multi-step causal chains
of impact. Typically, those chains will be of two sorts. One sort will
involve extreme events, such as floods and storms, as they impact on
rural infrastructure and cause direct loss of life. The other sort will
involve impacts on agriculture or on ecosystems on which rural people
depend. These impacts may themselves stem from extreme events, from
changing patterns of extremes due to climate change, or from changes
in mean conditions. The detection and attribution of extreme events is
discussed by the IPCC Special Report on Managing the Risks of Extreme
Events and Disasters to Advance Climate Change Adaptation (Seneviratne
et al., 2012). The detection and attribution of impacts on ecosystems
and on agriculture are dealt with in Chapters 4 and 7 of this report. Both
exercises are complex.
S
eneviratne et al. (2012) give a detailed and critical assessment of the
detection and attribution of observed patterns of extreme events, which
shows greatly varying levels of confidence in the attribution to climate
change of global and regional trends, and that “attribution of single
extreme events to anthropogenic climate change is challenging (p. 112).
They state that it is likely there has been a worldwide increase in
extreme high-water events during the late 20th century, with a likely
anthropogenic influence on it. They have medium confidence in detecting
trends toward more intense and frequent droughts in some parts of the
world (southern Europe and West Africa) since 1950. They note that
opposite trends exist elsewhere, and that there is low confidence in any
trend in drought in, for example, East Africa. WG I AR5 Chapter 2 similarly
ascribes low confidence in a global observed trend in drought in the
later 20th century, with a likely increase in frequency and intensity of
drought in the Mediterranean and West Africa and a likely decrease in
central North America. Lyon and DeWitt (2012) see a “recent and abrupt
decline in the East African long rains since 1999. Seneviratne et al.
(2012) assign low confidence to any observed long-term increases in
Finding Source
Importance of
non-climate
trends
The signifi cance of climate change needs to be considered in the multi-causal context of its interactions with other non-climate sources of change
a
nd stress (e.g., water scarcity, governance structures, institutional and jurisdictional fragmentation, limited revenue streams for public sector roles,
resource constraints, or infl exible land use patterns).
W 7.4.2
I
6.7.5
Different development paths may increase or decrease vulnerabilities to climate-change impacts. W 7.7
Neglect by policymakers and underinvestment in infrastructure and services has negatively affected rural areas. I 1.3.4
Policy neglect specifi cally disfavors rural women. I 1.3.4
Assessment of climate change impacts on agriculture has to be undertaken against a background of demographic and economic trends in rural areas. E 5.3.2
Global numbers of people at risk from hunger will be affected by climate change, but more by socioeconomic trends as captured in the difference
between the SRES scenarios.
E 5.6.5
Specifi c
characteristics
of smallholder
agriculture
Subsistence and smallholder livelihood systems suffer from a number of non-climate stressors, but are also characterized by having certain resilience
factors (effi ciencies associated with the use of family labor, livelihood diversity to spread risks).
E 5.3.2
Traditional knowledge of agriculture and natural resources is an important resilience factor. I 2.1.2, 3.2.2, 3.2.3
E 5.3.2
CC4
The combination of stressors and resilience factors gives rise to complex and locally specifi c impacts, resistant to modeling. E 5.4.7
W 7.2, 7.4, 7.5
Impacts on
agriculture
and
agricultural
trade
In low-latitude regions, temperature increases of 1–2°C are likely to have negative impacts on yields of major cereals. Further warming has
increasingly negative impacts in all regions.
E 5.4.2
Increases in global mean temperatures (GMTs) of 2–3°C might lead to a small rise or decline (10–15%) in food (cereals) prices, while GMT increases
in the range of 5.5°C or more might result in an increase in food prices of, on average, 30%.
E 5.6.1
Forestry
Loss of forest resources through climate change may affect 1.2 billion poor and forest-dependent people, including through impacts on non-timber
forest products.
E 5.4.5
Valuation
Robust valuation of climate change impact on human settlements is diffi cult, and social and environmental costs are poorly captured by monetary
metrics: non-monetary valuation methods should be explored.
W 7.4.3, 7.5
I 8.2.5
Adaptation
The need and the capacity to adapt vary considerably from region to region, and from farmer to farmer. I 1.3.3
Adaptation actions can be effective in achieving their specifi c goals, but they may have other (positive or negative) effects, including resource
competition.
I 6.7.5
Diversifi cation of agricultural and non-agricultural livelihood strategies is an important adaptation trend, but requires institutional support and access
to resources.
E 5.5.1, 5.5.2
The effectiveness of adaptation efforts is likely to vary signifi cantly between and within regions, depending on geographic location, vulnerability to
current climate extremes, level of economic diversifi cation and wealth, and institutional capacity.
I 6.8
Multi-stakeholder processes are increasingly important with respect to climate change adaptation. I 7.5.3
Links between
adaptation
and mitigation
Mitigation and adaptation policies are in many cases, and certainly for agriculture, closely linked. K 18.4.3, 18.7.1
E 5.4.1, 5.4.2, 5.6.5
W 7.1, 7.7
Table 9-2 | Relevant fi ndings on rural areas from the IPCC Fourth Assessment Report and the International Assessment of Agricultural Science and Technology for Development.
Sources: W = Wilbanks et al. (2007); E = Easterling et al. (2007); I = McIntyre et al. (2009); K = Klein et al. (2007); CC4 = Cross-Chapter Case Study C4 “Indigenous knowledge
for adaptation to climate change” in AR4 (Parry et al., 2007).
621
Rural Areas Chapter 9
9
t
ropical cyclone activity, as does WGI AR5 Chapter 2, and to attribution
of any changes in cyclone activity to anthropogenic influence. WGI
AR5 Chapter 2 states that an observed increase in the frequency and
intensity of North Atlantic cyclones is virtually certain. It also describes
varying regional trends toward heavy precipitation events, very likely
in central North America. Section 3.2.7 ascribes medium confidence
to observed increased likelihood of flooding at the scale of some
regions.
Handmer et al. (2012) discuss both observed and projected impacts of
extreme events on human systems and ecosystems, with numerous
examples of diverse, widespread negative impacts (see also Chapter
18). Important categories of extreme events causing negative impacts
in rural areas include tropical storms and droughts: Hurricane Stan in
October 2005 affected nearly 600,000 people on the Chiapas coast as
a consequence of flooding and sudden river overflows (Saldaña-Zorrilla,
2008). Droughts in rural areas produce severe economic stresses,
including employment reduction and migration (Gray and Mueller,
2
012). Agricultural livelihoods are affected by droughts. Ericksen et al.
(2012) review a variety of livestock mortality rates for recent droughts
in the Horn of Africa, ranging up to 80% of livestock in southern Kenya
in 2009.
Climate change impacts on agriculture and ecosystems run through rising
temperature and changes in rainfall variability and seasonality as well
as through extreme events. Changes in temperature caused reduction
in global yields of maize and wheat by 3.8 and 5.5% respectively from
1980 to 2008 relative to a counterfactual without climate change, which
offset in some countries some of the gains from improved agricultural
technology (Lobell et al., 2011; see also Section 7.2.1.1). Badjeck et al.
(2010) discuss current and future impacts on fisherfolk across the world.
Many local-level studies are subject to the attribution problems mentioned
above, but Wellard et al. (2012) cautiously note a convergence of climate
data with the perceptions of farmers and officials to the effect that over
the last 30 years the rainfall in Malawi has become less predictable, that
the rainy season is arriving later in the year causing delays in planting
Developed countries Developing countries
Demographic
trends
Rural population accounts for 22.3% of the total population (or about 276 million
p
eople) (UN-DESA Population Division, 2012). Rural areas account for 75% of land
area in OECD countries (OECD, 2006).
Rural population has peaked (absolute numbers) in Europe and North America.
Rural depopulation in some places, but also counter-urbanization with people
moving from urban to rural areas elsewhere.
Rural population accounts for 50.3% of the total population (or about 2.5 billion
p
eople) in less developed countries (excluding LDCs), 71.5% (or about 608 million
people) in LDCs.
Rural population has already peaked in Latin America and the Caribbean, East and
Southeast Asia; expected to peak around 2025 in the Middle East, North Africa,
South and Central Asia; around 2045 in sub-Saharan Africa.
Dependence on
agriculture
Agriculture accounts for only 13% of rural employment in the EU (OECD, 2006),
and less than 10% on average across developed countries; however, it has a strong
indirect infl uence on rural economies.
Increased competition as a result of economic globalization has resulted in
agriculture no longer being the main pillar of the rural economy in Europe.
Economic policies are primary drivers, with social re-composition and economic
restructuring taking place (Marsden, 1999; Lopez-i-Gelats et al., 2009).
Proportion of rural population engaged in agriculture declining in all regions
(Figure 9-2). Agriculture still provides jobs for 1.3 billion smallholders and landless
workers (World Bank, 2008).
Non-agricultural including labor-based and migration-based livelihoods increasingly
existing alongside (and complementing) farm-based livelihoods. Agricultural
initiatives and growth still important for adaptation and for smallholders in Africa
and Asia (Collier et al., 2008; Osbahr et al., 2008; Kotir, 2011).
Poverty and
inequality
Per capita gross domestic product (GDP) in rural areas of OECD countries is only
83% of national average (but signifi cant variation within and between countries):
driven by out-migration, aging, lower educational attainment, lower productivity of
labor, low levels of public services (OECD, 2006).
Rates of poverty (percentage of population living on less than US$2 per day) and
extreme poverty (percentage of population living on less than US$1.25 per day)
falling in rural areas in most parts of the world; but rural poverty and rural extreme
poverty rising in sub-Saharan Africa. Recent price hikes and volatility exacerbated
hunger and malnutrition among rural households, many of which are net food-
buyers (FAOSTATS, 2013). Hunger and malnutrition prevalent among rural children
in South Asia and sub-Saharan Africa (World Bank, 2007; IFAD, 2010); see Figure
9-2 and Table 9-4.
Economic,
policy,
governance
trends
Shift from agricultural (production) to leisure (consumption) activities; focus on
broader amenity values of rural landscapes for recreation, tourism, forests, and
ecosystem services (OECD, 2006; Rounsevell et al., 2006; Bunce, 2008).
Agricultural subsidies under pressure from international trade negotiations and
domestic budgetary constraints. As a result of recent price hikes, domestic price
support has been lowered in OECD countries.
New policy approach in OECD countries that focuses on investments and targets a
range of rural economic sectors and environmental services.
Interconnectedness and economic openness in rural areas have encouraged shifts
to commercial agriculture, livelihoods diversifi cation and help knowledge transfers
(Section 9.3.3).
Interlinkages between land tenure, food security, and biofuel policies impact rural
poverty (see Sections 7.1 and 7.2.2 for further details).
Decentralization of governance and emergence of rural civil society. Movements
toward land reform in some parts of Asia (Kumar, 2010). Emergence of economies
in transition, characterized in places by coexistence of leading and lagging regions;
political and democratic decentralization leading to increasing complexity of policy
(World Bank, 2007).
Environmental
degradation
Different socioeconomic scenarios have varying impacts on land use and
agricultural biodiversity (Reidsma et al., 2006).
Resource degradation, environmentally fragile lands subject to overuse and
population pressures, exacerbating social and environmental challenges. Multiple
stressors increase risk, reduce resilience, and exacerbate vulnerability among rural
communities from extreme events and climate change impacts (Section 13.2.6).
Rural-urban
linkages and
transformations
Changes in land use and land cover patterns at urban-rural fringe affected by new
residential development, local government planning decisions, and environmental
regulations (Brown, D.G. et al., 2008).
Stronger rural-urban linkages through migration, commuting, transfer of public
and private remittances, regional and international trade, infl ow of investment,
and diffusion of knowledge (through new information and communication
technologies) (IFAD, 2010). Continued out-migration to urban areas by the
semiskilled and low-skilled, reducing the size of the rural workforce (IFAD, 2010).
Trend for migration to small and medium-sized towns (Sall et al., 2010).
Increased volumes of agricultural trade, growing by 5% on average (annually)
between 2000 and 2008 (WTO, 2009). New initiatives of foreign direct investment
(FDI) in agriculture in the form of large-scale land acquisitions in developing
countries (World Bank, 2010; Anseeuw et al., 2012).
Table 9-3 | Major demographic, poverty-related, economic, governance, and environmental trends in rural areas of developed and developing countries.
622
Chapter 9 Rural Areas
9
1940 1960 1980 2000 2020 2040 20601940 1960 1980 2000 2020 2040 2060
1940 1960 1980 2000 2020 2040 2060
1940 1960 1980 2000 2020 2040 2060
1940 1960 1980 2000 2020 2040 20601940 1960 1980 2000 2020 2040 2060
(e) Africa
(c) Asia
(b) Europe
(a) Northern America
0
10
20
30
40
50
60
(f) Oceania
0
1000
2000
3000
4000
5000
6000
0
200
400
600
800
0
500
1000
1500
2000
2500
0
200
400
600
800
0
100
200
300
400
500
Population (Millions)Population (Millions)
(a)
(d)
(b)
(c)
(e)
(f)
(d) Latin America and
the Caribbean
Total population
Urban population
Rural population
Observed
Projected
Figure 9-1 | Trends in rural, urban, and total populations by region; solid lines represent observed values and dotted lines represent projections (UN DESA Population Division, 2013). Note: Regions used in the source do not correspond
with the IPCC regions covered in Chapters 22–30.
623
Rural Areas Chapter 9
9
of the main crops, and that damaging dry spells during the rainy season
have become more frequent.
Glacial retreat in Latin America is one of the best evidenced current
impacts on rural areas (see Section 27.3.1.1). In highland Peru there
have been rapid observed declines since 1962 in glacier area and dry-
season stream flow, on which local livelihoods depend, which accord
well with local perceptions of changes that are necessitating adaptation
(Orlove, 2009). Other studies of the area focus both on observed changes
in water availability and on glacial lake outburst floods, which are
attributable to climate change (Carey, 2010; Bury et al., 2011; Carey et
al., 2012). There is also a rich specialized literature on the impacts of
shrinking sea ice and changing seasonal patterns of ice formation and
melt on indigenous peoples in the Arctic (Ford, 2009; Beaumier and
Ford, 2010; see also Section 28.2.5.1.7).
Migration associated with weather-related extremes or longer-term
climate trends is discussed in Table 12-3, with empirical examples of
migrations linked to droughts, coastal storms, floods, and sea level rise.
The Asian Development Bank (ADB, 2012) gives a figure of 42 million
people displaced by extreme weather events in Asia and the Pacific over
2010–2011. Attribution of migration to climate change is extremely
complex, as recognized by Black et al. (2011a), because life in rural
areas across the world typically involves complex patterns of rural-
urban and rural-rural migration, subject to economic, political, social,
and demographic drivers, patterns that are modified or exacerbated by
climate events and trends rather than solely caused by them (see also
Section 12.4.1).
9.3.3. Future Impacts
This section examines the major impacts of climate change identified
or projected for rural areas, under the headings of economic base and
livelihoods; infrastructure; spatial and regional interconnections, including
migration, trade, investment, and knowledge; and second-order impacts
of climate policy. Section 9.3.4 assesses the literature on impact through
a different and specific lens, that of economic valuation. The biophysical
impacts of climate change on food crops are dealt with primarily in
Chapter 7; but also here and in Section 9.3.4 insofar as they affect rural
economies. Biophysical impacts on non-food cash crops are discussed
below. As with the observed impacts in Section 9.3.2, the future impacts
of climate change described here, and quantified in Section 9.3.4, are
at the latter stages of complex causal chains that flow through changing
patterns of extreme events and/or effects of climate change on biophysical
processes in agriculture and less-managed ecosystems. Lal et al. (2011)
show the regional specificity of projected socioeconomic impacts across
the rural USA, with different regions affected through agriculture, water
stress, and energy costs. Anderson et al. (2010) discuss the complexity
of projected impacts across dryland regions of developing countries.
These considerations increase the uncertainty associated with any
particular impact on the economic base, on land use, or on regional
interconnections.
9.3.3.1. Economic Base and Livelihoods
9.3.3.1.1. General considerations
Climate change will affect rural livelihoods, or “the capabilities, assets
(stores, resources, claims, and access) and activities required for a means
of living” (Chambers and Conway, 1992, p. 6). Many, though by no
means all, rural livelihoods are dependent on natural resources (e.g.,
agriculture, fishing, and forestry), and their availability will vary in a
changing climate. This will have effects on human security and well-
being (Kumssa and Jones, 2010; see also Chapter 12). Climate change
impacts on smallholder and subsistence farmers will be compounded by
environmental and physical processes affecting production at a landscape,
watershed, or community level; and other impacts, including those on
human health and on non-agricultural livelihoods (Morton, 2007) and
also trade and food prices (Anderson et al., 2010). Despite the growing
importance of non-farm livelihoods in rural areas worldwide (Ellis,
2000; Reardon et al., 2007), and households pursuing interdependent
agricultural and non-agricultural livelihoods in peri-urban areas as a
risk management strategy (Lerner and Eakin, 2010; Lerner et al., 2013),
there is a relative scarcity of literature on the interactions of these with
climate variability and climate change.
Climate variability and change interacts with, and sometimes compounds,
existing livelihood pressures in rural areas, such as economic policy,
globalization, environmental degradation, and HIV/AIDS, as has been
shown in Tanzania (Hamisi et al., 2012), Ghana (Westerhoff and Smit,
2009), South Africa (Reid and Vogel, 2006; Ziervogel and Taylor, 2008;
O’Brien et al., 2009), Malawi (Casale et al., 2010), Kenya (Oluoko-
Odingoa, 2011), Senegal (Mbow et al., 2008), and India (O’Brien et al.,
2004). Economic heterogeneity of farm households within communities,
in terms of farm and household size, crop choices, and input use, will be
important in determining impacts (Claessens et al., 2012), as will social
relations within households that affect production (Morton, 2007).
Projected impacts on yields and production of food crops are assessed in
Section 7.4.1 and Figure 7-7. Local warming in excess of 1°C is projected
to have negative impacts in both temperate and tropical regions without
adaptation (though individual locations may benefit). There is medium
confidence in large negative impacts of local increases of 3°C to 4°C,
on productivity, production, and food security, globally and particularly
Table 9-4 | Poverty indicators for rural areas of developing countries. Source: Adapted from IFAD (2010).
Incidence of poverty (%)
Incidence of rural
poverty (%)
Incidence of extreme
poverty (%)
Incidence of extreme
rural poverty (%)
Rural people as % of
those in extreme poverty
1988 2008 1988 2008 1988 2008 1988 2008 1988 2008
D
eveloping world 69.1 51.2 83.2 60.9 45.1 27.0 54.0 34.2 80.5 71.6
Note: the incidence of extreme poverty and poverty is defi ned as percentage of people living on less than US$1.25 per day and less than US$2 per day, respectively.
624
Chapter 9 Rural Areas
9
i
n tropical countries, that go beyond adaptive capacity. The impacts of
climate change on the agricultural sector in Africa, dominated by
smallholder farming and very largely rainfed, are considered to be very
significant to economies and livelihoods (Collier et al., 2008; Hassan,
2010; Kotir, 2011; Müller et al., 2011). These results emerge across a
range of scenarios. Several other studies also map declines in net
revenues from crops and the associated links with food security and
p
overty (Thurlow and Wobst, 2003; Reid et al., 2008; Molua, 2009;
Thurlow et al., 2009).
Post-harvest aspects of agriculture—storage on-farm and commercially,
handling, and transport—have been relatively neglected in discussions
of climate change, but will be affected by changes in temperature, rainfall,
humidity, and by extreme events. Many adaptation opportunities are
1988
2008
0
20
40
60
80
100
0
20
40
60
80
100
Percentage (%)Percentage (%)
RA/R PRPEPERPR/EP
RA/RPRPEPERPR/EP
RA/RP RPEPERPR/EP
RA/RPRPEPERPR/EP
Rural people as percentage of population
Agricultural population as percentage of rural
Incidence of poverty
RP
EP
ERP
R/EPR
A/R
P
Incidence of poverty in rural areas
Incidence of extreme poverty
Incidence of extreme poverty in rural areas
Rural people as percentage of
those in extreme poverty
(d) Middle East and
North Africa
(b) Latin America and
the Caribbean
(c) Asia and the Pacific
(a) Sub-Saharan Africa
Figure 9-2 | Demographic and poverty indicators for rural areas of developing countries, by region (adapted from IFAD, 2010). Shaded countries are those for which data were
available in the original source. Note: Regions used in the source do not correspond with the IPCC regions covered in Chapters 22–30.
625
Rural Areas Chapter 9
9
a
lready understood by post-harvest service providers, but getting post-
harvest knowledge into use at scale is a significant challenge (Stathers
et al., 2013; see also Tefera, 2012). Future impacts on production and
storage will affect prices. Food crises in Africa triggered by moderate
declines in agricultural production have been exacerbated by “exchange
entitlement failures”—food price spikes and asset price collapses
(Devereux, 2009). Rising food prices negatively affect many rural people
who are net food buyers (see Table 7-1), and the poorest of the poor in
rural areas—female-headed households (which tend to be poorer than
male-headed households) and those who have limited access to land,
modern agricultural inputs, infrastructure, and education (Ruel et al.,
2010).
The remainder of this section discusses issues around climate impacts
on agricultural livelihoods, other than food crop production: water as
an input to agriculture, non-food crops, livestock, and fisheries.
9.3.3.1.2. Water
Water supply will be impacted through climate change (Chapter 3). In
rural areas groundwater extraction and irrigation water availability is
crucial for agricultural livelihoods but is typically not included in modeled
projections of future crop yields, as discussed by Lobell and Field (2012).
At the same time, non-climate trends including population growth and
lack of adequate regulatory frameworks will greatly affect demand for
water by agriculture and other competing uses, as discussed by
Macdonald (2010) for the southwestern USA, by Juana et al. (2008) for
South Africa, and by multiple authors for the Middle East (Iglesias et al.,
2010; Chenoweth et al., 2011; Sowers et al., 2011; Hanafi et al., 2012;
Rochdane et al., 2012; Verner, 2012).
At the continental level in Africa, analysis of existing rainfall and recharge
studies suggests that climate change will not lead to widespread
catastrophic failure of improved rural groundwater supplies, but it
could affect a population of up to 90 million people, as they live in rural
areas where annual rainfall is between 200 and 500 mm yr
–1
, and where
decreases in annual rainfall, changes in intensity, or seasonal variations
may cause problems for groundwater supply (Macdonald et al., 2009).
At higher resolution groundwater resources are threatened (e.g., in
South Africa; Knüppe, 2011), and multiple water crises are expected to
result from the increasing demand, further affecting people in rural
areas (Nkem et al., 2011). Climate change is expected to impact water
resources in the Asian region in a major way. Immerzeel et al. (2010),
in a study of the Indus, Ganges, Brahmaputra, Yangtze, and Yellow River
basins, conclude that different river basins would experience different
impacts on water availability and food security due to climate change.
They further argue that the Brahmaputra and Indus basins would be
more susceptible to changes in water availability affecting the food
security of 60 million people. In southern Europe, declines in rainfall
and meltwater from glacial ice and snow would increase the costs
of production and living (Falloon and Betts, 2010). Drought could
threaten biodiversity and traditional ecosystems particularly in southern
Europe, with problems exacerbated by declining water quality. Decline
in economic activity may increase rural depopulation and harm the
development of rural communities in southern Europe (Westhoek et al.,
2006).
9.3.3.1.3. Non-food crops and high-value food crops
Non-food crops and high-value food crops, such as cotton, wine grapes,
beverage crops, and other cash crops, which represent an important
source of livelihood in many rural areas, have received less attention
than staple food crops when assessing the impacts of climate change.
Literature on biofuels such as jatropha focuses on the impacts of
biofuels on climate change rather than on the effects of climate on
yields and other relevant variables in these agricultural systems. Where
crops have dual use as food and biofuel (e.g., oilseeds, sugarcane, sugar
beet, maize, and wheat) impacts can be inferred from studies that focus
on their use for food.
The findings of Easterling et al. (2007), that cotton yields would decrease
as changes in temperature and precipitation overcome potential benefits
of increasing carbon dioxide (CO
2
), have been corroborated in other
findings, such as those of Haim et al. (2008, p. 433) that cotton cultivation
in Israel will decline by 52% and 38% by 2070–2100 under the SRES
A2 and B2 scenarios, and that the net revenue will also decrease by
240% and 173% in both scenarios. Few systematic assessments have
been done on other fiber crops such as jute, kenaf, and flax.
Climate change impacts on wine grapes have been extensively studied
and documented. Climate impacts such as increasing number of hot
days and decreasing frost risk may benefit some varieties. Lobell et al.
(2006) assess the impacts of climate change on yields of six perennial
crops in California by 2099, and report that the production of wine grapes
will experience relatively small changes compared to other commodities
during the concerned period. The uncertainty analysis shows the yield
variations are limited within 10%, although Gatto et al. (2009) argue
that the revenue of the industry in Napa, California, could decline by
2034. Jones et al. (2005) indicate that future climate change will exceed
climatic thresholds affecting ripening for existing varieties grown at the
margins of their climatic limits. Warmer conditions could also lead to
more poleward locations becoming more conducive to grape growing
and wine production.
Lobell and Field (2012) model impacts on 20 perennial crops in California
under the A2 and B1 scenarios; of the four crops with the most reliable
models cherry yields are projected to decline by nearly 20%, strawberries
and table grapes to experience smaller declines, and almonds a slight
positive trend. These projections do not incorporate adaptation options
or possible decline in irrigation water supply, which would limit
production. Yields of several cash crops in the Middle East such as olives,
apples, and pistachios may decline if winter temperatures are too high
(Verner, 2012).
The case of tropical beverage crops, in particular coffee, is discussed in
Box 9-1, and projected changes in area suitable for all three tropical
beverage crops are set out in Table 9-5.
9.3.3.1.4. Livestock
The impacts of climate change on livestock—which form a part of a
variety of farming systems (Devendra et al., 2005)—are seen by
Thornton et al. (2009) as a neglected research area complicated by other
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Chapter 9 Rural Areas
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Box 9-1 | Impacts of Climate Change on Tropical Beverage Crops
The major traded beverage crops coffee, tea, and cocoa support the livelihoods of several million small-scale producers in more than
60 countries of the tropics of Africa, Asia, and Latin America. Coffee production has long been recognized as sensitive to climate
variability, with global production and prices sensitive to occasional frosts in Brazil—the world’s largest producer (Varangis et al., 2003).
Likewise the livelihoods of millions of small producers are dependent both on stability of production and stability in world prices. During
the last crash in coffee prices from 2000–2003 poverty levels in the coffee growing regions of Nicaragua increased, while they fell in the
rest of the country (World Bank, 2003); subsequently during the drought associated with El Niño in 2005 coffee productivity fell to
between a third and half of normal, similarly leading to severely reduced income for small producers (Haggar, 2009).
Gay et al. (2006), analyzing the effects of recent climate change on coffee producing areas in Veracruz, Mexico, have developed
econometric models of the relationship between coffee productivity and fluctuations in temperature and precipitation, which gave an
R
2
of 0.69 against historical data. Extrapolating the historical tendencies in temperature and precipitation to 2020 and applying their
econometric model, they predict that coffee production is likely to decline by 34%, and this decline in production takes producers
from making net profits of on average around US$200 per acre to less than US$20 per acre. This has led to a series of studies
projecting the effects of climate change on the distribution of Arabica coffee growing areas of the coming decades summarized
below and in Table 9-5.
For Brazil, Assad et al. (2004) and Pinto et al. (2007) have mapped the changes in area suitable for coffee production in the four main
coffee producing states. A 3°C increase in temperature and 15% increase in rainfall (taken from the general prediction of climate
change for southern Brazil in the IPCC Third Assessment Report of 2001) would lead to major changes in the distribution of coffee
producing zones. In the main coffee producing states of Minas Gerais and São Paulo the potential area for production would decline
from 70 to 75% of the states to 20 to 25%, production in Gioas would be eliminated, but the area would be reduced only by 10% in
Parana. New areas suitable for production in Santa Catarina and Rio Grande do Sul will only partially compensate the loss of area in
other states (Pinto and Assad, 2008). The economic impacts of a rise in temperature of 3°C would cause a 60% decline in coffee
production in the state of São Paulo equal to nearly US$300 million income (Pinto et al., 2007).
Models developed by CIAT predict the distribution of coffee under the A2A climate scenario using a statistical downscaling of the
climate change data from 20 different General Circulation Models (GCMs) used in the IPCC Fourth Assessment. They use WorldClim
data to characterize the current distribution of coffee using 19 climatic variables and then use the climate data downscaled to 1, 5,
and 10 km resolution to map where those conditions may occur in the future (2020 or 2050). This method has been applied to coffee
distribution in Kenya (CIAT, 2010), Central America, and Mexico (Laderach et al., 2010; Glenn et al., 2013); tea production in Kenya
(CIAT, 2011a) and Uganda (CIAT, 2011b); and cocoa production in Ghana and Côte d’Ivoire (CIAT, 2011c; Laderach et al., 2013)
(Table 9-5). The suitability for coffee crops in Costa Rica, Nicaragua, and El Salvador will be reduced by 40% (Glenn et al., 2013)
while the loss of climatic niches in Colombia will force the migration of coffee crops toward higher altitudes by mid-21st century
(Ramirez-Villegas et al., 2012). In the same way, increases in temperature will affect tea production, in particular at low altitudes
(Wijeratne, et al., 2007). Only one similar study has been done for Robusta coffee (Simonett, 2006), in Uganda, which shows similarly
drastic changes in both distribution and total area suitable for coffee production.
Effects are also expected on the incidence of pests and diseases in these crops. Increased generations under climate change for the
coffee nematode have been predicted for Brazil (Ghini et al., 2008). Jaramillo et al. (2011) conclude that Coffee Berry Borer
(Hypothenemus hampei) distribution in East Africa has expanded as a result of rising temperatures, and predicts, based on A2A and B2B
scenarios of Met Office Hadley Centre climate prediction model 3 (HadCM3), that it will spread to affect the main coffee producing
areas of Ethiopia, Kenya, Uganda, Rwanda, and Burundi by 2050.
Continued next page
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Rural Areas Chapter 9
9
drivers of change, rapid change in livestock systems, spatial heterogeneity,
and social inequality between livestock keepers. They review various
pathways of impact on livestock. Impacts through drought will be
significant, as will heat stress, particularly of Bos taurus cattle. Impacts
through animal health and disease will be even harder to predict than
other categories of impact (Thornton et al., 2009). Franco et al. (2011)
reveal significant declines in forage for ranching in California under
SRES scenarios B1 and A2.
Pastoralists, who are dependent on livestock grazed in arid, semiarid,
or mountainous areas, display very specific combinations of adaptive
capacity, especially through mobility and vulnerability, as discussed in
Section 9.3.5. Ericksen et al. (2012), with particular reference to East
Africa, discuss possibilities of loss of rangeland productivity, changes
in rangeland composition toward browse species, and changes in herd
dynamics through more frequent droughts as possible impacts. In the
Middle East, rangelands will be under substantial climate stress, which
may reduce their carrying capacity, in light of the growing demand for
meat products and the region’s growing livestock population (Verner,
2012, p. 166). Little et al. (2001) discuss impacts of floods, directly and
through disease, on pastoral herds. Similarly in the Ferlo Region in
northern Senegal, modest reduction in rainfall of 15% in combination
with a 20% increase in rainfall variability could have considerable
effects on livestock stocking density and profits, reducing the optimal
stocking density by 30%, based on six GCMs (Hein et al., 2009).
As extensive livestock production is associated with semiarid areas
marginal for cropping, some authors project shifts toward livestock
production under climate change. Modeled data from across Africa on
the net income per unit of land from crops and different livestock
species show that farmers are more likely to keep livestock, compared
to crop cultivation, as temperatures increase and as precipitation
decreases. Within livestock production, beef production will decline and
sheep and goat production increase (Seo and Mendelsohn, 2007a). Large-
scale commercial beef cattle farmers are most vulnerable to climate
change, particularly because they are less likely to have diversified
(Seo and Mendelsohn, 2007b). Kabubo-Mariara (2009) shows for non-
pastoral areas of Kenya the nonlinear relationship of livestock production
to climate change, whereby increased mean precipitation of 1% could
reduce revenues from livestock by 6%. Jones and Thornton (2009)
identify major transition zones across Africa where increased probability
of drought up to 2050 will create conditions for shifts from cropping to
livestock.
9.3.3.1.5. Fisheries
Impacts of climate change on aquatic ecosystems will have adverse
consequences for the world’s 36 million fisherfolk, through multiple
pathways including changes in fish stock distribution and abundance,
and destruction of fishing gear and infrastructure in storms and severe
Box 9-1 (continued)
At a minimum climate change will cause considerable changes in the distribution of these crops, disrupting the livelihoods of millions
of small-holder producers. In many cases the area suitable for production would decrease considerably with increases of temperature
of only 2°C to 2.5°C. Although some local areas may experience improved conditions for coffee production, for example, high-altitude
areas of Guatemala, the overall predictions are for a reduction in area suitable for coffee production by 2050 in all countries studied
(Laderach et al., 2010).
Crop Countries Change in climate by 2050 Change in total area by 2050
Change in distribution by 2050
(in meters above sea level)
Coffee
Guatemala, Costa Rica,
Nicaragua, El Salvador,
Honduras, Mexico
6
2.0–2.5°C increase in temperature
5–10% decline in total rainfall
Between 38% and 89% decline in area suitable
for production
Minimum altitude suitable for production rise
from 600 to 1000
Kenya
1
2.3°C increase in temperature
Rainfall increase from 1405 mm to 1575 mm
Substantial decline in suitability of western
highlands, some decline in area optimal for
production in eastern highlands
Minimum altitude for production rise from
1000 to 1400
Tea
Kenya
2
2.3°C increase in temperature
Rainfall increase from 1655 mm to 1732 mm
Majority of western highlands lose suitability,
while losses are compensated by gains at
higher altitude in eastern highlands
Optimum altitude for production change from
1500–2100 to 2000–2300
Uganda
3
2.3°C increase in temperature
Rainfall increase from 1334 mm to 1394 mm
Considerable reduction in suitability for
production across all areas
Optimal altitude change from 1450–1650 to
1550–1650
Cocoa
Ghana, Côte d’Ivoire
4,5
2.1°C increase in temperature
No change in total rainfall
Considerable reduction in area suitable for
production; almost total elimination in Ivory
Coast without adaptation measures
Optimal altitude change from 100–250 to
450–500
Table 9-5 | Projected changes in areas suitable for production of tropical beverage crops by 2050.
Sources:
1
CIAT (2010);
2
CIAT (2011a);
3
CIAT (2011b);
4
CIAT (2011c);
5
Laderach et al. (2013);
6
Glenn et al. (2013). Projections use the SRES A2 scenario; the projection
methodology is described in Box 9-1.
628
Chapter 9 Rural Areas
9
w
eather events (Badjeck et al., 2010; see also Sections 5.4.3.3, 6.4.1.1,
7.4.2, 30.6.2.1). An indicator approach (assessing climate change
impacts together with the high share of fisheries as a source of income)
showed that economies with the highest vulnerability of capture
fisheries to climate change were in central and western Africa
(e.g., Malawi, Guinea, Senegal, and Uganda), Peru and Colombia in
northwestern South America, and four tropical Asian countries
(Bangladesh, Cambodia, Pakistan, and Yemen) (Allison et al., 2009). In
China, Japan, and South Korea, changes in climate and social systems
could have a negative impact on fisheries, adversely affecting livelihoods
and food security of the region (Kim, 2010).
9.3.3.2. Infrastructure
Assessments of the impacts of climate change on infrastructure take a
general or urban perspective and do not focus on rural areas, though
rural impacts can be inferred. River flooding and sea level rise will produce
temporary loss of land and land activities, and damage to transportation
infrastructure particularly on coastal areas (Kirshen et al., 2008), with
specific evidence from North America (Hess et al., 2008). Flooding events
may cause sediment transport and damage roads and bridges (Nearing
et al., 2004) as well as affecting reservoir storing capacity. Importantly,
in rural areas usually there are few alternatives once a road is blocked
and that may increase vulnerability of rural areas when facing extreme
hydroclimatological events that impact transportation infrastructure
(NRC, 2008). Climate change will affect the operation of existing water
infrastructures (Kundzewicz et al., 2008). Some documented impacts on
dams, reservoirs, and irrigation infrastructure include reduction of sediment
load due to reductions in flows (associated with lower precipitation),
positively affecting infrastructure operation (Wang et al., 2007); impacts
of climate variability and change on storage capacity that creates further
vulnerability (Lane et al., 1999); and failures in the reliability of water
allocation systems (based on water use rights) due to reductions of
streamflows under future climate scenarios (Meza et al., 2012).
In Arctic Canada and Alaska, infrastructure built for very cold weather
will deteriorate as the air and ground warm. Larsen et al. (2008)
estimate, using the Atmosphere-Ocean General Circulation Model
(AOGCM) intercomparison project and an A1B scenario, increases in
public infrastructure costs of 10 to 20% through 2030 and 10% through
2080 for Alaska, amounting to several billion dollars, much of it to be
spent outside of urban centers. Lemmen et al. (2008) reports that
foundation fixes alone in the largely rural Northwest Territories could
cost up to CAN$420 million, and that nearly all of northern Canada’s
extensive winter road network, which supplies rural communities and
supports extractive industries which bring billions of dollars to the
Canadian economy annually, is at risk (Furgal and Prowse, 2008) from
a 2°C to 4°C change in ground surface temperatures, which would imply
a cost of replacement with all-weather roadways of CAN$85,000 per
kilometer, over several decades.
9.3.3.3. Spatial and Regional Interconnections
In both developing and developed countries, rural areas have been
increasingly integrated with the rest of world. The main channels
t
hrough which this rapid integration process takes place are migration
(permanent and cyclical), commuting, transfer of public and private
remittances, regional and international trade, inflow of investment, and
diffusion of knowledge through new information and communication
technologies (IFAD, 2010), as well as the spatial intermingling of rural
and urban economic activities (see Box CC-UR).
9.3.3.3.1. Migration
It is difficult to establish a causal relationship between environmental
degradation and migration (see Section 12.4.1). Many authors argue
that migration will increase during times of environmental stress (e.g.,
Brown and Crawford, 2008; Afifi, 2011; Kniveton et al., 2011; Gray and
Mueller, 2012), and will lead to an increase in abandonment of settlements
(McLeman, 2011). Climate variability has been associated with rural-
urban migration (Mertz et al., 2011; Parnell and Walawege, 2011).
Another body of literature argues that migration rates are no higher
under conditions of environmental or climate stress (Cohen, 2004;
Brown, 2008; van der Geest and de Jeu, 2008; Tacoli, 2009; McLeman
and Hunter, 2010; Black et al., 2011a,b; Foresight, 2011; Gemenne,
2011; van der Geest, 2011). For Tacoli (2009) the current alarmist
predictions of massive flows of so-called “environmental refugees” or
“environmental migrants are not supported by past experiences of
responses to droughts and extreme weather events, and predictions
for future migration flows are tentative at best. Analogies with past
migration experiences are used frequently in such studies (McLeman
and Hunter, 2010). For example, in Ghana the causality of migration
was established to be relatively clear in the case of sudden-onset
environmental perturbations such as floods, whereas in case of slow-
onset environmental deterioration, there was usually a set of overlapping
causes—political and socioeconomic factors—that come into play (van
der Geest, 2011). Similarly, a recent survey by Mertz et al. (2010) has
argued that climate factors played a limited role in past adaptation
options of Sahelian farmers. Given the multiple drivers of migration
(Black et al., 2011a,b) and the complex interactions that mediate
migratory decision making by individual or households (McLeman and
Smit, 2006; Raleigh, 2008; Black et al., 2011a,b; Kniveton et al., 2011),
the projection of the effects of climate change on intra-rural and rural-
to-urban migration remains a major challenge.
9.3.3.3.2. Trade
Agricultural exports accounted for around one-sixth of world agricultural
production in 2012, while this proportion was higher for some
commodities such as oilseeds, sugar, and fish (OECD and FAO, 2013).
Global agricultural exports grew at an average annual rate of 9% in
2000–2005 and 11% in 2005–2011 (WTO, 2013, pp. 63–72). Apart from
a major price hike and high price volatility since 2007–2008, several
structural and cyclical factors—such as droughts in major producers,
expansion of area under biofuel crop production, financial speculation,
export restrictions—have led to volatility and unpredictability in the
trading environment (Chapter 7; see also Abbott, 2008; FAO, 2008;
Cooke and Robles, 2009; Karapinar and Haberli, 2010; Schmidhuber and
Matuschke, 2010; Timmer, 2010; Headey, 2011;Wright, B.D., 2011;
Anderson and Nelgen, 2012; Nazlioglu, 2013). In the absence of
629
Rural Areas Chapter 9
9
e
xtensive literature and reliable data on within-country trade, this
section focuses on international trade in the specific context of climate
change.
There is limited evidence and medium agreement that climate change
will affect trade patterns and it will increase international trade volumes
in both physical and value terms by altering the comparative advantage
of countries and regions, and given its potential impacts on agricultural
prices (Nelson et al., 2009b, 2010, 2013; Tamiotti et al., 2009). For
example, simulation based results from variants of the National Center
for Atmospheric Research (NCAR) and Commonwealth Scientific and
Industrial Research Organisation (CSIRO) climate models (A2 scenario)
suggest that climate change might lead to increases in export volumes
(of rice, wheat, maize, millet, sorghum, and other grains) from developed
to developing countries by 0.9 million Mtonnes to 39.9 million Mtonnes
by 2050. Higher export volumes are expected if future scenarios
consider CO
2
fertilization effects, as they produce lower world prices
than scenarios without CO
2
effects. Many regions including South Asia,
East Asia and Pacific, Middle East, North Africa, and sub-Saharan Africa
are projected to increase their imports substantially over this period
(Nelson et al., 2009b, 2010).
The recent literature highlights the potential role of trade in adaptation
to climate impacts on global crop yields, while cautioning policy makers
about the possible negative consequences of increased trade (Verburg
et al., 2009; Lotze-Campen et al., 2010; Huang et al., 2011; Schmitz et
al., 2012). Importing food might help countries adjust to climate change-
induced domestic productivity shocks and mitigate related welfare
losses (Reimer and Li, 2009; Tamiotti et al., 2009). Countries might also
capitalize on new export opportunities arising from higher achievable
yields, for example in Argentina (Asseng et al., 2013), or increasing
heterogeneity of climate impacts on yields in neighboring countries, for
example in Tanzania (Ahmed et al., 2012). Increased trade would lower
the cost of food and thus help alleviate food insecurity; however, if it is
driven by an expansion of agricultural areas (especially to marginal land
and to forests), it would also lead to negative environmental consequences
in the form of loss of biodiversity, deforestation, and additional carbon
emissions (Verburg et al., 2009; Lotze-Campen et al., 2010; Schmitz et
al., 2012).
If climate change affects crop yields negatively, and results in increased
frequency of extreme events (IPCC, 2012; see also Chapter 3), especially
in low-income developing countries, the consequent short-term food
deficits might need to be supplied, fully or partly, through food aid
(Alderman, 2010). Hence food aid agencies, such as the United Nations
World Food Programme, might face additional operational challenges
(Barrett and Maxwell, 2006; Harvey et al., 2010). Local or regional
procurement of food aid, targeted distribution of food, and safety net
programs through direct income transfers could be part of an overall
strategy to address climate-induced shocks to food security (see also
Chapter 7) (Alderman, 2010; Harvey et al., 2010).
The potential impacts of climate change on agricultural trade and the role
that trade could play in adaptation will inevitably depend on countries’
trade policies. There is medium evidence and medium agreement that
deepening agricultural markets through trade reform, improved market
access, avoiding export controls, and developing institutional mechanisms
t
o improve the predictability and the reliability of the world trading
system as well as investing in additional supply capacity of small-scale
farms in developing countries could help reduce market volatility and
offset supply shortages that might be caused by climate change (Reimer
and Li, 2009; Tamiotti et al., 2009; UNEP, 2009; Karapinar, 2011, 2012;
Tanaka and Hosoe, 2011; Ahmed et al., 2012).
9.3.3.3.3. Investment
Climate change may also affect investment patterns in rural areas. On
the one hand, countries, regions, and sectors that are expected to be
affected adversely by climate change may have difficulty attracting
investment. On the other hand, ecological zones that will become
favorable as a result of climate change are expected to see increasing
inflow of investment. The recent price hikes in agricultural commodities
have led to new initiatives of foreign direct investment (FDI) in large-
scale crop production (World Bank, 2010b; Anseeuw et al., 2012), with
capital-endowed countries with high food imports investing in large
production projects in low-income countries endowed with low-cost
labor forces and land and water resources. Climate change will lead to
similar investment patterns. However, there is a risk that these new
investments might not be integrated into local structures and that local
populations will become increasingly vulnerable as they lose access to
vital assets such as land and water (Anseeuw et al., 2012).
9.3.3.3.4. Knowledge
Rural areas are increasingly exposed to diffusion of knowledge through
migration, trade and investment flows, technology transfers, and
improved communication and transport facilities (IFAD, 2010), although
differentials on knowledge access and diffusion (e.g., access to high-
speed Internet) between rural and urban areas remain, even in high-
income countries. Future impacts of climate change on these channels
of integration will affect the pace and intensity of knowledge transfers.
If trade, migration, and investment flows will be intensified as a result
of climate change, this will have a positive impact on knowledge
transfer both from and to rural areas.
Traditional knowledge (TK) developed to adapt to past climate variability
and change can both be affected by climate change and used and
transformed in adaptation (Nyong et al., 2007). Ettenger (2012)
discusses how seasonal hunting camps among the Cree of Northern
Quebec that were the occasion for intergenerational knowledge transfer
have been disrupted by changing bird migrations, while new technologies
such as the Internet, GPS, and satellite phones have been integrated into
livelihood strategies. Climate change-induced migration can threaten TK
transfer (Valdivia et al., 2010; Gilles et al., 2013). Disaster management by
central government may undermine decentralization efforts, disfavoring
TK transfer (Dekens, 2008).
9.3.3.4. Second-Order Impacts of Climate Policy
Policy responses for mitigation and adaptation affect rural people and
their livelihoods and environments. Working toward increasing energy
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Chapter 9 Rural Areas
9
supply from renewable resources may result in landscape changes
(Dockerty et al., 2006; Prados 2010); increasing employment opportunities
(del Río and Burguillo, 2008); or increasing conflicts for scarce resources,
such as water (Gold and Bass, 2010; Blair et al., 2011; McIntyre and
Duane, 2011; Phadke, 2011). Planning applications for wind energy
schemes in the UK have been subject to local opposition when they are
perceived as having negative impacts on rural landscape qualities (van
der Horst, 2007; Wolsink, 2007; Jones and Eiser, 2010). Governance of
energy distribution is thus an important issue (Vermeylen, 2010; Devine-
Wright, 2011). Steps toward energy self-sufficiency can reinforce rural
autonomy in isolated rural communities, including indigenous groups
(Love and Garwood, 2011).
Social responses to such changes are expected (Molnar, 2010). The
promotion of biofuel crops has been an extremely controversial issue
during 2000–2010, as they have potential socioeconomic impacts related
to their asserted ability to act as stimulus for rural economies, promote
changes in land ownership, and affect food security (German et al.,
2011). Delucchi (2010) concludes that biofuels produced from intensive
agriculture will aggravate stresses on water supplies, water quality, and
land use, and impact rural areas (through land use change) and agriculture
(see also Box CC-WE). Concerns about the impact of biofuel production
on food security relates to increases in food prices, land concentration
(and landgrabs), and competition for water (Eide, 2008; Müller et al.,
2008; German et al., 2011). Gurgel et al. (2007), who modeled potential
production and implications of a global biofuels industry by the end of
the century under a reference scenario and a high-mitigation scenario,
recognized the need for a high land conversion rate to achieve moderate
objectives. Delucchi (2010) suggests developing biofuels programs with
low inputs of fossil fuels and chemicals, that do not require irrigation,
and on land with little or no economic or ecological opportunity cost
(Plevin et al., 2010). This implies analyzing each case in its context,
including production for both local and global markets, and factoring
in concerns for social, cultural, and economic costs of biofuel production
(i.e., impact of biofuel production on indigenous livelihoods and culture).
International mechanisms for