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The repercussions of climate change will be felt in various ways throughout both natural and human systems in Sub-Saharan Africa. Climate change projections for this region point to a warming trend, particularly in the inland subtropics; frequent occurrence of extreme heat events; increasing aridity; and changes in rainfall---with a particularly pronounced decline in southern Africa and an increase in East Africa. The region could also experience as much as one meter of sea-level rise by the end of this century under a 4 textdegreeC warming scenario. Sub-Saharan Africa's already high rates of undernutrition and infectious disease can be expected to increase compared to a scenario without climate change. Particularly vulnerable to these climatic changes are the rainfed agricultural systems on which the livelihoods of a large proportion of the region's population currently depend. As agricultural livelihoods become more precarious, the rate of rural--urban migration may be expected to grow, adding to the already significant urbanization trend in the region. The movement of people into informal settlements may expose them to a variety of risks different but no less serious than those faced in their place of origin, including outbreaks of infectious disease, flash flooding and food price increases. Impacts across sectors are likely to amplify the overall effect but remain little understood.
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Regional Environmental Change
ISSN 1436-3798
Reg Environ Change
DOI 10.1007/s10113-015-0910-2
Climate change impacts in Sub-Saharan
Africa: from physical changes to their social
Olivia Serdeczny, Sophie Adams, Florent
Baarsch, Dim Coumou, Alexander
Robinson, William Hare, Michiel
Schaeffer, Mahé Perrette, et al.
1 23
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Climate change impacts in Sub-Saharan Africa: from physical
changes to their social repercussions
Olivia Serdeczny
Sophie Adams
Florent Baarsch
Dim Coumou
Alexander Robinson
William Hare
Michiel Schaeffer
Julia Reinhardt
Received: 13 March 2015 / Accepted: 2 December 2015
Springer-Verlag Berlin Heidelberg 2016
Abstract The repercussions of climate change will be
felt in various ways throughout both natural and human
systems in Sub-Saharan Africa. Climate change projections
for this region point to a warming trend, particularly in the
inland subtropics; frequent occurrence of extreme heat
events; increasing aridity; and changes in rainfall—with a
particularly pronounced decline in southern Africa and an
increase in East Africa. The region could also experience
as much as one meter of sea-level rise by the end of this
century under a 4 C warming scenario. Sub-Saharan
Africa’s already high rates of undernutrition and infectious
disease can be expected to increase compared to a scenario
without climate change. Particularly vulnerable to these
climatic changes are the rainfed agricultural systems on
which the livelihoods of a large proportion of the region’s
population currently depend. As agricultural livelihoods
become more precarious, the rate of rural–urban migration
may be expected to grow, adding to the already significant
urbanization trend in the region. The movement of people
into informal settlements may expose them to a variety of
risks different but no less serious than those faced in their
place of origin, including outbreaks of infectious disease,
flash flooding and food price increases. Impacts across
sectors are likely to amplify the overall effect but remain
little understood.
Keywords Climate change Impacts Vulnerability
Sub-Saharan Africa
Africa has been identified as one of the parts of the world
most vulnerable to the impacts of climate change (IPCC
2014; Niang et al. 2014). Here we present an overview of
the impacts of climate change projected for the Sub-Sa-
haran region of the continent. Where possible, we draw
attention to how the magnitude of these impacts varies at
different levels of warming—particularly those corre-
sponding to 2 and 4 C above pre-industrial levels. This
paper offers a comprehensive understanding of how the
repercussions of climate change are felt throughout both
natural and human systems.
We combine original data analysis (heat extremes;
precipitation; aridity) with probabilistic projections (re-
gional sea-level rise) and a comprehensive literature review
(sectoral and human impacts). For the original data anal-
ysis, data were obtained from five CMIP5 GCMs for which
bias-corrected data were available (Hempel et al. 2013)as
selected by Warszawski et al. (2013). Where possible,
projections are presented for RCP2.6 and RCP8.5, which
are used as scenarios representing 2 and 4 C warming by
2100, respectively. For a detailed description of methods,
please see Schellnhuber et al. (2013). Unless accounted for
Electronic supplementary material The online version of this
article (doi:10.1007/s10113-015-0910-2) contains supplementary
material, which is available to authorized users.
&Olivia Serdeczny
Climate Analytics, Friedrichstr 231, 10969 Berlin, Germany
Potsdam Institute for Climate Impact Research (PIK),
Telegraphenberg A31, 14412 Potsdam, Germany
University of New South Wales, High St, Kensington,
NSW 2052, Australia
Universidad Complutense de Madrid, 28040 Madrid, Spain
Environmental Systems Analysis Group, Wageningen
University and Research Centre, PO Box 47,
6700 AA Wageningen, The Netherlands
Reg Environ Change
DOI 10.1007/s10113-015-0910-2
Author's personal copy
in individual models, projected impacts mostly do not
include adaptation.
Social, economic and demographic profile
of the Sub-Saharan region
Sub-Saharan Africa is a rapidly developing region of great
ecological, climatic and cultural diversity (NASAC 2015).
By 2050, its population is projected to approach 2 billion
people—a figure which rises to nearly 4 billion by 2100
(UN Department of Economic and Social Affairs 2013).
GDP growth increased from 3.7 % in 2012 to 4.7 % in
2013 although recent conflicts in the Central African
Republic and South Sudan have led to interruptions to
economic activity (World Bank 2013). National poverty
rates have been declining in most Sub-Saharan African
countries, with the exception of Mozambique, Cote d
and Guinea, although Sub-Saharan still has the largest
proportion of people living below the poverty line of all
world regions (World Bank 2015b). Levels of stunting
among children under 5 years of age as a result of chronic
hunger are slowly declining but remain high at 39.6 % in
2011 (United Nations Children’s Fund, World Health
Organization and The World Bank 2012). Around one in
four people in Sub-Saharan Africa is undernourished,
amounting to a quarter of the world’s undernourished
people (FAO, IFAD and WFP 2014).
The agriculture sector employs 65 % of Africa’s labor
force and the sector’s output has increased since 2000,
mainly due to an expansion of agricultural area (World
Bank 2013). Yield potential remains higher than actually
achieved, with inadequate water and nutrients being the
major limiting factors (Mueller et al. 2012). Agricultural
production in Sub-Saharan Africa is particularly vulnerable
to the effects of climate change, with rainfed agriculture
accounting for approximately 96 % of overall crop pro-
duction (World Bank 2015a). The production of crops and
livestock other than pigs in Sub-Saharan Africa is typically
located in semiarid regions (Barrios et al. 2008). In Bots-
wana, for example, pastoral agriculture represents the chief
source of livelihood for over 40 % of the nation’s residents,
with cattle representing an important source of status and
well-being for the vast majority of Kalahari residents
(Dougill et al. 2010). Relative poverty, which often limits
adaptive capacities of the local population and thus
increases vulnerability, is generally highest in highland
temperate, pastoral and agro-pastoral areas (Faures and
Santini 2008).
Higher food prices leading to currency depreciation and
conflict and emerging security threats have been identified
as a key risk to economic growth in the region (World
Bank 2013). Several historical case studies have identified
a connection between rainfall extremes and reduced GDP
because of reduced agricultural yields. Kenya suffered
annual damages of 10–16 % of GDP, not accounting for
indirect losses, because of flooding associated with the El
˜o in 1997–1998 and the La Nin
˜a drought 1998–2000.
The majority of flood losses were incurred in the transport
sector, and the drought event lead to a 41 % decline in
hydropower production and high costs to industrial pro-
duction and agricultural losses (World Bank 2004). Simi-
larly, historical temperature increases have had substantial
negative effects on agricultural value added in developing
countries. A 1 C increase in temperature in developing
countries has been found to be associated with 2.66 %
lower growth in agricultural output, leading to estimates of
economic growth reductions by an average of 1.3 per-
centage points for each degree of warming (Dell and Jones
2012) and reductions in export growth by 2.0–5.6 per-
centage points (Jones and Olken 2010).
Regional patterns of climate change
Temperature changes
Projected warming is slightly less strong than that of the
global land area, which is a general feature of the Southern
Hemisphere. In the low-emission scenario RCP2.6 (repre-
senting a 2 C world), African summer temperatures
increase until 2050 at about 1.5 C above the 1951–1980
baseline and remain at this level until the end of the cen-
tury. In the high-emission scenario RCP8.5 (representing a
4C world), warming continues until the end of the cen-
tury, with monthly summer temperatures over Sub-Saharan
Africa reaching 5 C above the 1951–1980 baseline by
2100. Geographically, this warming is rather uniformly
distributed, although inland regions in the subtropics warm
the most (see Figure SOM 1). In subtropical southern
Africa, the difference in warming between RCP2.6 and
RCP8.5 is especially large. This is likely due to a positive
feedback with precipitation: The models project a large
decrease in precipitation here (see Fig. 2), limiting the
effectiveness of evaporative cooling of the soil.
The normalized warming, indicating how unusual the
warming is compared to fluctuations experienced in the
past, shows a particularly strong trend in the tropics (Fig-
ure SOM 1). The monthly temperature distribution in
tropical Africa shifts by more than six standard deviations
under a high-emission scenario (RCP8.5), moving this
region to a new climatic regime by the end of the twenty-
first century. Under a low-emission scenario (RCP2.6),
only small regions in western tropical Africa will witness
substantial normalized warming of up to about four stan-
dard deviations.
O. Serdeczny et al.
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Heat extremes
Heat extremes, defined as temperatures 3 and 5 standard
deviations above the historical norm [3- and 5-sigma
events; see Schellnhuber et al. (2013) for further expla-
nation], increase under both emission scenarios, albeit
with large differences between the low- and the high-
emission scenarios. By 2100, the multi-model mean of
RCP8.5 projects that 75 % of summer months would be
hotter than 5-sigma (Figure SOM 2), which is substan-
tially higher than the global average (Coumou and
Robinson 2013). During the 2071–2099 period, more than
half (*60 %) of Sub-Saharan African summer months
are projected to be hotter than 5-sigma, with especially
strong increases in tropical West Africa (*90 %). Over
this period, almost all summer months across Sub-Saharan
Africa will be hotter than 3-sigma (Fig. 1). Under
RCP8.5, all African regions, especially the tropics, would
migrate to a new climatic regime. The precise timing of
this shift depends on the exact regional definition and the
model used.
Under the low-emission scenario, the bulk of the high-
impact heat extremes expected in Sub-Saharan Africa
under RCP8.5 would be avoided. Extremes beyond
5-sigma are projected to cover a minor, although non-
negligible, share of the surface land area (*5 %), con-
centrated over western tropical Africa (Figure SOM 2). In
contrast, the less extreme months, beyond 3-sigma, would
increase substantially occurring over about 30 % of the
Sub-Saharan land area (Figure SOM 2). Thus, even under a
low-emission scenario, a substantial increase in heat
extremes in the near term is anticipated.
Precipitation changes
A dipole pattern of wetting in tropical East Africa and
drying in southern Africa emerges in both seasons and in
both emission scenarios, with both increases and decreases
of 10–30 % (Fig. 2). Projected precipitation changes based
upon the full set of CMIP5 models show the same general
patterns, but the magnitude of change (in terms of per-
centages) is smaller (Collins et al. 2013). This likely
reflects only small differences in absolute terms as rainfall
over these regions is generally small. Under the low-
emission scenario, the models disagree on the direction of
change over larger areas. Under the high-emission sce-
nario, the percentage changes become larger everywhere
and the models converge in the direction of change. Due to
Fig. 1 Multi-model mean of the percentage of austral summer months in the time period 2071–2099 with temperatures greater than 3-sigma (top
row) and 5-sigma (bottom row) for scenario RCP2.6 (left) and RCP8.5 (right) over Sub-Saharan Africa
Climate change impacts in Sub-Saharan Africa: from physical changes to their social
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this stronger signal, model disagreement between areas
getting wetter and areas getting drier is limited to south-
eastern regions and some regions in tropical western Africa
for the months of June, July and August, and to south-
eastern regions for the months of December, January and
Wetting of the Horn of Africa is also reflected in pro-
jected extreme precipitation events based upon the full
CMIP5 model ensemble (Sillmann et al. 2013). The high-
emission scenario projects an increase in the total amount
of annual precipitation on days with at least 1 mm of
precipitation (total wet-day precipitation) in tropical
eastern Africa by 5–75 %, with the highest increase in the
Horn of Africa, although the latter represents a strong
relative change over a very dry area (Sillmann et al. 2013).
In contrast to global models, regional climate models
project no change, or even a drying for East Africa, espe-
cially during the long rains (Laprise et al. 2013). Consis-
tently, one regional climate model study projects an
increase in the number of dry days over East Africa (Vizy
and Cook 2012).
Sillmann et al. (2013) further projected changes of ?5
to -15 % in total wet-day precipitation for tropical
western Africa with large uncertainties, especially at the
Fig. 2 Multi-model mean of the percentage change in annual (top),
austral summer (DJF—middle) and austral winter (JJA–bottom)
precipitation for RCP2.6 (left) and RCP8.5 (right) for Sub-Saharan
Africa by 2071–2099 relative to 1951–1980. Hatched areas indicate
uncertainty regions with two out of five models disagreeing on the
direction of change compared to the remaining three models
O. Serdeczny et al.
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monsoon-dependent Guinea coast. Very wet days (that is,
the top 5 %) show even stronger increases: by 50–100 %
in eastern tropical Africa and by 30–70 % in western
tropical Africa. In southern Africa, total wet-day precip-
itation is projected to decrease by 15–45 % and very wet-
day precipitation to increase by around 20–30 % over
parts of the region. However, some localized areas along
the west coast of southern Africa are expected to see
decreases in very wet days (up to 30 %). Here, increases
in consecutive dry days coincide with decreases in heavy
precipitation days and maximum consecutive five-day
precipitation, indicating an intensification of dry condi-
tions. The percentile changes in total wet-day precipita-
tion, as well as in very wet days, are much less
pronounced in the low-emission scenario RCP2.6 (Sill-
mann et al. 2013).
Aridity and Potential Evapotranspiration
The long-term balance between demand and supply is a
fundamental determinant of the ecosystems and agricul-
tural systems able to thrive in a certain area. The aridity
index (AI) is an indicator which identifies ‘‘arid’’ regions,
that is, regions with a structural precipitation deficit (UNEP
1997; Zomer et al. 2008). AI is defined as total annual
precipitation divided by potential evapotranspiration. In
general, the annual mean of monthly potential evapotran-
spiration increases under global warming as it is primarily
temperature driven. In our analysis, this is observed over
all of Sub-Saharan Africa with strong model agreement,
except for regions projected to see a strong increase in
precipitation [see Figure SOM 2 and Schellnhuber et al.
(2013) for a detailed description of methods]. In East
Africa and the Sahel region, the multi-model mean shows a
small reduction in potential evapotranspiration, albeit with
little model agreement. By contrast, a more unambiguous
signal emerges for regions projected to get less rainfall
(notably southern Africa), where the projections show an
enhanced increase in potential evapotranspiration (see
Figure SOM 3).
Projected aridity changes show the strongest deteriora-
tion toward more arid conditions in southern Africa
(Fig. 3). In southwestern Africa, the shift toward more arid
conditions due to a decline in rainfall (Fig. 2) is exacer-
bated by temperature-driven increases in evapotranspira-
tion (see Figure SOM 3). By contrast, the higher aridity
index in East Africa is correlated with higher rainfall
projected by global climate models, which, however, is
uncertain and not reproduced by higher-resolution regional
climate models. In addition, note that for Somalia and
eastern Ethiopia, the shift implies a large relative shift
imposed on a very low aridity index value, which results in
AI values still classified as arid or semiarid.
Sea-level rise
Projections of future sea-level rise are not uniform across
the world. Sub-Saharan Africa as defined in this paper
stretches from 15north to 35south. Because of the
dominantly tropical location of this region, projections of
local sea-level rise along Sub-Saharan coastlines tend to be
higher than the global average, by about 10 %.
Sea-level rise for a selection of locations in Sub-Saharan
Africa is shown in Fig. 4. For a detailed description of the
methods, please see (Schellnhuber et al. 2014). In our
projections to 2081–2100, there are no significant differ-
ences between the three locations in West Africa (Abidjan,
´, Lagos) and Maputo, in southeast Africa. At each of
these locations, sea level is projected to rise between 0.4 m
and 1.15 m in a 4 C world, with a median rise of 0.65 m.
In a 2 C world, sea-level rise is expected to be consis-
tently lower, with a range of 0.2–0.7 m and a median rise
of 0.4 m. We note that local factors such as land subsi-
dence from natural or human factors, or change in
storminess, which may substantially modify sea-level
change experienced by the population, are not included in
the projections.
Sectoral impacts
Water resources
Rising demand poses substantial threats to water security in
Sub-Saharan Africa, and this is exacerbated by climatic
changes affecting river runoff, contributing to higher irri-
gation water demand and posing risks of shallow ground-
water contamination due to intense rainfall (MacDonald
et al. 2009). The factors increasing water demand include
irrigation and hydropower production. Both of these are
expected to rise with population and economic growth but
are also affected by climatic changes through an increase in
evaporative losses (Beck and Bernauer 2011).
The variability of interannual rainfall over most of
Africa is high (Janowiak 1988; Hulme et al. 2001). Sub-
stantial multi-decadal rainfall variability is particularly
pronounced in the Sahel region (Hulme et al. 2001). A
period of low rainfall during the 1970s and 1980s com-
pared to the 1900–1970 period caused severe droughts in
the region, for example (Mahe et al. 2013; Hulme 2002).
Descroix et al. (2009) and Amogu et al. (2010) found
decreasing streamflows for rivers in Sudanian areas and
increasing discharge for those in the Sahelian regions.
Serious flooding has increased in the Niger Basin in the last
two decades (Aich et al. 2014a; Amogu et al. 2010), with
the risk of flooding increasing with rising temperatures
(Aich et al. 2014b; Amogu et al. 2010).
Climate change impacts in Sub-Saharan Africa: from physical changes to their social
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In many parts of rural Sub-Saharan Africa, groundwater
is the sole source of safe drinking water (MacDonald et al.
2009). Most of Sub-Saharan Africa has generally low
permeability and minor aquifers, with some larger aquifer
systems located only in the Congo, parts of Angola and
southern Nigeria (MacDonald et al. 2012). Groundwater
recharge rates have been projected to decline by 30–70 %
in the western parts of southern Africa and to increase by
around 30 % in some parts of East and southeastern Africa
for both 2 and 3 C warming above pre-industrial levels
¨ll 2009). However, these increases may be overesti-
mated, as the increased incidence of heavy rains, which are
likely in East Africa (Sillmann et al. 2013), lowers actual
groundwater recharge because of infiltration limits which
are not considered in Do
¨ll (2009). The uncertainties asso-
ciated with these results are large and relate to climate
projections as well as those associated with the hydrolog-
ical model used and the lack of knowledge about ground-
water aquifers (MacDonald et al. 2009). A further
uncertainty relates to changes in land use because of
agriculture, which responds differently to changes in pre-
cipitation compared to natural ecosystems (Taylor et al.
2012). We can be more certain about increases in
groundwater extraction in absolute terms resulting from
population growth and growing demand particularly in
semiarid regions due to projected increases of droughts and
an expected expansion of irrigated land (Taylor et al.
Fig. 4 Local sea-level rise
above 1986–2005 mean as a
result of global climate change
(excluding contribution from
pumping groundwater and local
land subsidence or uplift from
natural or human causes).
Colors indicate the RCP
scenarios (RCP2.6, or 2 C
world: blue; RCP8.5, or 4 C
world: green), shading indicates
the uncertainty range, and thick
lines indicate median
projections. Global sea-level
rise is superimposed as thin
(median) and dashed lines (low
and high bounds) (color
figure online)
Fig. 3 Multi-model mean of the percentage change in the aridity
index in a 2 C world (left) and a 4 C world (right) for Sub-Saharan
Africa by 2071–2099 relative to 1951–1980. In non-hatched areas, at
least 4/5 (80 %) of models agree. In hatched areas, at least 2/5 (40 %)
disagree. Note that a negative change corresponds to a shift to more
arid conditions and vice versa
O. Serdeczny et al.
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Seasonal water shortages along river basins are expected
mostly in the southern parts of East Africa (Niang et al.
2014). Comparing changes in river flow across the Niger,
Upper Blue Nile, Oubangui and Limpopo river basins by
using the output of the five bias-corrected CMIP5 climate
models (Hempel et al. 2013), which also underlie temper-
ature and precipitation projections in this paper, and
applying the ecohydrological model SWIM (Krysanova
et al. 1998) show highly uncertain results with high dis-
agreement between models (Aich et al. 2014b). However,
for the Blue Nile Basin, a consistent increase in mean
annual flows and low flows was found for 2 C warming by
mid-century (RCP8.5 in 2020–2049) and 4 C world
(RCP8.5 in 2070–2099) with low flow increases of 10 to
50 %, respectively (Aich et al. 2014b), as well as a robust
trend in increasing risk of flooding. High flows are pro-
jected to increase by 10–50 % under 2 C warming by
mid-century and 10–150 % in a 4 C world (Aich et al.
For western Kenya (Nyando catchment), a tendency of
increasing peak flows for a 3 C world by mid-century has
been projected; mean annual runoff change as well as
changes in low flows are rather uncertain (Taye et al.
2011). In a recent model intercomparison by Schewe et al.
(2013), an increase in annual discharge of about 50 % in
East Africa (especially southern Somalia, Kenya and
southern Ethiopia) is projected with more than 80 % model
consensus for a warming of 2.7 C. For South Africa,
Schewe et al. (2013) found decreases of 30–50 % for
annual runoff in a warming scenario of 2.7 C by the end
of the century. For a warming of about 4.5 C above pre-
industrial levels, even more pronounced decreases in
southern Africa of up to 80 % were found (Fung et al.
2011; Arnell et al. 2011).
Projections on future discharge for the Niger Basin in
West Africa showed diverging trends between climate
models on mean and high flows, depending also on the
location in the basin, for a 2 and 4 C world. Trends in low
flows were mostly positive but have to be interpreted with
caution (Aich et al. 2014b). Schewe et al. (2013) found
decreases in annual runoff of 10–30 % with a strong level
of model agreement (60–80 %) for Ghana, Co
ˆte D’Ivoire
and southern Nigeria in a warming scenario of 2.7 C
above pre-industrial levels. Large uncertainties remain for
many regions (e.g., along the coast of Namibia, Angola and
central Congo) (Schewe et al. 2013).
Many of those areas that are classified as blue water
scarce can at present provide an adequate overall supply of
green water to produce a standard diet (Rockstro
¨m et al.
2009). Projections of green water availability by a single
hydrological model show decreases of about 20 % relative
to 1971–2000 over most of Africa and increases of about
20 % for Somalia, Ethiopia and Kenya by 2080 with a
global mean warming of about 3 C above pre-industrial
levels (Gerten et al. 2011).
Overall projections of impacts of climate change on
water resources in Sub-Saharan Africa are associated with
large uncertainties. Apart from addressing the lack of
observational data, key challenges for assessing climatic
risks to water availability relate to their responses to heat
waves, seasonal rainfall variability as well as the rela-
tionship between land use changes, evapotranspiration and
soil moisture at different levels of global warming (Niang
et al. 2014).
Agricultural production
The high levels of dependence on precipitation for the
viability of Sub-Saharan African agriculture, in combina-
tion with observed crop sensitivities to maximum temper-
atures during the growing season (Asseng et al. 2011;
Lobell et al. 2011; Schlenker and Roberts 2009), indicate
significant risks to the sector from climate change. The
IPCC states with high levels of confidence that the overall
effect of climate change on yields of major cereal crops in
the African region is very likely to be negative, with strong
regional variation (Niang et al. 2014). ‘‘Worst-case’’ pro-
jections (5th percentile) indicate losses of 27–32 % for
maize, sorghum, millet and groundnut for a warming of
about 2 C above pre-industrial levels by mid-century
(Schlenker and Lobell 2010). Using output from 14 CMIP3
GCMs and applying the crop model DSSAT, Thornton
et al. (2011) estimate mean yield losses of 24 for maize and
71 % for beans under warming exceeding 4 C. In a global
study using the same bias-corrected climate data from five
CMIP5 GCMs (see Hempel et al. 2013) that underlie
temperature and precipitation projections in this paper, and
seven crop models, Rosenzweig et al. (2014) find yield
decreases of [50 % for Maize in the Sahelian region and
around 10–20 % in other Sub-Saharan regions if nitrogen
stress is considered. Not considering nitrogen stress results
in higher model disagreement but still an overall negative
trend of 5 to [50 %. Cassava appears to be more resistant
to high temperatures and unstable precipitation than cereal
crops (Niang et al. 2014). Similarly, multiple-cropping
systems appear to reduce the risk of crop failure compared
to single-cropping systems (Waha et al. 2012).
A number of adverse effects on crop yields are as yet not
represented in modeling studies. High-temperature sensi-
tivity thresholds for important crops such as maize, wheat
and sorghum have been observed, with large yield reduc-
tions once the threshold is exceeded (Luo 2011). Maize,
which is one of the most common crops in Sub-Saharan
Africa, has been found to have a particularly high sensi-
tivity to temperatures above 30 C within the growing
season. Each day in the growing season spent at a
Climate change impacts in Sub-Saharan Africa: from physical changes to their social
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temperature above 30 C reduces yields by 1 % compared
to optimal, drought-free rainfed conditions (Lobell et al.
2011). The annual average temperature across Sub-Saharan
Africa is already above the optimal temperature for wheat
during the growing season (Liu et al. 2008), and it is
expected to increase further. The sharp declines in crop
yields that have been observed beyond certain thresholds
are mostly not included in present process-based agricul-
tural models (Ro
¨tter et al. 2011).
Moreover, climate extremes can alter the ecology of
plant pathogens, and higher soil temperatures can promote
fungal growth that kills seedlings (Patz et al. 2008). Such
effects are as yet not represented in modeling studies.
Similarly, the effect of CO
fertilization remains uncertain
but important: Depending on crop type and region,
assuming positive CO
fertilization may even reverse the
direction of impacts. However, major crops in West Africa
are C4 crops, such as maize, millet and sorghum, which
benefits less from higher CO
concentration, so that the
positive effect may be overestimated (Roudier et al. 2011).
Livestock production in Sub-Saharan Africa is also
vulnerable to climate change. Livestock is an important
source of food (such as meat and milk and other dairy
products), animal products (such as leather), income, or
insurance against crop failure (Seo and Mendelsohn 2007).
The pastoral systems of the drylands of the Sahel, for
example, are highly dependent on natural resources,
including pasture, fodder, forest products and water, all of
which are directly affected by climate variability (Djoudi
et al. 2011). Livestock is vulnerable to drought, particularly
where it depends on local biomass production (Masike and
Ulrich 2008), with a strong correlation between drought
and animal death (Thornton et al. 2009). Available range-
land may be reduced by human influences, including
moves toward increased biofuel cultivation, veterinary
fencing, increasing competition for land and land degra-
dation (Morton 2012; Sallu et al. 2010). Thorny bush
encroachment, for example, is brought about by land
degradation (Dougill et al. 2010), as well as rising atmo-
spheric CO
concentrations (Higgins and Scheiter 2012).
Savanna ecosystems
Among Sub-Saharan African ecosystems, savanna vege-
tation has been identified as highly vulnerable to the
effects of climate change (Midgley and Thuiller 2011).
During the last decades, the encroachment of woody
plants has already affected savannas (Buitenwerf et al.
2012;Ward2005). Woody plants are often unpalatable to
domestic livestock (Ward 2005). Observed expansions in
tree cover in South Africa have been attributed to
increased atmospheric CO
concentration or nitrogen
deposition (Wigley et al. 2010). In the western Sahel,
however, a 20 % decline in tree density and a significant
decline in species richness across the Sahel have been
observed for the second half of the twentieth century and
attributed to changes in temperature and rainfall vari-
ability (Gonzalez et al. 2012).
While short-term responses of ecosystems in African
biomes are typically driven by water availability and fire
regimes, in the longer term African biomes appear highly
sensitive to changes in atmospheric CO
(Midgley and Thuiller 2011). A potential shift in compet-
itive advantage from heat-tolerant C4 grasses to C3 trees
which better benefit from high CO
concentrations pro-
duces to the risk of abrupt vegetation shifts at the local
level (Higgins and Scheiter 2012). The effect may be fur-
ther enhanced by a positive feedback loop: Trees are
expected to accumulate enough biomass under elevated
atmospheric CO
concentrations to recover from fires
(Kgope et al. 2009), shading out C4 grass production and
contributing to lower severity of fires, which further pro-
motes tree growth. High rainfall savannas can be replaced
by forests in less than 20–30 years (Bond and Parr 2010).
However, forests are also at risk from changes in temper-
ature and precipitation. If extreme weather conditions
increase, forests may shrink at the expense of grasses
(Bond and Parr 2010). Despite persistent uncertainties
pertaining to these mechanisms and thresholds marking
tree mortality, increases in extreme droughts and temper-
atures pose risks of broadscale climate-induced tree mor-
tality (Allen et al. 2010).
Ocean ecosystems
Aquatic ecosystems globally respond sensitively to the
effects of climate change (Ndebele-Murisa et al. 2010;
Cheung et al. 2010). Consequent risks include the decline
in key protein sources and reduced income generation
because of decreasing fish catches (Badjeck et al. 2010).
Freshwater ecosystems are affected by droughts and asso-
ciated reductions in nutrient influxes as river inflow is
temporarily reduced (Ndebele-Murisa et al. 2010). Fur-
thermore, increasing freshwater demand in urban areas of
large river basins may lead to reduced river flows, which
may become insufficient to maintain ecological production,
meaning that freshwater fish populations may be impacted
(McDonald et al. 2011).
Ocean ecosystems respond to altered ocean conditions
with changes in primary productivity, species distribution
and food web structure (Cheung et al. 2010). Irreversible
changes are expected at further warming of 1 C above
present (Po
¨rtner et al. 2014). Theory and empirical studies
suggest a shift of ocean ecosystems toward higher latitudes
and deeper waters in response to such changes (Cheung
et al. 2010). However, there is also an associated risk that
O. Serdeczny et al.
Author's personal copy
some species and even whole ecosystems will be placed at
risk of extinction (Drinkwater et al. 2010). Projections for
the western African coast—where fish contributes as much
as 50 % of animal protein consumed (Lam et al. 2012)—
show adverse changes in maximum catch potential of -16
to -5 % for Namibia, -31 to 15 % for Cameroon and
Gabon and up to 50 % for the coast of Liberia and Sierra
Leone for a warming of 2 C above pre-industrial levels
(Cheung et al. 2010). These projections do not account for
changes in ocean acidity or oxygen availability, which are
known to negatively impact the performance of marine
organisms (Po
¨rtner 2010; Stramma et al. 2008,2010).
Coastal populations and infrastructure
In the Sub-Saharan African region, the populations of
Mozambique and Nigeria are projected to be most affected
by sea-level rise in terms of the absolute number of people
flooded annually (Hinkel et al. 2011). Assuming 126 cm
(64 cm) of global mean sea-level rise above 1995 values by
2100, which corresponds to upper bound (median) esti-
mates in a 4 C world, and assuming no adaptation,
approximately 2 (1) million more people in Mozambique
would be exposed to annual flooding than in scenario
without sea-level rise, while in Nigeria approximately 3
(2.5) million more people would be flooded annually. In
terms of the proportion of the total national population
affected by annually flooding, Guinea-Bissau, Mozam-
bique and Gambia are most severely impacted (Hinkel
et al. 2011).
Sea-level rise exacerbates the risk of coastal flooding
associated with tropical cyclone activity. A medium sea-
level rise scenario of 0.3 m by 2050 could see current 1-in-
100-year storm surge events in Maputo, Mozambique, for
example, occurring once in every 20 years (Neuman et al.
2013). Brecht et al. (2012) also finds Mozambique, along
with Madagascar, to be particularly vulnerable in a study of
the combined impacts of sea-level rise and cyclonic storm
surges. Dasgupta et al. (2011) project Mozambique and
Tanzania to be among those countries in the developing
world most exposed across several indicators (proportion
of total land area, GDP, urban land area, agricultural area
and wetland area exposed) to a 10 % intensification of
storm surges along with 1-m sea-level rise.
Sea-level rise and storm surges can have significant
economic impacts. Damage to port infrastructure in Dar es
Salaam, Tanzania, for instance—which handles approxi-
mately 95 % of Tanzania’s international trade and serves
landlocked countries further inland (Kebede and Nicholls
2011)—could have ramifications for the economies of
Tanzania and other countries in the region. Most of the
tourism facilities of Mombasa, Kenya, are located in
coastal zones, where damage is already caused almost
every year by extreme weather events (Kebede et al. 2012).
Damage to seafront hotel infrastructure has also already
been reported in Cotonou, Benin—with this also consid-
ered a risk with rising sea levels elsewhere (Hope 2009).
In terms of economic impacts, Mozambique and Gui-
nea-Bissau are projected to experience the highest annual
damage costs as a proportion of GDP as a result of coastal
flooding, forced migration, salinity intrusion and loss of dry
land associated with sea-level rise (Hinkel et al. 2011).
According to Dasgupta et al. (2011), the most economi-
cally important areas in the region that are prone to storm
surges in a scenario of 1-m sea-level rise are located in
Mozambique and Tanzania. Abidjan in Cote d’Ivoire is
also ranked highly in a global study of the average annual
loss as a percentage of GDP caused by coastal flooding in
cities, with around 1 % lost annually for 0.4 m of sea-level
rise by 2050 taking into account socioeconomic change,
subsidence and adaptation in the form of flood defences
(Hallegatte et al. 2013).
Human impacts
The sections below outline risks in three areas that have
been identified as affected by climate change and which are
subject to ongoing research: human health, migration and
conflict. It has long been established that climate change is
rarely a single driver but tends to be mediated by existing
contextual factors to produce repercussions for human life
(IPCC 2014). An extensive and growing body of research
on the nature and determinants of vulnerability is investi-
gating the role of context (e.g., Birkmann et al. 2013).
While this paper is unable to cover this rich scholarship,
the following discussion will illustrate some of the ways in
which contextual factors shape climate impacts, at the
same time that these impacts can coincide and interact with
one another to produce combined implications greater than
the sum of the first-order impacts.
Human health
Among the direct effects of climate change on human
health are fatalities and injuries as a result of extreme
weather events or disasters, such as flooding or landslides
following heavy rain (McMichael and Lindgren 2011;
WHO 2009). Extreme heat events can also have a direct
impact on health by causing heat stress. Lengthy exposure
to high temperatures can bring about heat cramps, fainting,
heat exhaustion, heat stroke and death and compromise
outdoor human activities (Smith et al. 2014). Correlations
between high ambient temperatures and increased all-cause
mortality have been identified in Ghana and Kenya
(Azongo et al. 2012; Egondi et al. 2012), with the young
Climate change impacts in Sub-Saharan Africa: from physical changes to their social
Author's personal copy
and the elderly particularly susceptible. Drought condi-
tions, which can affect the availability and quality of water,
have been linked to such illnesses as diarrhea, scabies,
conjunctivitis and trachoma (Patz et al. 2008).
Climate change impacts on agriculture are expected to
undermine human health by affecting the affordability and
availability of nutritious food. While levels of undernutri-
tion are already high across the Sub-Saharan African
region, projections indicate that with warming of
1.2–1.7 C by 2050, the proportion of the population that is
undernourished would increase by 25–90 % compared to
the present (Lloyd et al. 2011). Undernutrition places
people at risk of secondary or indirect health implications
by heightening susceptibility to other diseases (World
Health Organization 2009; World Bank Group 2010). It
can also lead to child stunting, which is associated with
reduced cognitive development and poor health into
adulthood (Cohen et al. 2008). Projections indicate that the
proportion of moderately stunted children in the region
would not increase above the 2010 baseline level of
16–22 % in a scenario without climate change, but with
1.2–1.7 C above pre-industrial values by 2050 could
increase by 9 %. The proportion of severely stunted chil-
dren, which is estimated at 12–20 % in 2010, is projected
to decrease by 40 % without climate change and by only
10 % with climate change (Lloyd et al. 2011).
Outbreaks of transmittable diseases, both food- and
water- and vector-borne, can occur following extreme
weather events such as flooding. Past outbreaks of cholera,
which is associated with contaminated water and poor
sanitation, have been observed to follow heavy rainfall
events combined with elevated temperatures (Tschakert
2007; Luque Ferna
´ndez et al. 2009; Reyburn et al. 2011).
This occurred during the severe flooding in Mozambique in
2000 and again in the province of Cabo Delgado in early
2013 (Star Africa 2013; UNICEF 2013).
Intra-seasonal rainfall variability is a key risk factor for
Rift Valley fever, a disease transmitted via mosquito or
domestic animals hosting the virus. Outbreaks tend to
occur after a long dry spell followed by an intense rainfall
event (Caminade et al. 2011). Projections of increased
rainfall variability in the Sahel point to a likely increase in
the incidence in this region. Northern Senegal and southern
Mauritania have been identified as risk hotspots, given the
relatively high livestock densities in these areas (Caminade
et al. 2011).
The distribution of some vector-borne diseases is
expected to shift. For example, malaria appears to already
be spreading into the highlands of Ethiopia, Kenya,
Rwanda and Burundi, where it previously was not present.
In the Sahel, the northern fringe of the malaria epidemic
belt is projected to shift southward by 1–2with a
warming of 1.7 C by 2031–2050 due to a projected
decrease in the number of rainy days in summer (Caminade
et al. 2011), potentially leaving fewer people in the
northern Sahel exposed to malaria. More recent malaria
model intercomparison further indicates a decrease in the
length of transmission season for the Sahel (Caminade
et al. 2014). Overall, an increase in the risk of malaria is
projected for eastern, central and southern Africa; for
eastern Africa, estimates of additional people at risk range
from around 40–80 million under 2 C warming and from
around 70–170 million under 4 C warming (Caminade
et al. 2014). There is, however, significant uncertainty in
anticipating changes in malaria distribution due to the
complexity of factors—both climatic and non-climatic—
involved, with the relationship between temperature and
malaria transmission varying from region to region
(Chaves and Koenraadt 2010).
Population movement
Generally, the displacement of people is projected to
increase under continued climate change (IPCC 2014). The
drivers of migration tend to be complex and also include
cultural, economic and political factors as well as non-
climatic environmental factors such as desertification
(Tacoli 2009). The response to the same type of climatic
driver can therefore vary considerably according to local
context (Findlay 2011). Sub-Saharan Africa is expected to
be particularly affected by migration associated with cli-
mate change-related drivers, including sea-level rise and
declining or disrupted availability of resources due to shifts
in climatic conditions or extreme weather events (Gemenne
The majority of migration in response to environmental
change worldwide occurs within country borders (Tacoli
2009), and much migration is from rural to urban areas.
This trend may be exacerbated by the impacts of climate
change as they place growing pressure on rural livelihoods
(Adamo 2010). Africa’s rate of urbanization, already the
highest in the world, is expected to increase further, with as
much as half the population expected to live in urban areas
by 2030 (UN-HABITAT 2010). Patterns of urbanization in
Senegal, for example, have been attributed to desertifica-
tion and drought, which have made nomadic pastoral
livelihoods less feasible and less profitable (Hein et al.
While migration in general can be seen in many cases as
an adaptive response to local environmental pressures
(Tacoli 2009; Warner 2010; Collier et al. 2008), it can
bring with it a whole set of other risks—not only for the
migrants but also for the population already residing at
their site of relocation. Repercussions can arise from ten-
sions between ethnic groups, political and legal restric-
tions, and competition for and limitations on access to land
O. Serdeczny et al.
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(Tacoli 2009). In general, levels of poverty and unem-
ployment are often high among migrants, particularly
among unskilled subsistence farmers who have moved to
urban areas (Tacoli 2009). Population movements also
have health implications. For example, the spread of
malaria into the East African highlands mentioned above is
associated with the migration of people from the lowlands
to the highlands (Chaves and Koenraadt 2010). Further
costs and trade-offs that can result from migration, and in
particular forced displacement, include loss of social ties,
loss of sense of place and of cultural identity (Barnett and
O’Neill 2012).
Conditions in the new place of residence can place
people at risk of different environmental risks to those they
may have left behind, especially when migrants come to
reside in precarious conditions. Many informal settlements
worldwide are constructed on steep, unstable hillsides,
along the foreshores of former mangrove swamps or tidal
flats, or in low-lying flood plains (Douglas et al. 2008).
Where adequate sanitation and water drainage infrastruc-
ture are lacking, residents must depend on water supplies
that can easily become contaminated (Douglas et al. 2008).
These and other health risks are often particularly acute in
densely populated urban areas. Heat extremes, for example,
are felt more in cities due to the urban heat island effect
(UN-HABITAT 2010). Further the urban poor are among
the most vulnerable to food production shocks that cause
jumps in food prices (Ahmed et al. 2009; Hertel et al.
The connection between environmental factors and conflict
is contested. Gleditsch (2012) summarizes a suite of recent
studies on the relationship between violent conflict and
climate change and stresses that there is to date a lack of
evidence for such a connection. Other meta-analyses by
Hsiang et al. (2013) and Hendrix and Salehyan (2012)
suggest that deviation from normal precipitation and mild
temperatures increases the risk of conflict. In Africa,
(Hsiang and Meng 2014) have investigated and reproduced
the disputed finding of (Burke et al. 2009) that the likeli-
hood of civil war is greater in hotter years. The most recent
assessment report of the IPCC is the first to posit an indi-
rect causal connection between poverty and economic
shocks amplified by climate change and intra-state violence
(IPCC 2014).
These analyses add support to the long-standing claim
that, on both long and short timescales, depletion of a
dwindling supply of, as well as uneven access to, resources
has the potential to lead to competition between different
groups and heighten the threat of conflict (Hendrix and
Glaser 2007). The causal connection also operates in the
opposite direction, with conflict often leading to environ-
mental degradation and increasing the vulnerability of
populations to a range of climate-generated stressors
(Biggs et al. 2004; IPCC 2014). The breakdown of gov-
ernance due to civil war can also exacerbate poverty and
cause ecosystem conservation arrangements to collapse;
both of these factors can potentially cause further
exploitation of natural resources (Mitchell 2013).
It is clear that how these dynamics play out is complex
and not uniform, with the environment figuring as only one
of several interrelated drivers of conflict (Kolmannskog,
2010). However, given that unprecedented climatic con-
ditions (Fig. 1) are expected to place severe stress on the
availability and distribution of resources, the potential for
climate-related violent conflict constitutes a real risk in
some circumstances (Barnett and Adger 2007).
Development repercussions
The climatic and sectoral impacts outlined above can
combine to further produce complex and not easily pre-
dicted consequences for various aspects of human devel-
opment. Figure 5integrates projected physical and sectoral
impacts across different warming levels.
Any sectoral assessment falls short of providing a com-
prehensive picture of climate impacts under different
warming levels as potential interactions between impacts
across sectors are rarely represented. Slow-onset impacts in
different sectors may interact and thereby change the overall
toll of climate damages. Elliott et al. (2014), for example, find
irrigation adaptation limits for agriculture in southern Sub-
Saharan Africa due to climate-induced constraints in fresh-
water availability. Human responses to changes in one sector
can also bring about impacts in other sectors. Expansion of
agricultural areas to compensate for crop yield declines, for
example, can come at the cost of terrestrial carbon sinks and
other ecosystem services (Frieler et al. 2015).
Extreme weather events in particular can cause simul-
taneous damage across sectors, exacerbating the overall
effect. From the list of impacts described for Sub-Saharan
Africa in this paper, for example extreme events, such as
flooding events which are expected to increase, for exam-
ple, for the Upper Blue Nile River basin, can trigger out-
breaks of disease to which people are likely to be more
vulnerable under conditions of existing food insecurity. At
the same time, tropical cyclones and flooding events can
cause severe damage to critical infrastructure, including
transport, tourism and healthcare infrastructure. This can
be particularly serious if precisely those institutions that are
designed to cope with impacts, such as healthcare infras-
tructure, are themselves placed under additional pressure
due to extreme weather events.
Climate change impacts in Sub-Saharan Africa: from physical changes to their social
Author's personal copy
While these examples illustrate how complicated and
at times speculate the link of human and biophysical
impacts is, some human impacts are more easily traced to
the physical and sectoral climate signal. For example,
while food security is determined by a number of factors,
child malnutrition and stunting have been observed to
correlate with periods of inadequate local agricultural
yields (Black et al. 2008; Lloyd et al. 2011; UNDP 2007).
Other human impacts are more indirectly associated with
the effects of climate change. Food security is potentially
undermined where food price increases following harvest
loss—whether in regions neighboring or distant—dispro-
portionately affect the urban poor (Ahmed et al. 2009;
Hertel et al. 2010). Here too a cross-sectoral perspective is
required. In certain regions, for example West Africa,
projected agricultural yield declines need to be seen in
concert with potential decreases in protein intake due to
declining fish catch potential.Theadverseeffectsofa
projected decrease in fish catchpotentialbyupto50%on
regional protein intake amount to decreases of 7.6 % for
Ghana and 7.0 % for Sierra Leone compared to the
amount of protein consumed in 2000 (Lam et al. 2012).
The job loss associated with projected declines in catches
is estimated at almost 50 % compared to the year 2000
(Lam et al. 2012).
It is beyond the scope of this paper to map out the
differential vulnerability of different population groups to
climatic impacts or to do justice to the rich literature on
multi-dimensional poverty and its effects on vulnerability.
However, it becomes clear that a number of factors are
affected by climate change that co-determine the level of
development: Human health is negatively affected;
employment opportunities may dwindle; critical infras-
tructure is damaged, and tourism revenues are threatened.
Often the poor are disproportionately exposed to physical
impacts, such as storm surges or more indirect effects such
as food price increases.
This paper shows that climatic changes and sectoral climate
impacts need to be expected to affect the population of Sub-
Saharan Africa in a variety of ways. Changes are not uni-
form across the region. East Africa is at higher risk of
flooding and concurrent health impacts and infrastructure
damages. West Africa is projected to experience severe
impacts on food production, including through declines in
oceanic productivity, with severe risks for food security and
negative repercussions for human health and employment.
South Africa sees the strongest decrease in precipitation with
concurrent risks of drought. Sea-level rise puts at risk a
growing number of densely populated coastal cities, whose
population is set to increase and may receive yet more in-
Fig. 5 Climatic changes and impacts across sectors at different levels
of warming. Transient warming for heat extremes and precipitation is
based on RCP8.5 where impacts in the periods 2009–2039;
2023–2053; 2044–2074 and 2064–2094 are grouped under 1.5, 2, 3
and 4 C above pre-industrial levels, respectively. Where no refer-
ences are given, results are based on original data analysis as
presented in Schellnhuber et al. (2013), particularly Appendices
A.1–3). (a) Aich et al. (2014b); (b) Gerten et al. (2011); (c) Higgins
and Scheiter (2012); (d) Schlenker and Lobell (2010); (e) Thornton
et al. (2011); (f) Rosenzweig et al. (2014); (g) Cheung et al. (2010);
(h) Caminade et al. (2014)
O. Serdeczny et al.
Author's personal copy
migration as a result of rural livelihood degradation. The
potential interactions and amplifying effects across sectors
are not yet reflected in the science. Integrating impacts
across sectors and population dynamics remains a major
challenge for science and—due to the resulting uncertain-
ties—to adaptation planning and decision making alike.
Acknowledgments We thank the entire author team of the Turn
Down the Heat report series. We are also grateful for the tireless
comments provided to us by the World Bank’s regional offices, in
particular Kanta Kumari Rigaud. Further thanks go to Rosina Bier-
baum and Erick Fernandes who immensely helped in the publication
of the reports, effectively providing a basis for this article.
Adamo SB (2010) Environmental migration and cities in the context
of global environmental change. Curr Opin Environ Sustain
2(3):161–165. doi:10.1016/j.cosust.2010.06.005
Ahmed SA, Diffenbaugh NS, Hertel TW (2009) Climate volatility
deepens poverty vulnerability in developing countries. Environ
Res Lett 4(3):034004. doi:10.1088/1748-9326/4/3/034004
Aich V, Kone
´B, Hattermann F, Mu
¨ller EN (2014a) Floods in the
Niger Basin—analysis and attribution. Nat Hazards Earth Syst
Sci Discuss 2:5171–5212. doi:10.5194/nhessd-2-5171-2014
Aich V, Liersch S, Vetter T, Huang S, Tecklenburg J, Hoffmann P,
Koch H, Fournet S, Krysanova V, Mu
¨ller EN, Hattermann FF
(2014b) Comparing impacts of climate change on streamflow in
four large African river basins. Hydrol Earth Syst Sci
18:1305–1321. doi:10.5194/hess-18-1305-2014
Allen CA, Macalady AK, Chenchouni H, Bachelet D, McDowell N,
Vennetier M, Kitzberger T, Rigling A, Breshears DD, Hogg EH,
Gonzalez P, Fensham R, Zhang Z, Castro J, Demidova N, Lim
J-H, Allard G, Running SW, Semerci A, Cobb N (2010) A global
overview of drought and heat-induced tree mortality reveals
emerging climate change risks for forests. For Ecol Manag
259:660–684. doi:10.1016/j.foreco.2009.09.001
Amogu O, Descroix L, Ye
´ro KS, Le Breton E, Mamadou I, Ali A,
Vischel T, Bader J-C, Moussa IB, Gautier E, Boubkraoui S,
Belleudy P (2010) Increasing river flows in the Sahel? Water
2:170–199. doi:10.3390/w2020170,
4441/2/2/170. Accessed 11 Nov 2013
Arnell NW, van Vuuren DP, Isaac M (2011) The implications of
climate policy for the impacts of climate change on global water
resources. Glob Environ Change 21(2):592–603. doi:10.1016/j.
Asseng S, Foster I, Turner NC (2011) The impact of temperature
variability on wheat yields. Glob Change Biol 17(2):997–1012.
Azongo DK, Awine T, Wak G, Binka FN, Oduro AR (2012) A time-
series analysis of weather variability and all-cause mortality in
the Kasena-Nankana Districts of Northern Ghana, 1995–2010.
Glob Health Action. doi:10.3402/gha.v5i0.19073
Badjeck MC, Allison EH, Halls AS, Dulvy NK (2010) Impacts of
climate variability and change on fishery-based livelihoods.
Marine Policy 34:375–383. doi:10.1016/j.marpol.2009.08.007
Barnett J, Adger WN (2007) Climate change, human security and
violent conflict. Polit Geogr 26:639–655. doi:10.1016/j.polgeo.
Barnett J, O’Neill S (2012) Islands, resettlement and adaptation. Nat
Clim Change 2:8–10. doi:10.1038/nclimate1334
Barrios S, Ouattara B, Strobl E (2008) The impact of climatic change
on agricultural production: is it different for Africa? Food Policy
33:287–298. doi:10.1016/j.foodpol.2008.01.003
Beck L, Bernauer T (2011) How will combined changes in water
demand and climate affect water availability in the Zambezi
river basin? Glob Environ Change 21(3):1061–1072. doi:10.
Biggs R, Bohensky E, Desanker PV, Fabricius C, Lynam T,
Misselhorn AA, Musvoto C, Mutale M, Reyers B, Scholes RJ,
Shikongo S, van Jaarsveld AS (2004) Nature supporting people:
Southern African millennium ecosystem assessment. Integrated
report. Council for Scientific and Industrial Research, Pretoria
Birkmann J, Cardona OD, Carreno ML, Barbat AH, Pelling M,
Schneiderbauer S, Kienberger S, Keiler M, Alexander D, Zeil P,
Welle T (2013) Framing vulnerability, risk and societal
responses: the MOVE framework. Nat Hazards 67:193–211.
Black RE, Allen LH, Bhutta ZA, Caulfied LE, De Onis M, Ezzati M,
Mathers C et al (2008) Maternal and child undernutrition: global
and regional exposures and health consequences. Lancet
371:243–260. doi:10.1016/S0140-6736(07)61690-0
Bond WJ, Parr CL (2010) Beyond the forest edge: ecology, diversity
and conservation of the grassy biomes. Biol Conserv
143(10):2395–2404. doi:10.1016/j.biocon.2009.12.012
Brecht H, Dasgupta S, Laplante B, Murray S, Wheeler D (2012) Sea-
level rise and storm surges: high stakes for a small number of
developing countries. J Environ Dev 21(1):120–138. doi:10.
Buitenwerf R, Bond WJ, Stevens N, Trollope WSW (2012) Increased
tree densities in South African savannas: [50 years of data
suggests CO
as a driver. Glob Change Biol 18(2):675–684.
Burke MB, Miguel E, Satyaneth S, Dykema JA, Lobell DB (2009)
Warming increases the risk of civil war in Africa. Proc Natl
Acad Sci 106(49):20670–20674. doi:10.1073/pnas.0907998106
Caminade C, Ndione JA, Kebe CMF, Jones AE, Danuor S, Tay S,
Tourre YM, Lacaux JP, Vignolles C, Duchemin JB, Jeanne I,
Morse AP (2011) Mapping Rift Valley fever and malaria risk
over West Africa using climatic indicators. Atmos Sci Lett
12:96–103. doi:10.1002/asl.296
Caminade C, Kovats S, Rocklov J, Tompkins AM, Morse AP, Colo
´lez FJ, Stenlund H, Martens P, Lloyd SJ (2014) Impact of
climate change on global malaria distribution. Proc Natl Acad
Sci USA 111(9):3286–3291. doi:10.1073/pnas.1302089111
Chaves LF, Koenraadt CJM (2010) Climate change and highland
malaria: fresh air for a hot debate. Q Rev Biol 85(1):27–55.
Cheung WWL, Lam VWY, Sarmiento JL, Kearney K, Watson R,
Zeller D, Pauly D (2010) Large-scale redistribution of maximum
fisheries catch potential in the global ocean under climate
change. Glob Change Biol 16(1):24–35. doi:10.1111/j.1365-
Cohen MJ, Tirado C, Aberman N-L, Thompson B (2008) Impact of
climate change and bioenergy on nutrition. FAO and IFPRI,
Collier P, Conway G, Venables T (2008) Climate change and Africa.
Oxf Rev Econ Policy 24(2):337–353. doi:10.1093/oxrep/grn019
Collins M, Knutti RM, Arblaster J, Dufresne JL, Fichefet T,
Friedlingstein P, Gao X, Gutowski WJ, Johns T, Krinner G,
Shongwe M, Tebaldi C, Weaver AJ and Wehner M (2013) Long-
term climate change: projections, commitments and irreversibil-
ity. In: Stocker TF, Qin D, Plattner GK, Tignor M, Allen SK,
Boschung J, Nauels A, Xia Y, Bex V, Midgley PM (eds) Climate
change 2013: the physical science basis. Contribution of
Working Group I to the Fifth Assessment Report of the
Climate change impacts in Sub-Saharan Africa: from physical changes to their social
Author's personal copy
Intergovernmental Panel on Climate Change. Cambridge
University Press, Cambridge, UK, New York, NY, USA
Coumou D, Robinson A (2013) Historic and future increase in the
global land area affected by monthly heat extremes. Environ Res
Lett 8(3):034018. doi:10.1088/1748-9326/8/3/034018
Dasgupta S, Laplante B, Murray S, Wheeler D (2011) Exposure of
developing countries to sea-level rise and storm surges. Clim
Change 106:567–579. doi:10.1007/s10584-019-9959-6
Dell M, Jones BF (2012) Temperature shocks and economic growth:
evidence from the last half century. Am Econ J Macroecon
4(3):66–95. doi:10.1257/mac.4.3.66
Descroix L, Mahe
´G, Lebel T, Favreau G, Galle S, Gautier E, Olivry JC,
Albergel J, Amogu O, Cappelaere B, Dessouassi R, Diedhiou A,
Le Breton E, Mamadou I, Sighomnou D (2009) Spatio-temporal
variability of hydrological regimes around the boundaries between
Sahelian and Sudanian areas of West Africa: a synthesis. J Hydrol
375:90–102. doi:10.1016/j.jhydrol.2008.12.012
Djoudi H, Brockhaus M, Locatelli B (2011) Once there was a lake:
vulnerability to environmental changes in northern Mali. Reg
Environ Change 13(3):493–508. doi:10.1007/s10113-011-0262-5
¨ll P (2009) Vulnerability to the impact of climate change on
renewable groundwater resources: a global-scale assessment.
Environ Res Lett 4(3):35006. doi:10.1088/1748-9326/4/3/035006
Dougill AJ, Fraser EDG, Mark S (2010) Anticipating vulnerability to
climate change in dryland pastoral systems: using dynamic
systems models for the Kalahari. Centre for Climate Change
Economics and Policy, Working paper no. 32, pp 1–28
Douglas I, Alam K, Maghenda M, Mcdonnell Y, Mclean L, Campbell
J (2008) Unjust waters: climate change, flooding and the urban
poor in Africa. Enviro Urban 20(1):187–205. doi:10.1177/
Drinkwater K, Beaugrand G, Kaeriyama M, Kim S, Ottersen G, Perry
RI, Po
¨rtner H-O, Polovina JJ, Takasuka A (2010) On the
processes linking climate to ecosystem changes. J Mar Syst
79:374–388. doi:10.1016/j.jmarsys.2008.12.014
Egondi T, Kyobutangi C, Kovats S, Muindi K, Ettarh R, Rocklov J
(2012) Time-series analysis of weather and mortality patters in
Nairobi’s informal settlements. Glob Health Action
5(19065):23–32. doi:10.3402/gha.v5i0.19065
Elliott J, Deryng D, Mu
¨ller C et al (2014) Constraints and potentials
of future irrigation water availability on agricultural production
under climate change. Proc Natl Acad Sci US A
111(9):3239–3244. doi:10.1073/pnas.1222474110
FAO, Ifad and WFP (2014) The state of food insecurity in the world:
strengthening the enabling environment for food security and
nutrition. FAO, Rome
Faures J-M, Santini G (2008) Water and the rural poor: interventions
for improving livelihoods in Sub-Saharan Africa. FAO, Rome
Findlay AM (2011) Migrant destinations in an era of environmental
change. Glob Environ Change 21S:S50–S58. doi:10.1016/j.
Frieler K, Levermann A, Elliott J et al (2015) A framework for the
cross-sectoral integration of multi-model impact projections:
land use decisions under climate impacts uncertainties. Earth
Syst Dyn 6(2):447–460. doi:10.5194/esd-6-447-2015
Fung F, Lopez A, New M (2011) Water availability in ?2C and
?4C worlds. Philos Transact Ser A Math Phys Eng Sci
369(1934):99–116. doi:10.1098/rsta.2010.0293
Gemenne F (2011) Why the numbers don’t add up: a review of
estimates and predictions of people displaced by environmental
changes. Glob Environ Change 21(S1):S41–S49. doi:10.1016/j.
Gerten D, Heinke J, Hoff H, Biemans H, Fader M, Waha K (2011)
Global water availability and requirements for future food
production. J Hydrometeorol 12(5):885–899. doi:10.1175/
Gleditsch NP (2012) Whither the weather? Climate change and
conflict. J Peace Res 49(1):3–9. doi:10.1177/0022343311431288
Gonzalez P, Tucker CJ, Sy H (2012) Tree density and species decline
in the African Sahel attributable to climate. J Arid Environ
78:55–64. doi:10.1016/j.jaridenv.2011.11.001
Hallegatte S, Green C, Nicholls RJ, Corfee-Morlot J (2013) Future
flood losses in major coastal cities. Nat Clim Change. doi:10.
Hein L, Metzger MJ, Leemans R (2009) The local impacts of climate
change in the Ferlo, Western Sahel. Clim Change 93:465–483.
Hempel S, Frieler K, Warszawski L, Schewe J, Piontek F (2013) A
trend-preserving bias correction—the ISI-MIP approach. Earth
Syst Dyn 4:219–236. doi:10.5194/esd-4-219-2013
Hendrix CS, Glaser SM (2007) Trends and triggers: climate, climate
change and civil conflict in Sub-Saharan Africa. Polit Geogr
26:695–715. doi:10.1016/j.polgeo.2007.06.006
Hendrix CS, Salehyan I (2012) Climate change, rainfall, and social
conflict in Africa. J Peace Res 49(1):35–50. doi:10.1177/
Hertel TW, Burke MB, Lobell DB (2010) The poverty implications of
climate-induced crop yield changes by 2030. Glob Environ
Change 20(4):577–585. doi:10.1016/j.gloenvcha.2010.07.001
Higgins SI, Scheiter S (2012) Atmospheric CO2 forces abrupt
vegetation shifts locally, but not globally. Nature 488(7410):
209–212. doi:10.1038/nature11238
Hinkel J, Brown S, Exner L, Nicholls RJ, Vafeidis AT, Kebede AS
(2011) Sea-level rise impacts on Africa and the effects of
mitigation and adaptation: an application of DIVA. Reg Environ
Change 12(1):207–224. doi:10.1007/s10113-011-0249-2
Hope KRS (2009) Climate change and poverty in Africa. Int J Sustain
Dev World Ecol 16(6):451–461. doi:10.1080/1354500903354424
Hsiang SM, Meng KC (2014) Reconciling disagreement over climate-
conflict results in Africa. PNAS 111(6):2100–2103. doi:10.1073/
Hsiang SM, Burke M, Miguel E (2013) Quantifying the influence of
climate on human conflict. Science. doi:10.1126/science.1235367
Hulme M (2002) Rainfall changes in Africa: 1931–1960 to 1961–1990.
Int J Climatol 12:685–699. doi:10.1002/joc.3370120703
Hulme M, Doherty R, Ngara T, New M, Lister D (2001) African
climate change: 1900–2100. Clim Res 17:145–168. doi:10.3354/
IPCC (2014) Summary for policymakers. 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 Intergovermental Panel on Climate
Change [Field CB, Barros VR, Dokken DJ, Mach KJ, Mastran-
drea MD, Bilir TE, Chatterjee M, Ebi YL, Estrada YO, Genova
RC, Girma B, Kissel ES, Levy AN, MacCracken S, Mastrandrea
PR, White LL (eds)]. Cambridge University Press, Cambridge,
UK and New York, USA. pp 1–32
Janowiak JE (1988) An investigation of interannual rainfall variabil-
ity in Africa. J Clim 1:240–255. doi:10.1175/1520-0442(1988)
Jones BF, Olken BA (2010) Climate shocks and exports. Am Econ
Rev 100(2):454–459. doi:10.1257/aer.100.2.454
Kebede AS, Nicholls RJ (2011) Exposure and vulnerability to climate
extremes: population and asset exposure to coastal flooding in
Dar es Salaam, Tanzania. Reg Environ Change 12(1):81–94.
Kebede AS, Nicholls RJ, Hanson S, Mokrech M (2012) Impacts of
climate change and sea-level rise: a preliminary case study of
Mombasa, Kenya. J Coastal Res 278:8–19. doi:10.2112/JCOAS
Kgope BS, Bond WJ, Midgley GF (2009) Growth responses of
African savanna trees implicate atmospheric [CO
] as a driver of
O. Serdeczny et al.
Author's personal copy
past and current changes in savanna tree cover. Austral Ecol
35(4):451–463. doi:10.1111/j.1442-9993.2009.02046.x
Kolmannskog V (2010) Climate change, human mobility, and
protection: initial evidence from Africa. Refug Surv Q
29(3):103–119. doi:10.1093/rsq/hdq033
Krysanova V, Mu
¨ller-Wohlfeil D-I, Becker A (1998) Development
and test of a spatially distributed hydrological/water quality
model for mesoscale watersheds. Ecol Model 106:261–289.
Lam VWY, Cheung WWL, Swartz W, Sumaila UR (2012) Climate
change impacts on fisheries in West Africa: implications for
economic, food and nutritional security. Afr J Mar Sci. doi:10.
Laprise R, Herna
´az L, Tete K et al (2013) Climate projections
over CORDEX Africa domain using the fifth-generation Canadian
Regional Climate Model (CRCM5). Clim Dyn 41:3219–3246.
Liu J, Fritz S, van Wesenbeeck CFA, Fuchs M, You L, Obersteiner
M, Yang H (2008) A spatially explicit assessment of current and
future hotspots of hunger in Sub-Saharan Africa in the context of
global change. Glob Planet Change 64:222–235. doi:10.1016/j.
Lloyd SJ, Kovats RS, Chalabi Z (2011) Climate change, crop yields,
and undernutrition: development of a model to quantify the
impact of climate scenarios on child undernutrition. Environ
Health Perspect. doi:10.1289/ehp.1003311
Lobell DB, Schlenker W, Costa-Roberts J (2011) Climate trends and
global crop production since 1980. Science 333(6042):616–620.
Luo Q (2011) Temperature thresholds and crop production: a review.
Clim Change. doi:10.1007/s10584-011-0028-6
Luque Ferna
´ndez MA, Bauernfeind A, Jime
´nez JD, Gil CL, El Omeiri
N, Guibert DH (2009) Influence of temperature and rainfall on
the evolution of cholera epidemics in Lusaka, Zambia,
2003–2006: analysis of a time series. Trans R Soc Trop Med
Hyg 103:137–143. doi:10.1016/j.trstmh.2008.07.017
MacDonald AM, Calow RC, MacDonald DMJ, Darling WG,
Dochartaigh B (2009) What impact will climate change have
on rural groundwater supplies in Africa? Hydrol Sci J
54(4):690–703. doi:10.1623/hysj.54.4.690
MacDonald AM, Bonsor HC, Dochartaigh B, Taylor RG (2012)
Quantitative maps of groundwater resources in Africa. Environ
Res Lett 7(2):24009. doi:10.1088/1748-9326/7/2/024009
Mahe G, Lienou G, Descroix L, Bamba F, Paturel JE, Laraque A,
Meddi M, Habaieb H, Adeaga O, Dieulin C, Kotti FC, Khomsi K
(2013) The rivers of Africa: witness of climate change and human
impact on the environment. Hydrol Process 27:2105–2114.
Masike S, Ulrich P (2008) Vulnerability of traditional beef sector to
drought and the challenges of climate change: The case of
Kgatleng District, Botswana. J Geogr Reg Plan 1(1):12–18.
McDonald RI, Green P, Balk D, Fekete BM, Revenga C, Todd M,
Montgomery M (2011) Urban growth, climate change, and
freshwater availability. Proc Natl Acad Sci USA 108(15):
6312–6317. doi:10.1073/pnas.1011615108
McMichael AJ, Lindgren E (2011) Climate change: present and future
risks to health, and necessary responses. J Intern Med
270(5):401–413. doi:10.1111/j.1365-2796.2011.02415.x
Midgley GF, Thuiller W (2011) Potential responses of terrestrial
biodiversity in Southern Africa to anthropogenic climate change.
Reg Environ Change 11(S1):127–135. doi:10.1007/s10113-010-
Mitchell SA (2013) The status of wetlands, threats and the predicted
effect of global climate change: the situation in Sub-Saharan
Africa. Aquat Sci 75:95–112. doi:10.1007/s00027-102-0259-2
Morton J (2012) Livestock and climate change: impacts and
adaptation. Agriculture for development. Tropical Agriculture
Association Report No 17:17–20
Mueller ND, Gerber JS, Johnston M, Ray DK, Ramankutty N, Foley JA
(2012) Closing yield gaps through nutrient and water management.
Nature 490(7419):254–257. doi:10.1038/nature11420
NASAC (2015) Climate change adaptation and resilience in Africa.
Recommendations to policymakers. Network of African Science
Ndebele-Murisa MR, Musil CF, Raitt L (2010) A review of
phytoplankton dynamics in tropical African lakes. S Afr J Sci
106(1/2):13–18. doi:10.4102/sajs.v106i1/2.64
Neuman J, Emanuel KA, Ravela S, Ludwig LC, Verly C (2013)
Assessing the risk of cyclone-induced storm surge and sea level
rise in Mozambique. WIDER Working Paper 2013/03. UNU-
World Institute for Development Economics Research, Helsinki
Niang I, Ruppel OC, Abdrabo MA, Essel A, Lennard C, Padgham J,
Urquhart P (2014) Africa. In: Climate change 2014: impacts,
adaptation and vulnerability. Contribution of Working Group II
to the Fifth Assessment Report of the Intergovernmental Panel
on Climate Change. Cambridge University Press, Cambridge
Patz JA, Olson SH, Uejo CK, Gibbs HK (2008) Disease emergence
from global climate and land use change. Med Clin North Am
92:1473–1491. doi:10.1016/j.mcna.2008.07.007
¨rtner H-O (2010) Oxygen- and capacity-limitation of thermal
tolerance: a matrix for integrating climate-related stressor effects
in marine ecosystems. J Exp Biol 213(6):881–893. doi:10.1242/
¨rtner H-O, Karl DM, Boyd PW, Cheung WWL, Lluch-Cota SE,
Nojiri Y, Schmidt DN, Zavialov PO (2014) Ocean systems. In:
Climate change 2014: Impacts, adaptation, and vulnerability.
Part A: global and sectoral impacts. Contribution of Working
Group II to the Fifth Assessment Report of the Intergovernmen-
tal Panel on Climate Change. Cambridge University Press,
Cambridge, U.K., and New York, U.S
Reyburn R, Kim DR, Emch M, Khatib A, von Seidlein L, Ali M
(2011) Climate variability and the outbreaks of cholera in
Zanzibar, East Africa: a time series analysis. Am J Trop Med
Hyg 84(6):862–869. doi:10.4269/ajtmh.2011.10-0277
¨m J, Falkenmark M, Karlberg L, Hoff H, Rost S, Gerten D
(2009) Future water availability for global food production: the
potential of green water for increasing resilience to global
change. Water Resour Res 45(W00A12):1–16. doi:10.1029/
Rosenzweig C, Elliott J, Deryng D et al (2014) Assessing agricultural
risks of climate change in the 21st century in a global gridded
crop model intercomparison. Proc Natl Acad Sci USA 14:1–6.
¨tter RP, Carter TR, Olesen JE, Porter JR (2011) Crop–climate
models need an overhaul. Nat Clim Change 1(4):175–177.
Roudier P, Sultan B, Quirion P, Berg A (2011) The impact of future
climate change on West African crop yields: what does the
recent literature say? Glob Environ Change 21:1073–1083.
Sallu SM, Twyman C, Stringer LC (2010) Resilient or vulnerable
livelihoods? Assessing livelihood dynamics and trajectories in
rural Botswana. Ecol Soc 15(4). http://www.ecologyandsociety.
Schellnhuber HJ, Reyer C, Hare B, Waha K, Otto IM, Serdeczny O,
Schaeffer M, Schleußner C-F, Reckien D, Marcus R, Kit O,
Eden A, Adams S, Aich V, Albrecht T, Baarsch F, Boit A,
Canales Trujillo N, Cartsburg M, Coumou D, Fader M, Hoff H,
Jobbins G, Jones L, Krummenauer L, Langerwisch F, Le Masson
V, Ludi E, Mengel M, Mo
¨hring J, Mosello B, Norton A, Perette
M, Pereznieto P, Rammig A, Reinhardt J, Robinson A, Rocha M,
Climate change impacts in Sub-Saharan Africa: from physical changes to their social
Author's personal copy
Sakschewski B, Schaphoff S, Schewe J, Stagl J, Thonicke K
(2014) Turn down the heat: confronting the new climate normal.
The World Bank, Washington, DC
Schellnhuber H-J, Hare B, Serdeczny O, Schaeffer M, Adams S,
Baarsch F, Schwan S, Coumou D, Robinson A, Vieweg M,
Piontek F, Donner R, Runge J, Rehfeld K, Rogelj J, Perette M,
Menon A, Schleussner C-F, Bondeau A, Svirejeva-Hopkins A,
Schewe J, Frieler K, Warszawski L, Rocha M (2013) Turn down
the heat: Climate extremes, regional impacts and the case for
resilience. World Bank, Washington, DC
Schewe J, Heinke J, Gerten D, Haddeland I, Arnell NW, Clark DB,
Dankers R (2013) Multi-model assessment of water scarcity
under global warming. Proc Natl Acad Sci USA I(1):1–13.
Schlenker W, Lobell DB (2010) Robust negative impacts of climate
change on African agriculture. Environ Res Lett 5(1):014010.
Schlenker W, Roberts MJ (2009) Nonlinear temperature effects
indicate severe damages to U.S. crop yields under climate
change. Proc Natl Acad Sci 106(37):15594–15598. doi:10.1073/
Seo SN, Mendelsohn R (2007) Climate change impacts on animal
husbandry in Africa: a Ricardian analysis. World Bank Policy
Research Working Paper No. 4261. doi: 10.1596/1813-9450-4261
Sillmann J, Kharin VV, Zweiers FW, Zhang X, Bronaugh D (2013)
Climate extreme indices in the CMIP5 multi-model ensemble.
Part 2: future climate projections. J Geophys Res Atmos
118(6):1–55. doi:10.1002/jgrd.50188
Smith KR, Woodward A, Campbell-Lendrum D, Chadee DD, Honda
Y, Liu Q, Olwoch JM, Revich B, Sauerborn R (2014) Human
health: impacts, adaptation and co-benefits. In: Climate change
2014: Impacts, adaptation and vulnerability. Contribution of
Working Group II to the Fifth Assessment Report of the
Intergovernmental Panel on Climate Change. Cambridge
University Press, Cambridge, U.K., and New York, US
Star Africa (2013) Mozambique flood death toll at 113. http://en.
Stramma L, Johnson GC, Sprintall J, Mohrholz V (2008) Expanding
oxygen-minimum zones in the tropical oceans. Science
320(5876):655–658. doi:10.1126/science.1153847
Stramma L, Schmidtko S, Levin LA, Johnson GC (2010) Ocean
oxygen minima expansions and their biological impacts. Deep
Sea Res Part I 57(4):587–595. doi:10.1016/j.dsr.2010.01.005
Tacoli C (2009) Crisis or adaptation? Migration and climate change in
a context of high mobility. Environ Urban 21:513–525. doi:10.
Taye MT, Ntegeka V, Ogiramoi NP, Willems P (2011) Assessment of
climate change impact on hydrological extremes in two source
regions of the Nile River Basin. Hydrol Earth Syst Sci
15:209–222. doi:10.5194/hess-15-209-2011
Taylor RG, Scanlon B, Do
¨ll P, Rodell M, van Beek R, Wada Y,
Longuevergne L, Leblanc M, Famiglietti JS, Edmunds M,
Konikow L, Green TR, Chen J, Taniguchi M, Bierkens MFP
(2012) Ground water and climate change. Nat Clim Change
3:322–329. doi:10.1038/nclimate1744
Thornton PK, van de Steeg J, Notenbaert A, Herrero M (2009) The
impacts of climate change on livestock and livestock systems in
developing countries: a review of what we know and what we
need to know. Agric Syst 101:113–127. doi:10.1016/j.agsy.2009.
Thornton PK, Jones PG, Ericksen PJ, Challinor AJ (2011) Agriculture
and food systems in sub-Saharan Africa in a 4 C?world. Philos
Trans A Math Phys Eng Sci 369:117–136. doi:10.1098/rsta.
Tschakert P (2007) Views from the vulnerable: understanding
climatic and other stressors in the Sahel. Glob Environ Change
17:381–396. doi:10.1016/j.gloenvcha.2006.11.008
UN Department of Economic and Social Affairs (2013) World
population prospects: The 2012 revision. Volume I: comprehen-
sive tables. New York, USA
UNDP (United Nations Development Programme) (2007) Human
Development Report 2007: Fighting Climate Change: Human
solidarity in a divided world
UNEP (United Nations Environment Programme) (1997) World atlas
of desertification 2ED. UNEP, London
UN-HABITAT (2010) The state of African cities 2010: governance,
inequalities and urban land markets. UN-HABITAT, Nairobi,
pp 1–280
UNICEF Mozambique (2013) Flood emergency preparedness and
response. Situation report. Reporting period: February 6–7, 2013
United Nations Children
´s Fund, World Health Organization and The
World Bank (2012) UNICEF-WHO-World Bank Joint Child
Malnutrition Estimates. UNICEF, New York; WHO, Geneva,
The World Bank, Washington DC
Vizy EK, Cook KH (2012) Mid-twenty-first-century changes in
extreme events over northern and tropical Africa. J Clim
25:5748–5767. doi:10.1175/JCLI-D-11-00693.1
Waha K, Mu
¨ller C, Bondeau A, Dietrich JP, Kurukulasuriya P,
Heinke J, Lotze-Campen H (2012) Adaptation to climate change
through the choice of cropping system and sowing date in sub-
Saharan Africa. Glob Environ Change 23(1):130–143. doi:10.
Ward D (2005) Do we understand the causes of bush encroachment in
African savannas? Afr J Range Forage Sci 22:101–105. doi:10.
Warner K (2010) Global environmental change and migration:
governance challenges. Glob Environ Change 20(3):402–413.
Warszawski L, Frieler K, Huber V, Piontek F, Serdeczny O, Schewe J
(2013) The Inter-Sectoral Impact Model Intercomparison Project
(ISI-MIP): project framework. Proc Natl Acad Sci USA
111:3228–3232. doi:10.1073/pnas.1312330110
WHO (2009) Protecting health from climate change: connecting
science, policy and people. World Health Organization, Geneva,
pp 1–36
Wigley BJ, Bond WJ, Hoffman MT (2010) Thicket expansion in a
South African savanna under divergent land use: local vs. global
drivers? Glob Change Biol 16(3):964–976. doi:10.1111/j.1365-
World Bank (2004) Kenya—towards a water-secure Kenya: water
resources sector memorandum. Report No. 28398-KE. World
Bank, Washington, DC
World Bank (2013) Fact sheet: The World Bank and agriculture in
Africa. Accessed 13
Jan 2015
World Bank (2015a) Rainfed agriculture. http://water.worldbank.
Accessed 13 January 2015
World Bank (2015b) Regional dashboard: poverty and equity,
Sub-Saharan Africa.
region/SSA. Accessed 13 Jan 2015
World Bank Group (2010) World development report 2010: devel-
opment and climate change. World Bank Group, Washington,
DC, pp 1–439
Zomer RJ, Trabucco A, Da Bossio, Verchot LV (2008) Climate change
mitigation: a spatial analysis of global land suitability for clean
development mechanism afforestation and reforestation. Agric
Ecosyst Environ 126(1–2):67–80. doi:10.1016/j.agee.2008.01.014
O. Serdeczny et al.
Author's personal copy

Supplementary resource (1)

... Numerous impacts of climate change on agro-ecological zones in SSA have been reported in many scientific studies. Such impacts include reductions in crop yields, quality of crops (Cohn et al., 2016, Mpakairi and Muvengwi, 2019, Apraku et al., 2021, and the drying up of some streams and rivers (Payne et al., 2020, Jin et al., 2021, increases in urban temperature (Ayanlade, 2016, Ayanlade, 2017, Mpakairi and Muvengwi, 2019, Payne et al., 2020 and heat fluxes Howard, 2019, Adhikari et al., 2015), loss of pastureland Ojebisi, 2020, Thornton andHerrero, 2015); loss of vegetation and biodiversity, and destruction of wildlife ecosystems (Abrams et al., 2018, Mpakairi et al., 2020; decreasing household incomes of farmers (Ayanlade et al., 2018a), and other societal impacts (Serdeczny et al., 2017). Agro-ecological zones in SSA are mainly determined by climatic elements that differ from one ecological system to the next. ...
... Moreover, the latest Intergovernmental Panel on Climate Change (IPCC) report further stated, with high levels of confidence, that extreme weather events resulting from climate change are likely to have negative impacts on yields of major cereal crops in the SSA region (IPCC, 2021). As agricultural livelihoods in the SSA region become riskier due to extreme events, the rate of rural-urban migration may be expected to grow, adding to the already significant urbanization trend in the region (Serdeczny et al., 2017). This is because extreme events affect the rainfed agricultural systems on which the livelihoods of a large proportion of the region's population currently depend (Araro et al., 2020, Kogo et al., 2021. ...
... Indirect impacts on people's mobility due to climate change are likely to amplify the overall impacts across sectors, and there is little understanding of how severe such impacts may be in the future (Adger et al., 2015). These scientific pieces of evidence suggest that climate change has not only led to shifts in average climatic conditions but also to much more frequent extreme weather events, which pose threats to agricultural production in the SSA, as well as to urban settlements (Serdeczny et al., 2017, Stuch et al., 2021, Mulungu and Ng'ombe, 2019. Managing the multiple risks of extreme climatic events and disasters in different agro-ecological zones ought to be a research priority in SSA regions, because rural farmers already facing hunger and food insecurity (Mbatha et al., 2021) will be at even greater risk. ...
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This study seeks to provide a critical overview of the existing evidence on extreme climate events and the adaptation options of the affected population in order to help scholars navigate the field. The study examined the recent extreme climate events that occurred in Sub-Saharan Africa (SSA), the climate change adaptation options mentioned in the literature, and the need for international technological transfer in SSA. 181 peer-reviewed publications were evaluated on the following topics: 1) the impacts of climate extremes in SSA; 2) the adaptation options discussed in the literature for the region; 3) the analysis of the needs and the gaps of the international technology transfer in SSA, and 4) the various impact areas of the technology transfer on the adaptive capacity in SSA. The major finding from this study is that the impacts of climate change have been observed in the region, with many extreme events leading to reductions in crop yield qualities and quantities, with much greater impacts on the smallholder farmers' livelihoods in SSA countries. Based on these findings climate change conceptual framework is proposed which summarises the observed impacts of climate change on agriculture and food systems in SSA countries. The study concluded that there are new adaptation options that SSA countries can adopt from developed countries, and that much greater agricultural technological transfer is needed to facilitate better adaptation to climate change in SSA.
... The African continent is amongst the most affected by climate change and environmental degradation and is most vulnerable to their further progression. Climate change projections for Sub-Saharan and Southern Africa show a clear warming trend in inland subtropics, alongside a higher frequency of extreme heat events, increasing aridity, precipitation changes, sea-level rise, and extensive biodiversity loss [4][5][6][7][8]. ...
... Though knowledge about the precise pathways by which environmental change affects health needs further refinement [11], it is evident that it has a variety of significant, adverse social and health impacts. Amongst other issues, climate change, biodiversity loss, deforestation, desertification, droughts, reducing water quality and resources, and land degradation are increasing the prevalence of malaria and other food-, water-, and vector-borne diseases in areas where they have previously not been present; driving soil impoverishment and reduced agricultural output that will further challenge food insecurity and undernutrition; increasing migration, urban poverty and environmental injustice that comes with rapid urbanization in the region; threatening child development and increasing susceptibility to diseases; driving extreme weather event-related fatalities and injuries; and increasing the likelihood of heat stress, heat stroke and death due to prolonged exposure to high temperatures [5][6][7][8][12][13][14][15][16][17]. ...
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Climate change, biodiversity loss and large-scale environmental degradation are widely recognized as the biggest health threats of the 21st century, with the African continent already amongst the most severely affected and vulnerable to their further progression. The healthcare sys-tem's contribution to climate change and environmental degradation requires healthcare professionals to address environmental issues urgently. However, the foundation for context-relevant interventions across research, practice, and education is not readily available. Therefore, we conducted a convergent mixed-methods study to investigate South African healthcare professionals' knowledge, attitudes, practices, and barriers to environmental sustainability. Healthcare professionals participated in a cross-sectional questionnaire (n = 100) and in-depth semi-structured focus group discussions (n = 18). Data were analyzed using descriptive statistics and thematic analysis, respectively, and integrated to provide holistic findings. Our results confirm overwhelmingly positive attitudes and a high degree of interest in education, implementation, and taking on more corresponding responsibility, but a lack of substantial knowledge of the subject matter, and only tentative implementation of practices. Identified barriers include a lack of knowledge, resources, and policies. Further research, education, and policy development on overcoming these barriers is required. This will facilitate harnessing the extant enthusiasm and advance environmental sustainability in South Africa's healthcare practice.
... It is influenced largely by tropical, subtropical and mid-latitude changes with most of its rainfall happening during the summer period (Landman et al., 2001). The area could also experience a sea-level rise of one meter by the end of the century (Serdeczny et al., 2016). Engelbrecht et al. (2015) report that temperatures within most of the Southern African countries are predicted to rise between 4 °C and 6 °C by the end of the current century, much higher than projected by the IPCC. ...
... However, this region will possibly be more vulnerable to the impacts of CC than any other region (Kula et al., 2013). Serdeczny et al. (2016) suggest that the consequences of CC will be felt in different ways in sub-Saharan Africa, both naturally and in human systems. According to Pereira (2017), sub-Saharan Southern and Northern Africa have seen temperature rises at a pace twice than that of the rest of the world, with the most extreme warming in Southern Africa, especially over the last two decades. ...
... Erratic rainfall has a large influence on agricultural productivity. Close to 70% of the population in the West African region depends mainly on rain-fed agriculture, thereby, making climate change a direct threat to progress toward several UN Sustainable Development Goals (SDGs), most notably goal 1 (No Hunger) (Serdeczny et al., 2017;Diedhiou et al., 2018). The climate change model used in West Africa predicted increases in temperatures of 1.5 to 2 0 C higher than global mean temperatures. ...
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Rainfall variability is a serious trend that is posing a lot of challenges to agricultural development in many countries across the world in recent times. The majority of these countries can be found in sub-Saharan Africa. These countries continue to suffer due to the fact that agricultural commodities are the mainstay of their economies. In this paper, efforts were made (i) to shed more light on the evidence of erratic rainfall and its impacts on agriculture production in West Africa; (ii) to discuss the possible causes of food insecurity (iii) and how to mitigate the challenges posed by erratic rainfall to agriculture in the sub-region. A narrative review method was used to analyze the literature. The application of a narrative perspective to review the literature enables a broad understanding of the topic. The results provided evidence of an erratic rainfall pattern in the sub-region, with particular reference to Ghana and its impact on food security. It also assessed the feasibility of adopting weather forecast-based advice, integrated soil fertility management practices, and irrigation schemes as farmer coping strategies for mitigating the impact of an erratic rainfall pattern on crop production in West Africa.
... The totaled implications of climatic upshot on livestock husbandry systems with and without adaptation are far less certain to imagine. Livestock is a critical risk management resource; livestock may be one of the few assets available to around 170 million impoverished households in rural parts of Sub-Saharan Africa [22]. Wherefore, Bertram [21] for example, predicted that the most severe effects of climate variations and climatic upshot could be evident in livestock husbandry practices and other systems especially in the least developed countries, where most people are already vulnerable. ...
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Climate change and extreme weather events have an impact on crop and livestock husbandry in developing countries, particularly in Sub-Saharan Africa. The direct effects posed by anthropogenic to changes in environmental conditions have been thoroughly proven in recent years through empirical studies. As a result, since 1960, the global average temperature has risen by 1 degree Celsius. In Ethiopia, climate change has had an impact on livestock production and productivity. The majority of livestock owners in the country believe climate change will influence pasture shortages, water shortages, livestock genetic resource losses, loss of livestock life, and less meat on mature livestock or reduced growth rate to achieve the required weight. Consequently, regarding mature animals, that leads to reduced livestock physiological processes, low milk supply, and impaired procreant function. Drought oxen will become malnourished and will be unable to generate the required draught power or energy for farm activities such as ox-cart, ploughing, causing crop cultivation to be hampered. Moreover, conferring to patterns and occurrences of rainfall have a significant impact on the present quantity of water and pasture for livestock. As a result, the absence of quality pasture for livestock and enough water roots livestock productivity and reproduction to suffer in Ethiopia. Higher temperatures caused by climate change may hasten the growth of diseases and parasites that may proliferate in or outside of the host livestock for too long. However, climate variation and climate change are anticipated to far reach more detrimental effects on livestock well-being and productivity, particularly in disadvantaged areas. Therefore, in these food and human livelihood are of essence for survival. The purpose of this study is to highlight the potential effects of changes in climate contribution to livestock production and productivity in Ethiopia.
... Studies have found that to make the most effective decisions for policy formulation on climate change adaptation and climate services, short-term and mid-term climate projections at a local scale are needed [14]. Climate change projections have so far been conducted at the regional scale in Southern Africa and SSA in particular, using general circulation models (GCMs) [15,16]. Studies have demonstrated that GCMs are capable of reproducing temperature distributions realistically. ...
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Among the projected effects of climate change, water resources are at the center of the matrix. Certainly, the southern African climate is changing, consequently, localized studies are needed to determine the magnitude of anticipated changes for effective adaptation. Utilizing historical observation data over the Olifants River Catchment, we examined trends in temperature and rainfall for the period 1976–2019. In addition, future climate change projections under the RCP 4.5 and RCP 8.5 scenarios for two time periods of 2036–2065 (near future) and 2066–2095 (far future) were analysed using an ensemble of eight regional climate model (RCA4) simulations of the CORDEX Africa initiative. A modified Mann-Kendall test was used to determine trends and the statistical significance of annual and seasonal rainfall and temperature. The characteristics of extreme dry conditions were assessed by computing the Standardized Precipitation Index (SPI). The results suggest that the catchment has witnessed an increase in temperatures and an overall decline in rainfall, although no significant changes have been detected in the distribution of rainfall over time. Furthermore, the surface temperature is expected to rise significantly, continuing a trend already evident in historical developments. The results further indicate that the minimum temperatures over the Catchment are getting warmer than the maximum temperatures. Seasonally, the minimum temperature warms more frequently in the summer season from December to February (DJF) and the spring season from September to November (SON) than in the winter season from June to August (JJA) and in the autumn season from March to May (MAM). The results of the SPI affirm the persistent drought conditions over the Catchment. In the context of the current global warming, this study provides an insight into the changing characteristics of temperatures and rainfall in a local context. The information in this study can provide policymakers with useful information to help them make informed decisions regarding the Olifants River Catchment and its resources.
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The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes COVID-19, emerged in late 2019, halfway through the preparation of the IPCC WGII Sixth Assessment Report. This Cross-Chapter Box assesses how the massive shock of the pandemic and response measures interact with climate-related impacts and risks as well as its significant implications for risk management and climate resilient development.
This article contributes to ongoing debates surrounding ‘child labour’ and education, by offering an alternative framework of analysis, which we apply to rural Sub-Saharan Africa (SSA). In contrast to the dominant Child’s Rights discourse of the ILO and Sustainable Development Goals, which largely place ‘child labour’ and education (in the narrow sense of schooling) in an oppositional relationship that prioritises schooling, we propose a more nuanced conceptual framework, which we term the “edu-workscape”. This framework aims to capture the complex, dynamic and context-specific nature of children’s working and educational lives. We apply the framework to explore ‘education’ and ‘work’ and, to a lesser extent, ‘harm’ and ‘hazardous work’, across three interwoven and overlapping social arenas: the household, school, and the workplace. This we do through a purposive critical literature review of largely qualitative studies in rural SSA, where the largest numbers of young people are estimated to be both ‘in child labour’ and ‘out of school’. In this review, we first unpick the dominant understandings of ‘work, childhood’ and ‘education’ and question some of the common assumptions about their relationship. In particular, we highlight some of the gendered ways in which rural schools can add to young people’s burden of work and can cause harm. In applying our framework, we demonstrate how work, learning and harm can apply across the whole edu-workscape in ways that interact, are dynamic, gendered and context-dependent. We therefore argue that any judgements about children’s workloads, learning or harm need to take account of this. Conceptualizing the work-education dynamic in this way has significant implications for research methodologies regarding children’s work/labour and education in any context, and the kinds of understandings they are likely to generate, with concomitant implications for policy and planning regarding both children’s work and schooling.
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The Africa chapter on climate change impacts, adaptation, and vulnerability under the IPCC's Working Group II.
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This study aims to compare impacts of climate change on streamflow in four large representative African river basins: the Niger, the Upper Blue Nile, the Oubangui and the Limpopo. We set up the eco-hydrological model SWIM (Soil and Water Integrated Model) for all four basins individually. The validation of the models for four basins shows results from adequate to very good, depending on the quality and availability of input and calibration data. For the climate impact assessment, we drive the model with outputs of five bias corrected Earth system models of Coupled Model Intercomparison Project Phase 5 (CMIP5) for the representative concentration pathways (RCPs) 2.6 and 8.5. This climate input is put into the context of climate trends of the whole African continent and compared to a CMIP5 ensemble of 19 models in order to test their representativeness. Subsequently, we compare the trends in mean discharges, seasonality and hydrological extremes in the 21st century. The uncertainty of results for all basins is high. Still, climate change impact is clearly visible for mean discharges but also for extremes in high and low flows. The uncertainty of the projections is the lowest in the Upper Blue Nile, where an increase in streamflow is most likely. In the Niger and the Limpopo basins, the magnitude of trends in both directions is high and has a wide range of uncertainty. In the Oubangui, impacts are the least significant. Our results confirm partly the findings of previous continental impact analyses for Africa. However, contradictory to these studies we find a tendency for increased streamflows in three of the four basins (not for the Oubangui). Guided by these results, we argue for attention to the possible risks of increasing high flows in the face of the dominant water scarcity in Africa. In conclusion, the study shows that impact intercomparisons have added value to the adaptation discussion and may be used for setting up adaptation plans in the context of a holistic approach.
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More than one billion people are suffering hunger and malnutrition in 2009. Food security has deteriorated since 1995 and reductions in child malnutrition are proceeding too slowly to meet the Millennium Development Goal (MDG) target of halving hunger by 2015. Three major challenges threaten current and future efforts to overcome food insecurity and malnutrition: climate and global environmental change and the consequent loss of ecosystems' services, the growing use of food crops as a source of fuel and the food and financial crises. This paper reviews and analyses the current and projected effects of climate change and bioenergy on nutrition and proposes policy recommendations to address these challenges. The first section of the review lays out the public health and socioeconomic consequences of malnutrition and explores causes and costs. The paper then analyses the implications of climate and global environmental change and biofuel production for food security and nutrition, addressing strategies for adaptation and mitigation. This analysis includes a number of important socioeconomic factors, besides climate change and biofuel production, that are currently impacting food and nutrition security, and that will likely contribute to future effects. The paper concludes with a series of policy proposals and recommendations to adapt to and mitigate the impacts of climate and global environmental change placing human rights in the centre of decision making. These proposals include a number of options for improving sustainability and food and nutrition security while addressing the links between climate change and bioenergy demand.
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In this paper, we explore the resilience and vulnerability of livelihoods within two different social-ecological dryland contexts of Botswana over the last 30 years. We drew on primary field data sources, including oral histories, livelihood surveys, ecological surveys, as well as documented evidence of environmental, socioeconomic, and institutional dynamics to identify a broad range of activities that combine to create a range of different household livelihood outcomes. We used this information as a starting point to assess the ways in which livelihoods have changed over time, and evaluated whether they have become more resilient or more vulnerable, and considered the factors that have contributed to these outcomes. In the context of dynamic dryland social-ecological systems, we applied a livelihood trajectory approach to explore the shocks and stresses that affect livelihoods and to elucidate the characteristics of livelihood strategies that contribute to increased resilience or vulnerability. We used a vulnerability framework as a means of framing discussion about vulnerability and resilience and as a means of identifying broader insights. The research identified "accumulator", "diversifier", and "dependent" households and the ways in which they move between these categories. More resilient livelihood trajectories can be achieved if the important role of formal and informal institutions is recognized.
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This study addresses the increasing flood risk in the Niger basin and assesses the damages that arise from flooding. Statistics from three different sources (EM-DAT, Darthmouth Flood Observatory, NatCat Munich RE) on people affected by floods show positive trends for the entire basin beginning in the 1980s. An assessment of four subregions across the Niger basin indicates even exponential trends for the Sahelian and Sudanian regions. These positive trends for flooding damage match up to a time series of annual maximum discharge (AMAX): the strongest trends in AMAX are detected in the Sahelian and Sudanian regions, where the population is also increasing the fastest and vulnerability generally appears to be very high. The joint effect of these three factors can possibly explain the exponential increase in people affected by floods in these subregions. In a second step, the changes in AMAX are attributed to changes in precipitation and land use via a data-based approach within a hypothesis-testing framework. Analysis of rainfall, heavy precipitation and the runoff coefficient shows a coherent picture of a return to wet conditions in the basin, which we identify as the main driver of the increase in AMAX in the Niger basin. The analysis of flashiness (using the Richards–Baker Index) and the focus on the "Sahel Paradox" of the Sahelian region reveal an additional influence of land-use change, but it seems minor compared to the increase in precipitation.
A rapidly growing body of research examines whether human conflict can be affected by climatic changes. Drawing from archaeology, criminology, economics, geography, history, political science, and psychology, we assemble and analyze the 60 most rigorous quantitative studies and document, for the first time, a striking convergence of results. We find strong causal evidence linking climatic events to human conflict across a range of spatial and temporal scales and across all major regions of the world. The magnitude of climate’s influence is substantial: for each one standard deviation (1σ) change in climate toward warmer temperatures or more extreme rainfall, median estimates indicate that the frequency of interpersonal violence rises 4% and the frequency of intergroup conflict rises 14%. Because locations throughout the inhabited world are expected to warm 2σ to 4σ by 2050, amplified rates of human conflict could represent a large and critical impact of anthropogenic climate change.
Introduction This chapter examines what is known about the effects of climate change on human health and, briefly, the more direct impacts of climate-altering pollutants (CAPs; see Glossary) on health. We review diseases and other aspects of poor health that are sensitive to weather and climate. We examine the factors that influence the susceptibility of populations and individuals to ill health due to variations in weather and climate, and describe steps that may be taken to reduce the impacts of climate change on human health. The chapter also includes a section on health "co-benefits." Co-benefits are positive effects on human health that arise from interventions to reduce emissions of those CAPs that warm the planet or vice versa. This is a scientific assessment based on best available evidence according to the judgment of the authors. We searched the English-language literature up to August 2013, focusing primarily on publications since 2007. We drew primarily (but not exclusively) on peer-reviewed journals. Literature was identified using a published protocol (Hosking and Campbell-Lendrum, 2012) and other approaches, including extensive consultation with technical experts in the field. We examined recent substantial reviews (e.g., Gosling et al., 2009; Bassil and Cole, 2010; Hajat et al., 2010; Huang et al., 2011; McMichael, 2013b; Stanke et al., 2013) to check for any omissions of important work. In selecting citations for the chapter, we gave priority to publications that were recent (since AR4), comprehensive, added significant new findings to the literature, and included areas or population groups that have not previously been well described or were judged to be particularly policy relevant in other respects. We begin with an outline of measures of human health, the major driving forces that act on health worldwide, recent trends in health status, and health projections for the remainder of the 21st century. 11.1.1. Present State of Global Health The Fourth Assessment Report (AR4) pointed to dramatic improvement in life expectancy in most parts of the world in the 20th century, and this trend has continued through the first decade of the 21st century (Wang et al., 2012).
Climate changes will affect food production in a number of ways. Crop yields, aquatic populations and forest productivity will decline, invasive insect and plant species will proliferate and desertification, soil salinization and water stress will increase. Each of these impacts will decrease food and nutrition security, primarily by reducing access to and availability of food, and also by increasing the risk of infectious disease. Although increased biofuel demand has the potential to increase incomes among producers, it can also negatively affect food and nutrition security. Land used for cultivating food crops may be diverted to biofuel production, creating food shortages and raising prices. Accelerations in unregulated or poorly regulated foreign direct investment, deforestation and unsustainable use of chemical fertilizers may also result. Biofuel production may reduce women's control of resources, which may in turn reduce the quality of household diets. Each of these effects increases risk of poor food and nutrition security, either through decreased physical availability of food, decreased purchasing power, or increased risk of disease. The Impact of Climate Change and Bioenergy on Nutrition articulates the links between current environmental issues and food and nutrition security. It provides a unique collection of nutrition statistics, climate change projections, biofuel scenarios and food security information under one cover which will be of interest to policymakers, academia, agronomists, food and nutrition security planners, programme implementers, health workers and all those concerned about the current challenges of climate change, energy production, hunger and malnutrition. © Springer Science+Business Media B.V. 2012. All rights reserved.