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IS CASSAVA THE ANSWER TO AFRICAN CLIMATE CHANGE ADAPTATION?
Research Area on Decision and Policy Analysis (DAPA)

2030s

Climatic changes for cassavagrowing regions
38.3 (±73.9)

1.2 (±0.8)

Millet

Annual mean temperature change (°C)
1.7 (±1.4)

Maize

1.5 (±1.1)

1.3 (±0.9)
11.4 (±31.9)

9.4 (±56.3)

Cassava
Beans
Banana

SAF

NAF
CAF
EAF
-1.8 (±25)
Predicted changes in climates as average
of 24 GCMs (and uncertainties expressed
as standard deviations), by Africa regions.

WAF

area without
changes

Millet

-1.6 (±56.2)

Cassava

Africa regions
CAF: Central Africa SAF: South Africa
EAF: East Africa
SAH: Sahel
NAF: North Africa WAF: West Africa

Beans
Banana
Sorghum

!

Impact assessment methods are sensitive to uncertainties in climate data, and hence these must be
considered when assessing crop responses to combinations of increasing temperatures, varied
precipitation patterns and increased CO2 concentrations. There was a relatively strong disagreement in
GCM signals even for temperature and the uncertainty related to GCMs in rainfall was high.

Potato
Millet
Maize

~4%

NAF

Beans

70%

Banana

In CAF, there were very little
increases (<1% for all crops
except potato and beans, which
were predicted a substantial
decrease).

Sorghum
Potato
Millet

Cassava production is located in
WAF, EAF, CAF

Countries with increases below
1.5 °C where the most production
is located.

Of

overall increase in yearly
predicted rainfall in the SAH.

Cassava

Sorghum
Potato
Millet

BEANS (-16%±8.8)
POTATO (-14.7±8.2)
BANANA (-2.5%±4.9)
SORGHUM (-2.66%±6.45)
Whilst most areas in Africa
were
predicted
to
experience decreases in
overall suitability of the
additional crops modeled,
cassava
always
outperformed or (in the
worst case) equaled the
average of these crops.

Cassava
Beans

SAH

Banana
Sorghum
Potato
Millet
Maize
Cassava
Beans

WAF

Impacts of climate change on cassava suitability in
sub-regions of Africa (Average change in suitability)

17%

Conversely, for other major food
staples, we found that they are
all projected to experience
negative impacts, with the
greatest impacts for:

Maize

The EcoCrop model was used in
assessing the impacts of climate change.
It evaluates on a monthly basis if there
are adequate climatic conditions within a
growing season for temperature and
precipitation and calculates the climatic
suitability of the resulting interaction
between rainfall and temperature.

Predicted changes in
cassava suitability as
average of 24GCMs

Responses in SAF were observed
positive only for cassava, millet,
and banana (5% each).

Maize

SAF

Impacts of CC on cassava climate suitability

In EAF, however, cassava
showed the greatest
potential compared to all
other crops (10%), whereas
beans and potatoes were
the most affected.

In WAF, large negative impacts were
predicted for potato (-15%,), beans
(-20%), and banana (-13%,), whereas
millet, maize, and cassava were
predicted to remain the same. Sorghum
showed positive impacts (10%)

Cassava

>90%

In SAH, responses were
similar to those found in
WAF

Maize

SAH
-12.3 (±50.4)

9%

area with gain
in suitability

28%

Potato

Banana

Banana

-50

-25

0

Overall suitability change (%)

25

 Discrimination of areas according to gains and losses using

the mean change in suitability of all crops but cassava. Typology:
C: cassava, O: other crops; G: increase in suitability, L: decrease
in suitability. For instance, “C:G, O:L” indicates that in that area
cassava (C) increases in suitability (G), and all other crops in
average (O) decrease suitability (L)

 Boxplots are combinations of GCM-by-country predictions. Thick
black vertical lines are the median, boxes show the first and third
quartile and whiskers extend 5% and 95% of the distributions

WAF

area with loss
in suitability

SAH

47% 36%
!

area with loss
in suitability

Sorghum

Beans

area without
changes

63%

In NAF, moderate negative impacts were
predicted for beans (-4%), and potato (-4%),
slight positive changes for millet and banana.

EAF

The GCMs predicts
increases
in
temperatures
between 1.2 and
2
°C, and changes in
precipitation ranged
between -39 to +64
mm/year across all
Africa.

1.4 (±0.9)

Potato

Total annual rainfall change (mm)

1.6 (±1.3)

Cassava reacted very well to the predicted future climate
conditions compared to other crops.
Predicted changes in suitability of other staples (average among crops and GCMs)

Sorghum

CAF

We use downscaled
projections of 24
Global
Climate
Models (GCMs) for the
SRES-A1B emissions
scenario by 2030s
period (2020-2049).

Impacts of CC on other staple crops

Impacts on pests and diseases

SAF

area with gain
in suitability

NAF

Variation amongst individual GCM predictions was
significant and predicted impacts with very high certainty
(>80% GCMs predicting changes in the same direction).

Changes in cassava climatic suitability by
2030s as predicted by EcoCrop indicate
increases in the vast majority of areas, and
especially seem to occur in a greater
proportion over currently cropped areas and
where the most significant production is
reported.

EAF
Boxplots are combinations of GCM-by-country
predictions. Thick black vertical lines are the median,
boxes show the first and third quartile and whiskers
extend 5% and 95% of the distributions

CAF
-20

-10

0

10

20

30

Overall suitability change (%)
The most severe impacts were observed in WAF and the SAH,
where predicted changes were negative in ~80% of the countries.
3.3 km2 negatively
impacted areas

7.2 km
unchanged
2

5.5 km positively
impacted areas

Nigeria

−0.6 (±2.9)

Tanzania
8.3 (±5.5)

DR of the Congo
−0.1 (±0.7)

Angola

3.1 (±6.6)

Madagascar
Mozambique

5.6 (±2.7)

−0.6 (±4)

−3.7% to

+17.5%

is the projected change in
suitability across the
continent. Cassava is actually
positively impacted in many
areas of Africa.

Low temperatures
inhibit plant growth
and reduce leaf
production rate,
biomass and roots
yield but rarely kill
the plant.

Cassava is
tolerant to
within-season
drought, but this
depends on the
timing, intensity
and duration.

2.1
1.8
0.8

0.42

1.7

-5.5

-4.5
-8

Whitefly
Mealybug
Cassava mosaic disease
Cassava brown streak disease

Abiotic breeding priorities
Many cassava-growing regions (>80% of area) are not abiotically
constrained in 2030, meaning that they are unlikely to benefit from crop
improvement for abiotic traits.

Some cassava agroclimatological data
Cassava grows
optimally in the
range 25–29°C
although it can
withstand
temperatures
of up to 38°C.

Area likely to become pest and
disease free (million km2)

0.25

Ghana

-1.5

15.1 14.5

1

4.7 (±3.2)

Overall suitability change

19.1 18.1

600

Uganda

−0.3 (±1.5)

Area predicted to improve climate
suitability (million km2)

24.0 22.5

Newly affected
regions (million km2)

2

Ivory Coast

Current climatically suitable area
(million km2)

20.5 19.2

Countries with the highest harvest area and
overall suitability change (% ± SD)
0.2 (±3.2)

We then examined the challenges that cassava will likely face from pests and diseases
through the use of ecological niche modeling for cassava mosaic disease, whitefly, brown
streak disease, and cassava mealybug. The findings show that the geographic distribution
of these pests and diseases are projected to change, with both new areas opening up and
areas where the pests and diseases are likely to move away or reduce in pressure.

Above the
optimal
temperatures,
cassava increases
photosynthetic
rates and
branching.

Increased drought tolerance could bring benefits to nearly 30% of
cassava-growing regions in EAF, SAF, and SAH.
Cold tolerance is also a priority despite the projected warmer climates.
This is largely because of constraints in high-elevation regions of EAF or
in low latitudinal regions in SAF where seasonal temperatures during
winter pose a constraint for cassava development.




Designed by Carlos Navarro-Racines (CIAT-CCAFS 2013) e-mail:c.e.navarro@cgiar.org

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Is Cassava the Answer to African Climate Change Adaptation?

  • 1. IS CASSAVA THE ANSWER TO AFRICAN CLIMATE CHANGE ADAPTATION? Research Area on Decision and Policy Analysis (DAPA) 2030s Climatic changes for cassavagrowing regions 38.3 (±73.9) 1.2 (±0.8) Millet Annual mean temperature change (°C) 1.7 (±1.4) Maize 1.5 (±1.1) 1.3 (±0.9) 11.4 (±31.9) 9.4 (±56.3) Cassava Beans Banana SAF NAF CAF EAF -1.8 (±25) Predicted changes in climates as average of 24 GCMs (and uncertainties expressed as standard deviations), by Africa regions. WAF area without changes Millet -1.6 (±56.2) Cassava Africa regions CAF: Central Africa SAF: South Africa EAF: East Africa SAH: Sahel NAF: North Africa WAF: West Africa Beans Banana Sorghum ! Impact assessment methods are sensitive to uncertainties in climate data, and hence these must be considered when assessing crop responses to combinations of increasing temperatures, varied precipitation patterns and increased CO2 concentrations. There was a relatively strong disagreement in GCM signals even for temperature and the uncertainty related to GCMs in rainfall was high. Potato Millet Maize ~4% NAF Beans 70% Banana In CAF, there were very little increases (<1% for all crops except potato and beans, which were predicted a substantial decrease). Sorghum Potato Millet Cassava production is located in WAF, EAF, CAF Countries with increases below 1.5 °C where the most production is located. Of overall increase in yearly predicted rainfall in the SAH. Cassava Sorghum Potato Millet BEANS (-16%±8.8) POTATO (-14.7±8.2) BANANA (-2.5%±4.9) SORGHUM (-2.66%±6.45) Whilst most areas in Africa were predicted to experience decreases in overall suitability of the additional crops modeled, cassava always outperformed or (in the worst case) equaled the average of these crops. Cassava Beans SAH Banana Sorghum Potato Millet Maize Cassava Beans WAF Impacts of climate change on cassava suitability in sub-regions of Africa (Average change in suitability) 17% Conversely, for other major food staples, we found that they are all projected to experience negative impacts, with the greatest impacts for: Maize The EcoCrop model was used in assessing the impacts of climate change. It evaluates on a monthly basis if there are adequate climatic conditions within a growing season for temperature and precipitation and calculates the climatic suitability of the resulting interaction between rainfall and temperature. Predicted changes in cassava suitability as average of 24GCMs Responses in SAF were observed positive only for cassava, millet, and banana (5% each). Maize SAF Impacts of CC on cassava climate suitability In EAF, however, cassava showed the greatest potential compared to all other crops (10%), whereas beans and potatoes were the most affected. In WAF, large negative impacts were predicted for potato (-15%,), beans (-20%), and banana (-13%,), whereas millet, maize, and cassava were predicted to remain the same. Sorghum showed positive impacts (10%) Cassava >90% In SAH, responses were similar to those found in WAF Maize SAH -12.3 (±50.4) 9% area with gain in suitability 28% Potato Banana Banana -50 -25 0 Overall suitability change (%) 25  Discrimination of areas according to gains and losses using the mean change in suitability of all crops but cassava. Typology: C: cassava, O: other crops; G: increase in suitability, L: decrease in suitability. For instance, “C:G, O:L” indicates that in that area cassava (C) increases in suitability (G), and all other crops in average (O) decrease suitability (L)  Boxplots are combinations of GCM-by-country predictions. Thick black vertical lines are the median, boxes show the first and third quartile and whiskers extend 5% and 95% of the distributions WAF area with loss in suitability SAH 47% 36% ! area with loss in suitability Sorghum Beans area without changes 63% In NAF, moderate negative impacts were predicted for beans (-4%), and potato (-4%), slight positive changes for millet and banana. EAF The GCMs predicts increases in temperatures between 1.2 and 2 °C, and changes in precipitation ranged between -39 to +64 mm/year across all Africa. 1.4 (±0.9) Potato Total annual rainfall change (mm) 1.6 (±1.3) Cassava reacted very well to the predicted future climate conditions compared to other crops. Predicted changes in suitability of other staples (average among crops and GCMs) Sorghum CAF We use downscaled projections of 24 Global Climate Models (GCMs) for the SRES-A1B emissions scenario by 2030s period (2020-2049). Impacts of CC on other staple crops Impacts on pests and diseases SAF area with gain in suitability NAF Variation amongst individual GCM predictions was significant and predicted impacts with very high certainty (>80% GCMs predicting changes in the same direction). Changes in cassava climatic suitability by 2030s as predicted by EcoCrop indicate increases in the vast majority of areas, and especially seem to occur in a greater proportion over currently cropped areas and where the most significant production is reported. EAF Boxplots are combinations of GCM-by-country predictions. Thick black vertical lines are the median, boxes show the first and third quartile and whiskers extend 5% and 95% of the distributions CAF -20 -10 0 10 20 30 Overall suitability change (%) The most severe impacts were observed in WAF and the SAH, where predicted changes were negative in ~80% of the countries. 3.3 km2 negatively impacted areas 7.2 km unchanged 2 5.5 km positively impacted areas Nigeria −0.6 (±2.9) Tanzania 8.3 (±5.5) DR of the Congo −0.1 (±0.7) Angola 3.1 (±6.6) Madagascar Mozambique 5.6 (±2.7) −0.6 (±4) −3.7% to +17.5% is the projected change in suitability across the continent. Cassava is actually positively impacted in many areas of Africa. Low temperatures inhibit plant growth and reduce leaf production rate, biomass and roots yield but rarely kill the plant. Cassava is tolerant to within-season drought, but this depends on the timing, intensity and duration. 2.1 1.8 0.8 0.42 1.7 -5.5 -4.5 -8 Whitefly Mealybug Cassava mosaic disease Cassava brown streak disease Abiotic breeding priorities Many cassava-growing regions (>80% of area) are not abiotically constrained in 2030, meaning that they are unlikely to benefit from crop improvement for abiotic traits. Some cassava agroclimatological data Cassava grows optimally in the range 25–29°C although it can withstand temperatures of up to 38°C. Area likely to become pest and disease free (million km2) 0.25 Ghana -1.5 15.1 14.5 1 4.7 (±3.2) Overall suitability change 19.1 18.1 600 Uganda −0.3 (±1.5) Area predicted to improve climate suitability (million km2) 24.0 22.5 Newly affected regions (million km2) 2 Ivory Coast Current climatically suitable area (million km2) 20.5 19.2 Countries with the highest harvest area and overall suitability change (% ± SD) 0.2 (±3.2) We then examined the challenges that cassava will likely face from pests and diseases through the use of ecological niche modeling for cassava mosaic disease, whitefly, brown streak disease, and cassava mealybug. The findings show that the geographic distribution of these pests and diseases are projected to change, with both new areas opening up and areas where the pests and diseases are likely to move away or reduce in pressure. Above the optimal temperatures, cassava increases photosynthetic rates and branching. Increased drought tolerance could bring benefits to nearly 30% of cassava-growing regions in EAF, SAF, and SAH. Cold tolerance is also a priority despite the projected warmer climates. This is largely because of constraints in high-elevation regions of EAF or in low latitudinal regions in SAF where seasonal temperatures during winter pose a constraint for cassava development.   Designed by Carlos Navarro-Racines (CIAT-CCAFS 2013) e-mail:c.e.navarro@cgiar.org