Sustainable extensification: Breathing new life into Africa's Sleeping Giant Mary Ollenburger (WUR, ICRISAT) Katrien Descheemaeker (WUR) Todd Crane (ILRI) Ken Giller (WUR)
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Sustainable extensification:
Breathing new life into
Africa's Sleeping Giant
Mary Ollenburger (WUR,
ICRISAT)
Katrien Descheemaeker (WUR)
Todd Crane (ILRI)
Ken Giller (WUR)
Africa’s Sleeping Giant?
• Guinea Savannah zone has high potential for agriculture-driven
growth (World Bank, 2009)
• Rainfed agriculture can be a pathway from poverty only if
farmers can grow and market high-value crops, or if land
expansion is possible (Harris and Orr 2014)
Rainfall: IFPRI/HarvestChoice,
Borders: FAO, Population density: WorldPop
Case Study: Bougouni, Mali
Map of Mali showing
Bougouni and AR villages
with data
Population
growth/density
• Rainfall 1200 mm/year,
• May-October
• Population density: 26 people
per sq. km.
• Main crops: cotton, maize,
groundnut
• Fertilizer availability tied to
cotton production
Can intensification or extensification of rainfed agriculture
lift farmers in Bougouni out of poverty?
Rainfall: IFPRI/HarvestChoice, Borders: FAO
Population density: WorldPop
Simple scenarios, exploring a solution space
• Many scenarios, using limited data, to quickly explore options
• Input data:
• Household survey at district level for yields, input costs
(AfricaRISING baselines), market survey for crop prices
• Rapid characterization of population of 109 farm
households in 3 villages (crop areas, livestock and
equipment)
• Calculated income from crops and food self-sufficiency for
each farm based on 50th and 90th percentile yields
Scenarios with current crop allocation
• Baseline: 50th percentile yields
• Yield gap reduction: 90th percentile yields
0
10
20
30
40
50
Farms
Cro
p a
rea (
ha
) Crops
Cotton
Groundnut
Maize
Other
Rice
Sorghum
Optimization Scenarios
Maximize gross margins by re-allocating crop areas subject to
constraints:
• Meet household calorie requirements with staple grains
• Maize area < twice cotton area (fertilizer availability
constraint)
• Total cropped area constrained to current area (or a
factor thereof)
1. With 50th percentile yields
2. With 90th percentile yields
3. Including cowpea, with 90th percentile yields
4. Allowing 50% land area expansion with 90th percentile
yields
Results: Crop Area
BaselineOptimization at 90th
percentile yield
Optimization at 90th percentile yield with cowpea
Optimization at 90th percentile yield with land expansion
0
20
40
60
0
20
40
60
Farms
Cro
p a
rea (
ha
) Crops
Cotton
Maize
Groundnut
Sorghum
Rice
Other
Dunanfana
Baseline Optimized
0
5
10
15
Farms
Fra
ction
of h
ouse
ho
ld fo
od
nee
ds
met
by o
wn p
rodu
ction 50%
90%
Optimized 90% with cowpea
Optimized 50%
Optimized 90%
Optimized 90% with land expansion
Results: Food Security
100% of household
calorie requirement
0
500
1000
Farms
Gro
ss m
arg
in f
rom
cro
ps (
US
D)
per
active
hou
seh
old
mem
ber
50%
Optimized 50%
90%
Optimized 90%
Optimized 90% with cowpea
Optimized 90% with land expansion
Results: Gross Margins
$1.25/person/day
poverty level
$2/person/day
poverty level
What can we learn from simple scenarios?
• “Rapid prototyping” of farm
designs to explore potential
• Intensification and cropland
expansion improve food
security, help some farms
move out of extreme poverty
• … but that’s it
• Optimizing dysfunctional
systems vs. system redesign
• Need to consider other
income sources, e.g. livestock
and non-farm income
IFPRI ARBES team
Ousmane Sanogo, Institut d’Economie Rurale
Mouvement Biologique Malienne
ICRISAT Technicians
The McKnight Foundation
Thank You
Africa Research in Sustainable Intensification for the Next Generation
africa-rising.net
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