mark rosegrant food security, farming, and climate change to 2050 mark rosegrant
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IFPRI Policy Seminar "Food Security, Farming, and Climate Change to 2050" by Mark RosegrantTRANSCRIPT
Food Security, Farming, and Climate Change to 2050
Scenarios, Results, Policy Options
Mark W. Rosegrant and Gerald C. NelsonInternational Food Policy Research Institute
December 1, 2010
AcknowledgementsThe authors
◦ Gerald C. Nelson, Mark W. Rosegrant, Amanda Palazzo, Ian Gray, Christina Ingersoll, Richard Robertson, Simla Tokgoz, Tingju Zhu, Timothy Sulser, Claudia Ringler, Siwa Msangi, and Liangzhi You
Project Foresight: The Future of Food and Farming as catalyst for this effort
Philip Thornton and Peter Jones for downscaled climate scenarios
Jawoo Koo for crop modeling assistanceSeveral anonymous reviewers
Page 2
Food Security Challenges
Population growth◦ 50 percent more people by 2050◦ Almost all in developing countries
Income growth in developing countries◦ More demand for high valued food (meat,
fish, fruits, vegetables) and feed for livestock
Increased demand on land and watero Demands for energy and climate mitigation
as well as food, feed, and fiber Climate change – a threat multiplier
◦ Reduced productivity of existing varieties, cropping systems
Page 3
New messages for sustainable food security and climate change resilienceAddress poverty with broad-based
income growthInvestment in agricultural productivity
growth is key adaptation policy
• On-farm: water harvesting, minimum tillage, integrated soil fertility management
• Rural infrastructure investment to improve access to markets, risk insurance, credit, inputs
Strengthen international trade agreements
Page 4
OutlineFuture scenarios for climate change
and food securityImpacts: crop yields, supply,
demand, and trade Assessing the food security
challenge with and without climate change
Page 5
CHARACTERIZING PLAUSIBLE FUTURESOverall (economic and demographic) scenarios
under varying climate futures
Page 6
Overall scenariosPlausible futures for population and GDP growth
Optimistic◦High GDP and low population growth
Baseline◦Medium GDP and medium population
growthPessimistic
◦Low GDP and high population growth
Page 7
Global and regional GDP per-capita growth scenarios
Page 8
Pessimistic
Baseline Optimistic
Central Africa
2.42 3.92 4.85
Western Africa
2.04 3.63 4.03
Eastern Africa
2.72 4.18 4.97
Northern Africa
1.78 2.60 3.49
Southern Africa
0.55 2.98 3.44
PessimisticBaseline OptimisticPopulation 1.04 0.70 0.35GDP 1.91 3.21 3.58GDP per capita 0.86 2.49 3.22
Global growth rate assumptions, annual average 2010-2050 (%)
African GDP per capita growth rate assumptions, annual average 2010-2050 (%)
Climate ScenariosOur modeling approach, for each
overall scenario◦Two GCMs – MIROC (Japanese) and CSIRO
(Australian)◦Two SRES scenarios – A1B and B1◦Perfect mitigation
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FOOD SUPPLY AND DEMAND RESULTSCombining biophysical and socio-economic
drivers
Page 10
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Income and population growth drive prices higher(price increase (%), 2010 – 2050, Baseline economy and demography)
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Climate change adds to price increases(price increase (%), 2010 – 2050, Baseline economy and demography)
Mean effect from four climate
scenarios
Page 13
Climate change scenario effects differ(price increase (%), 2010 – 2050, Baseline economy and demography)
Minimum and maximum effect from four climate
scenarios
Page 14
Economy and population scenarios alter price outcomes(Price increase (%), 2010 – 2050, Changing economy and demography)
Rice price increase smallest in optimistic
scenario as Asian demand falls with higher income
Maize price increase largest in pessimistic
scenario as food demand rises with low income and
high population growth
Impact on Calorie Consumption
Average = 12 % decline in developing countries due to climate change (Average of four GCM, A1, A2 ,B1,
B2 Scenarios)
South
Asia
East
Asia
and P
acifi
c
Euro
pe an
d Cen
tral
Asia
Latin A
mer
ica
and C
arib
bean
Mid
dle E
ast an
d Nor
th A
frica
Sub Sah
aran
Africa
-
500
1,000
1,500
2,000
2,500
3,000
3,500 2000 2050 No CC 2050 with CCk
Ca
l/C
ap
ita
/da
y
Impact on Childhood Malnutrition
Average = 11% increase in developing countries due to climate change (Average of four GCM, A1, A2 ,B1,
B2 Scenarios)
-
10,000
20,000
30,000
40,000
50,000
60,000
70,000
80,000 2000 2050 No CC 2050 with CC
Mil
lio
ns o
f C
hil
dre
n
2010
2015
2020
2025
2030
2035
2040
2045
2050
Pessimistic scenario
Perfect miti-gation
2010
2015
2020
2025
2030
2035
2040
2045
2050
1,800
2,000
2,200
2,400
2,600
2,800
3,000
3,200
3,400
3,600
Optimistic scenarioKc
als/
day
Developedcountries
All developingcountries
Low-income developing countries
Assessing food security and climate change outcomes
Exploring productivity enhancementsIncrease annual yield growth by 40
percent in developing countriesCommercial (hybrid) maize yield
improvement to 2 percent per year in selected countries
Wheat yield improvement to 2 percent per year in selected countries
Cassava yield improvement to 2 percent in selected countries
Irrigation efficiency
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Productivity improvements reduce malnutrition (change in number of malnourished children in 2050, million)
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Scenario 2050 simulation minus 2050 baseline (million)
Low-income Developing
Middle-income Developing
Overall -6.6 -12.5
Commercial maize -2.1 -1.7
Developing country wheat -0.7 -1.9
Developing country cassava -1.0 -0.4
Irrigation -0.1 -0.3
ConclusionsSustainable economic growth is a
powerful form of climate change adaptation
Agricultural productivity research output in hands of farmers can reduce poverty and improve climate change resilience
Open international trade is essential for dealing with uncertainties
Mitigation is critical◦ Adaptation to 2050 is manageable, but less
certain beyond
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