Presentation during IITA R4D week 2015 (23 - 27 Nov. 2015). By: Keith Wiebe, IFPRI

1. www.iita.orgA member of CGIAR consortium
Global Futures & Strategic Foresight
Quantitative modeling to inform decision making
in the CGIAR and its partners
23 November 2015
(R4D Week 2015)
Keith Wiebe, IFPRI

2. Global Futures & Strategic Foresight
Quantitative modeling to inform decision making
in the CGIAR and its partners
Keith Wiebe, IFPRI
IITA, Ibadan, 23 November 2015

3. Outline
• Introduce the Global Futures & Strategic Foresight
(GFSF) program
• Share some recent projections from the IMPACT
model
• Describe some of the work that IITA is doing as part
of GFSF
• Reflect on how we might help inform decision
making in the CGIAR

4. Selected drivers of change
• Today, this season, this year
• Weather, pests, markets, conflict, migration…
• Medium term
• Agricultural policies, trade policies, markets…
• Long term
• Population, income, resources, climate, preferences,
technology…

5. Socioeconomic and climate drivers
Shared
Socioeconomic
Pathways (SSPs)
Representative
Concentration
Pathways (RCPs)
Source: Downloaded from the RCP Database version 2.0.5 (2015). RCP 2.6: van Vuuren et al. 2006; van Vuuren et al. 2007. RCP 4.5: Clark
et al. 2007; Smith and Wigley 2006; Wise et al 2009. RCP 6.0: Fujino et al 2006; Hijioka et al 2008. RCP 8.5: Riahi and Nakicenovic, 2007.
CO2 equiv. (ppm)Radiative forcing
(W/m2)
Population (billion) GDP (trillion USD, 2005 ppp)

6. Global Futures & Strategic Foresight
1. Improved tools for biophysical and
economic modeling
2. Stronger community of practice for
scenario analysis and ex ante impact
assessment
3. Improved assessments of alternative
global futures
4. To inform research, investment and policy
decisions in the CGIAR and its partners

7. 1. Improved modeling tools
• Complete recoding of IMPACT v3
• Disaggregation geographically
and by commodity
• Improved water & crop models
• New data management system
• Modular framework
• Training

8. 2. Stronger community of
practice
• All 15 CGIAR centers now
participate in GFSF
• Bioversity, CIAT, CIMMYT, CIP,
ICARDA, ICRAF, ICRISAT, IFPRI, IITA,
ILRI, IRRI, IWMI, WorldFish;
AfricaRice and CIFOR are joining
• Collaboration with other
global economic modeling
groups through AgMIP
• PIK, GTAP, Wageningen, IIASA, UFL,
FAO, OECD, EC/JRC, USDA/ERS, …

9. • Role of agricultural
technologies
• Africa regional reports
• Analyses by CGIAR
centers
• CCAFS regional studies
• AgMIP global
economic assessments
• Private sector
Rainfed Maize
(Africa)
Irrigated Wheat
(S. Asia)
Rainfed Rice
(S. + SE. Asia)
Rainfed Potato
(Asia)
Rainfed Sorghum
(Africa + India)
Rainfed Groundnut
(Africa + SE Asia)
Rainfed Cassava
(E. + S. + SE. Asia)
3. Improved assessments

10. 4. Informing decisions
• National partners
• Regional organizations
• International organizations
and donors
• CGIAR
• Centers
• CRPs
• System level?

11. Modeling climate impacts on agriculture:
biophysical and economic effects
General
circulation
models
(GCMs)
Global
gridded crop
models
(GGCMs)
Global
economic
models
Δ Temp
Δ Precip
…
Δ Yield
(biophys)
Δ Area
Δ Yield
Δ Cons.
Δ Trade
Climate Biophysical Economic
Source: Nelson et al., Proceedings of the National Academy of Sciences (2014)

12. Projections to 2050 w/o climate
change
Average of 5 global economic models for coarse grains, rice, wheat, oilseeds &
sugar
0
10
20
30
40
50
60
70
80
90
100
Yields Area Production Prices Trade
Percentchangefrom2005to2050
SSP1 SSP2 SSP3
Source: Wiebe et al., Environmental Research Letters (2015)

13. Climate change impacts in 2050
Average of 5 global economic models for coarse grains, rice, wheat, oilseeds &
sugar
-10
-5
0
5
10
15
20
Yields Area Production Prices Trade
Percentchangein2050
SSP1-RCP4.5 SSP2-RCP6.0 SSP3-RCP8.5
Source: Wiebe et al., Environmental Research Letters (2015)

14. IMPACT model: selected results
• Yields
• Prices
• Total demand
• Per-capita food demand
• Trade
• Food security

15. Growth in global cereal production
(SSP2, NoCC)
Source: IFPRI, IMPACT version 3.2, September 2015

16. Growth in cereal production by
region
(SSP2, NoCC)
World Latin Am & Caribbean
South Asia Sub-Saharan Africa
Source:
IFPRI, IMPACT version 3.2,
September 2015

17. Growth in global production of
pulses and oilseeds (SSP2, NoCC)
Source: IFPRI, IMPACT version 3.2, September 2015
Pulses Oilseeds

18. Rainfed maize and climate change: Projected
yield changes in 2050, before economic
responses
(HadGEM2, RCP 8.5)
Source: IFPRI DSSAT simulations

19. Yield effects of climate change
(SSP2)
Cereals
Source: IFPRI, IMPACT version 3.2, September 2015
WLD = World; EAP = East Asia and Pacific; EUR = Europe; FSU = Former Soviet Union; LAC = Latin America and Caribbean;
MEN = Middle East and North Africa; NAM = North America; SAS = South Asia; SSA = Sub-Saharan Africa;

20. Yield effects of climate change
(SSP2)
Cereals Maize
Rice Wheat
WLD = World; EAP = East Asia and Pacific; EUR = Europe; FSU = Former Soviet Union; LAC = Latin America and Caribbean;
MEN = Middle East and North Africa; NAM = North America; SAS = South Asia; SSA = Sub-Saharan Africa;
Source: IFPRI, IMPACT version 3.2, September 2015

21. Yield effects of climate change
(SSP2)
Source: IFPRI, IMPACT version 3.2, September 2015
Cereals Roots & tubers
Oilseeds Pulses
Fruits & veg
Sugar
WLD = World; EAP = East Asia and Pacific; EUR = Europe; FSU = Former Soviet Union; LAC = Latin America and Caribbean;
MEN = Middle East and North Africa; NAM = North America; SAS = South Asia; SSA = Sub-Saharan Africa;

22. Price impacts of climate and
socioeconomic drivers
Source: IFPRI, IMPACT version 3.2, September 2015
SSPsRCPs
Cereals Meats

23. Total global demand: aggregated
commodities (SSP2, NoCC)2010=1.00
Source: IFPRI, IMPACT version 3.2, September 2015

24. Total global demand: maize, rice,
wheat (SSP2, NoCC)2010=1.00
Source: IFPRI, IMPACT version 3.2, September 2015

25. Composition of food supply (SSP2,
NoCC)
Source: IFPRI, IMPACT version 3.2, September 2015
WLD = World; EAP = East Asia and Pacific; EUR = Europe; FSU = Former Soviet Union; LAC = Latin America and Caribbean;
MEN = Middle East and North Africa; NAM = North America; SAS = South Asia; SSA = Sub-Saharan Africa

26. Maize demand composition
(mmt) (SSP2, NoCC)
Source: IFPRI, IMPACT version 3.2, September 2015

27. Soybean demand composition
(mmt)
Source: IFPRI, IMPACT version 3.2, September 2015

28. Cassava demand composition
(mmt)
Source: IFPRI, IMPACT version 3.2, September 2015

29. Source: IFPRI, IMPACT version 3.2, September 2015
EAP = East Asia and Pacific; EUR = Europe; FSU = Former Soviet Union; LAC = Latin America and Caribbean;
MEN = Middle East and North Africa; NAM = North America; SAS = South Asia; SSA = Sub-Saharan Africa
Millionmetrictons
Cereals
Net trade and climate change
(SSP2)

30. Net trade and climate change
(SSP2)
Source: IFPRI, IMPACT version 3.2, September 2015
EAP = East Asia and Pacific; EUR = Europe; FSU = Former Soviet Union; LAC = Latin America and Caribbean;
MEN = Middle East and North Africa; NAM = North America; SAS = South Asia; SSA = Sub-Saharan Africa
Soybeans
Millionmetrictons

31. Population at risk of hunger
(SSP2, RCP8.5)
Source: IFPRI, IMPACT version 3.2, September 2015
EAP = East Asia and Pacific; SAS = South Asia; FSU = Former Soviet Union;
MEN = Middle East and North Africa; SSA = Sub-Saharan Africa; LAC = Latin America and Caribbean

32. Exploring the impacts of improved
technologies and practices on…
-40.0
-35.0
-30.0
-25.0
-20.0
-15.0
-10.0
-5.0
0.0
Malnourished Children Pop. at-risk-of-hunger
No till Drought tolerance Heat tolerance
Nitrogen use efficiency Integrated soil fertility mgt Precision agriculture
Water harvesting Sprinkler irrigation Drip irrigation
Crop Protection - insects
Source: Rosegrant et al. (2014)
Food Security
(Percent difference from 2050 CC baseline)
Source: Islam et al. (draft)
Crop yields
(Percent difference from 2050 CC baseline)

33. Global Futures & Strategic Foresight in
IITA
• Mandate crops: cassava, yam, maize, plantain/banana,
cowpea and soybean
• Objectives of GFSF in IITA:
• Development of modelling tools adapted to needs of IITA
• Community of practice to enhance validity of modelling tools and
results:
• Engagement between modellers and non-economists in IITA (breeders;
agronomists; etc.)
• Engagement between IITA and modellers in NARS: training workshops; etc.
• Informing R4D priority setting
• Agronomy versus breeding: resource allocation
• Better targeting of improved technologies depending on agro-ecological
characteristics
• National policies to enhance adoption of improved technologies:
engagement with policy-makers

34. Projected growth in cowpea production and
consumption in Nigeria and Niger (SSP2)
0
2000
4000
6000
8000
10000
12000
14000
2005 2010 2015 2020 2025 2030 2035 2040 2045 2050
Nigeria-Cons-NoCC
Nigeria-Cons-HadGEM
Nigeria-Prod-NoCC
Nigeria-Prod-HadGEM
Nigeria (000 MT)
0
500
1000
1500
2000
2500
3000
2005 2010 2015 2020 2025 2030 2035 2040 2045 2050
Niger-Cons-NoCC
Niger-Cons-HadGEM
Niger-Prod-NoCC
Niger-Prod-HadGEM
Niger (000 MT)
Source: IITA (in progress)

35. Projected gap between production and
consumption of soybean in Africa
(SSP2, RCP8.5)
-5000
-4500
-4000
-3500
-3000
-2500
-2000
-1500
-1000
-500
0
2005 2030 2040 2050
Demandgap(000MT)
Africa - SSP2- NoCC
Africa - SSP2- HadGEM
Source: IITA (in progress)

36. Future plans for GFSF work in
IITA
• Tools: develop accurate ‘base’
results for IITA’s mandate crops
• Biophysical crop modelling: calibrate and
validate standard and promising
technologies
• Socio-economic modelling: results for base
year (2005) for all IITA’s mandate crops;
intrinsic productivity growth rates (IPRs);
• Community of practice: training
workshop on bio-economic
modelling (BUK)
• Priority setting: report on impact of
promising cowpea technologies
Arega Tahirou Sika
Alpha Kamara,
agronomist
Boukar Ousmane,
cowpea breeder
Ken Boote
Prof. Jibrin

37. 4. Informing decision making
• National partners
• Regional organizations
• International organizations
and donors
• CGIAR
• Center work planning
• CRP Phase 2 proposals
• PIM, RTB, Maize, et al.
• System level?
• ISPC and donor interest

38. The CGIAR Research Agenda
System Level Outcomes (SLOs) and
Intermediate Development Objectives (IDOs)
Increased
resilience of
the poor to
climate
change and
other
shocks
Enhanced
smallholder
market
access
Increased
incomes
and
employment
Increased
productivity
Improved
diets for
poor and
vulnerable
people
Improved
food safety
Improved
human and
animal
health
through
better
agricultural
practices
Natural
capital
enhanced
and
protected,
especially
from
climate
change
Enhanced
benefits
from
ecosystem
goods and
services
More
sustainably
managed
agro-
ecosystems
Reduced Poverty
Improved natural
resource systems
and ecosystem
services
Improved food and
nutrition security
for health

39. Model improvements under way
• Livestock and fish
• Nutrition and health
• Land use
• Environmental impacts
• Variability
• Gender
• Poverty

40. Concluding thoughts
• Collective effort, involving all 15 CGIAR centers (and
other partners)
• Multiple scales of analysis
• Opportunity to inform decision making in the
CGIAR and its partners
• Quantitative model results as one input among several
• On-going effort to build capacity and a community
of practice to assess options over time
• Looking forward to collaboration with IITA!

41. Thank you
k.wiebe@cgiar.org