Public Sector Research Priorities for Sustainable Food Security by Gerald Nelson, IFPRI and Dominique van der Mensbrugghe, FAO at the Food Security Futures I Conference, on 11 April 2013 in Dublin, Ireland.

1. Public Sector Research Priorities
for Sustainable Food Security
Perspectives from Plausible
Scenarios
Gerald C. Nelson, IFPRI and Dominique van der Mensbrugghe, FAO
Food Security Futures 1, Dublin, Ireland, 11 April 2013

2. Harry S Truman
Give me a one-handed economist! All my economists say, On the
one hand… on the other.
The future is an uncertain place.
Plausible scenarios help to bound the uncertainty to
guide investments and policy decisions.

3. After a steady decline, progress towards the
MDG hunger target has stalled
Millions of hungry people
1050
World Developing world
1000
1000
980
950
931
922
898
900
909 905
867 868
885
850
852 852
800
1995-97 2007-09 2015
Source: Food and Agriculture Organization of the United Nations (2012).

4. Regional disparities in progress in reducing
undernourishment are large. Between 1990 and
2011,…
350
Increase of 64 Decrease of 22
300
Million undernourished
million in Sub- million in South Asia
250 Saharan Africa
200
150
100
50
0
Sub-Saharan South East Asia South Asia East Asia Latin America Other developing
Africa
1990/92 2010/12
Source: Food and Agriculture Organization of the United Nations (2012).

5. What Might the Future
Hold?
Recent findings from FAO and the CGIAR

6. Participants who determine the future
▪ The private sector
▪ Ranging from the smallest of small holder to the largest of global agribusinesses, manages
resources to meet their own internal imperatives of subsistence, survival and profitability.
▪ The public sector
▪ Provides
▪ A ‘level playing field’ – the set of formal institutions that all participants are legally obliged to
adhere, and enforcement
▪ Provision of various kinds of public goods that improve the workings of the private sector
▪ Civil society
▪ Watches over both the public and private sectors and uses its voice to improve the
functioning of both.

7. The sources of food security challenges: drivers
of change
▪ Demand
▪ The number of people
▪ Their command over financial and physical resources
▪ Their dietary desires
▪ Their location
▪ Supply
▪ The capacity of natural resources, augmented by human actions, to meet these
demands over an extended period.

8. FAO AT2050: Cautious optimism for improved food
security, but climate change effects not included
▪ Supply – agricultural production increases by 60 percent between 2006 and 2050
▪ Demand – population growth is more important than income growth
▪ Population growth – 39 percent
▪ Income growth – 21 percent
▪ Well-being outcome – caloric intake increases at the global level by 12.8 percent
▪ 2006 – 2,772 kcal/day/person
▪ 2050 – 3,070 kcal/day/person
▪ Significantly more in the poorest regions
▪ But including climate change nuances the good news, potentially significantly for
some regions
Source: Alexandratos and Bruinsma (2012), FAO.

9. Modest cereal yield improvements
(kg/ha left-axis, growth percent per annum right-axis)
5,000 2.5
4,500
4,000 2.0
3,500
Percent per annum
3,000 1.5
Kt/ha
2,500
2,000 1.0
1,500
1,000 0.5
500
0 0.0
sub-Saharan South Asia Near East & N. Latin America Developing World Developed East Asia
Africa Africa countries countries
2006 2050 Growth 0.65% p.a. vs. 2% p.a. 1960-2005
Source: Alexandratos and Bruinsma (2012).

10. Land use change continues in Latin America and
Sub-Saharan Africa
(million hectares left-axis, percent change 2005/07 - 2050 right-axis)
160 32
140 28
120 24
Percent change 2005/7-2050
100 20
Million hectares
80 16
60 12
40 8
20 4
0 0
Developing Latin America sub-Saharan Africa Near East & N. East Asia South Asia Developed
countries Africa countries
Irrigated land change, million hectare (left-axis) Rain-fed land change, million hectare (left-axis) Percent change between 2005/07-2050 (right-axis)
Source: Alexandratos and Bruinsma (2012).

11. Food Security, Farming, and Climate Change to
2050: Key Findings
▪ GDP and population growth result in price increases between 2010 and 2050
▪ Climate change hurts productivity and causes even greater price increases
▪ International trade flows are an important adaptation component
Source: Nelson et al, 2010.

12. Income and population growth drive prices higher
(price increase (%), 2010 – 2050, Baseline economy and demography)
Nelson et al, 2010.

13. Climate change increases prices even more
(price increase (%), 2010 – 2050, Baseline economy and demography)
Minimum and maximum
effect from four climate
scenarios
Nelson et al, 2010.

14. Three main messages to policy makers
▪ In low-income countries, sustainable development is a more important priority
than climate change adaptation today
▪ Prepare today for higher temperatures and changes in precipitation in all sectors
tomorrow
▪ Invest more in capacity to adapt agriculture
▪ Keep international trade relatively free from barriers
▪ Collect better data today and tomorrow on existing situation and practices
▪ Weather, land cover, water availability, prices, practices

15. Parsing the future: Plausible scenarios in 2013
▪ What do we know?
▪ Population will grow
▪ Incomes will increase in many places
▪ Temperatures will rise, precipitation patterns will change
▪ But by how much?
▪ Use combinations of plausible drivers to generate a range of plausible outcomes
▪ Shared Socioeconomic Pathways (SSPs) from IPCC
▪ New IPCC socioeconomic scenarios – population, income, urbanization
▪ Add new IPCC climate scenario – RCP8.5 – most extreme in the new suite of GHG
emission pathways

16. The selected scenarios
Scenario SSP GCM Crop model
S1 SSP2 None Reference yields
S2 SSP3 None Reference yields
S3 SSP2 IPSL—RCP 8.5 LPJml
S4 SSP2 Hadley—RCP 8.5 LPJml
S5 SSP2 IPSL—RCP 8.5 DSSAT
S6 SSP2 Hadley—RCP 8.5 DSSAT

17. The per capita income gap remains large in 2050
but is reduced in some scenarios
50,000
45,000
40,000
35,000
$2007 per capita
30,000
25,000
2010
20,000 SSP2
SSP3
15,000
10,000
5,000
0
World Developing South Asia E. Europe & Middle East Sub-Saharan Latin High Income
East Asia Central Asia & North Africa America &
Africa Caribbean

18. Temperatures and precipitation increase
(Absolute changes in annual mean temperature [°C] (top) and annual mean
precipitation [mm/day] (bottom), 2000-2050)
HadGEM-ES2, RCP8.5 IPSL-CM5A-LR, RCP8.5
Temperature
Increases of
6°C to 8°C in
northern
latitudes
Precipitation
Drying in
southeast US
and northern
Brazil
Source: Müller, C., & Robertson, R. D. (2013 submitted). Projecting future crop productivity for global economic modeling.
Agricultural Economics.

19. Rainfed maize yields decline
(Relative changes in rain fed maize productivity climate scenarios for the RCP8.5
emission scenario, 2000-2050)
HadGEM-ES2, RCP8.5 IPSL-CM5A-LR, RCP8.5
DSSAT
DSSAT
effects are
greater than
LPJmL
LPJmL
Source: Müller, C., & Robertson, R. D. (2013 submitted). Projecting future crop productivity for global economic modeling.
Agricultural Economics.

20. What are the consequences?
▪ Prices
▪ Calorie availability
▪ Child malnutrition

21. Climate change causes price increases
Difference in 2050 (SSP2), climate change to no climate change
(percent)

22. Consequences for Well-
Being
Average calorie availability and number of malnourished children

23. In High income countries, neither income nor climate SSP3 with no
change scenarios affect average calorie availability climate change
3,600
3,400
Kcals per person per day
3,200
SSP2 with no
3,000
climate change
SSP2 with
climate change
2,800
2,600
2,400
2,200
2010 2015 2020 2025 2030 2035 2040 2045 2050
SSP2, no climate change SSP3, no climate change SSP2, IPSL, LPJmL
SSP2, Hadley, LPJmL SSP2, IPSL, DSSAT SSP2, Hadley, DSSAT

24. In Middle income countries, income growth and climate
change effects are both important SSP2 with no
3,600 climate change
3,400
Kcals per person per day
3,200
3,000
2,800
2,600 SSP3 with no SSP2 with
climate change climate change
2,400
2,200
2010 2015 2020 2025 2030 2035 2040 2045 2050
SSP2, no climate change SSP3, no climate change SSP2, IPSL, LPJmL
SSP2, Hadley, LPJmL SSP2, IPSL, DSSAT SSP2, Hadley, DSSAT

25. In Low income countries, income growth and climate
change effects are both important
3,600
3,400
Kcals per person per day
3,200
SSP2 with
3,000
SSP2 with no climate change
climate change
2,800
2,600 SSP3 with no
climate change
2,400
2,200
2010 2015 2020 2025 2030 2035 2040 2045 2050
SSP2, no climate change SSP3, no climate change SSP2, IPSL, LPJmL
SSP2, Hadley, LPJmL SSP2, IPSL, DSSAT SSP2, Hadley, DSSAT

26. in Middle income developing countries, income growth is most
important in reducing the number of malnourished children
(million)
110
105
100
95
SSP3 with no
90 climate change
85
80
75
70
65
SSP2 with no SSP2 with
60 climate change climate change
2010 2015 2020 2025 2030 2035 2040 2045 2050
S1 S2 S3 S4 S5 S6

27. in Low income developing countries, income growth is most
important in reducing the number of malnourished children
(million)
50
45
SSP3 with no
climate change
40
35
SSP2 with no
climate change
30
SSP2 with
25
climate change
2010 2015 2020 2025 2030 2035 2040 2045 2050
S1 S2 S3 S4 S5 S6

28. Price outcomes differ by model
Difference in 2050 (SSP2), climate change to no climate change (percent)
110 Coarse grains Oil seeds Rice Sugar Wheat
% change relative to Reference Scenario S1 in 2050
90
70
50
30
10
-10
S3S4S5S6S3S4S5S6S3S4S5S6S3S4S5S6S3S4S5S6S3S4S5S6S3S4S5S6S3S4S5S6S3S4S5S6
AIM ENVISAGE FARM GTEM MAGNET GCAM GLOBIOM IMPACT MAgPIE

29. What is missing in these scenarios?
▪ Climate change
▪ Increasing extreme events
▪ Effects of changes in pest pressure
▪ Malnutrition
▪ Calorie availability contribution to undernutrition
▪ Calorie (and other nutrient) distribution to different groups
▪ Modeling overnutrition
▪ Sustainability
▪ Definitions
▪ Metrics

30. Priorities for CGIAR and FAO scenario development
and strategic foresight:
Cooperation is key to address missing elements
▪ Cooperative quantitative modeling
▪ Linking (and enhancing) partial and general equilibrium modeling
▪ Linking (and enhancing) biophysical and socioeconomic modeling
▪ Cooperative use of institutional and outside substantive expertise
▪ Actively involve biological experts in scenario development
▪ Sustained cooperation with model intercomparison efforts