global futures & strategic foresight quantitative modeling to inform decision making in the...

www.iita.org A 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

Global Futures & Strategic Foresight Quantitative modeling to inform decision making

in the CGIAR and its partners

Keith Wiebe, IFPRI

IITA, Ibadan, 23 November 2015

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

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…

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)

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

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

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, …

• 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

4. Informing decisions

• National partners • Regional organizations • International organizations

and donors • CGIAR

• Centers • CRPs • System level?

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)

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

Perc

ent

chan

ge f

rom

20

05

to

20

50

SSP1 SSP2 SSP3

Source: Wiebe et al., Environmental Research Letters (2015)

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

Perc

ent

chan

ge in

20

50

SSP1-RCP4.5 SSP2-RCP6.0 SSP3-RCP8.5

Source: Wiebe et al., Environmental Research Letters (2015)

IMPACT model: selected results

• Yields

• Prices

• Total demand

• Per-capita food demand

• Trade

• Food security

Growth in global cereal production (SSP2, NoCC)

Source: IFPRI, IMPACT version 3.2, September 2015

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

Growth in global production of pulses and oilseeds (SSP2, NoCC)


Pulses Oilseeds

Rainfed maize and climate change: Projected yield changes in 2050, before economic responses (HadGEM2, RCP 8.5)

Source: IFPRI DSSAT simulations

Yield effects of climate change (SSP2)

Cereals


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;


Cereals Maize

Rice Wheat





Cereals Roots & tubers

Oilseeds Pulses

Fruits & veg

Sugar


Price impacts of climate and socioeconomic drivers


SSP

s R

CPs

Cereals Meats

Total global demand: aggregated commodities (SSP2, NoCC)

20

10

= 1

.00


Total global demand: maize, rice, wheat (SSP2, NoCC)

20

10

= 1

.00


Composition of food supply (SSP2, NoCC)


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

Maize demand composition (mmt) (SSP2, NoCC)


Soybean demand composition (mmt)


Cassava demand composition (mmt)



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

Mill

ion

met

ric

ton

s

Cereals

Net trade and climate change (SSP2)

Net trade and climate change (SSP2)


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

Mill

ion

met

ric

ton

s

Population at risk of hunger (SSP2, RCP8.5)


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

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)

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

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)

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

De

man

d g

ap (

00

0 M

T)

Africa - SSP2- NoCC

Africa - SSP2- HadGEM

Source: IITA (in progress)

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

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

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

Model improvements under way

• Livestock and fish

• Nutrition and health

• Land use

• Environmental impacts

• Variability

• Gender

• Poverty

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!

Thank you [email protected]

mailto:[email protected]