The Knowledge Lab on Climate Resilient Food Systems: An analytical support facility to achieve the SDGs (All Presentation Slides)

Knowledge Lab on Climate
Resilient Food Systems
Channing Arndt, Director
Environment and Production Technology Division
International Food Policy Research Institute (IFPRI)
IFPRI/AGRA Workshop
Nairobi, Kenya, February 7, 2019

Food systems fundamentally influence the environment
of the planet, the livelihoods of billions of people
(including most of the world’s poor), and the nutrition of
every human being. Robust food systems can serve as
catalysts for achieving the Sustainable Development
Goals, but their current weaknesses are major sources of
vulnerability to a variable and changing climate.
The Knowledge Lab on Climate-Resilient Food
Systems

What is resilience?
▪ An ability to withstand shocks:
o Climate/weather
o Economic
oHealth
▪ At various levels:
oHousehold
o Institution/firm
o Country/region

1. Two-Way Integration of Expertise
2. A High Impact Collaborative Research Program
3. Partnerships for Impact
Three Pillars of the Knowledge Lab

A. Leveraging new technologies
B. Facilitating social change
C. Assessing country resilience
Pillar 2 - Collaborative Research

A. Leveraging new technologies
• Information and communications technologies including remote sensing
• Distributed energy systems and the energy-water-food nexus
• Bio-innovation
B. Facilitating social change
• Management of common property
• ICT enabled extension
• Gender relations in a context of change
C. Assessing country resilience (model framework)
• Investment analysis (DREAMpy and RIAPA)
• Linked biophysical and economic models (IMPACT-SIMM and SACRED at the
country/regional scale and the full IMPACT modeling suite at global scale)
• Linked energy planning and economywide modeling (ISM_E)
Pillar 2 - Collaborative Research

▪ Vastly greater human and institutional capabilities in developing
countries.
▪ Greater capabilities in developing countries leads to greater
emphasis on enhancing capabilities.
▪ Quality analytical work must build on a large and increasing
stock of knowledge requiring partnerships.
Pillar 1 - Two-way Integration of Expertise

▪ Formal courses taught on a regular basis targeted at:
• Users of research (basic concepts and intuition)
• Producers of research (advanced frameworks)
o Space exists between what is taught at universities and actual research
practice.
▪ Four domains within IFPRI
• Models for assessing resilience (start here)
• Impact evaluation
• Remote sensing
• Welfare measurement
Pillar 1 – Distance learning

▪ Efficiently meet ongoing capacity building objectives.
▪ Develop and maintain relationships with key individuals
and key institutions in developing countries.
▪ Expand the user base of IFPRI research products and
frameworks.
▪ Set the groundwork for effective research collaboration.
Pillar 1 - Goals of Distance Learning Program

▪ Contacted
• African Research Universities Alliance (12 top universities in Africa)
• African Economic Research Consortium (1000+ African researchers)
• The Think Initiative (46 think tanks in 23 countries such the Centre for
the Study of the Economies of Africa in Nigeria and REPOA in Tanzania)
• Chinese Academy of Agricultural Sciences
• Planning/Finance units (BAPPENAS in Indonesia, NEDA in the
Philippines, CIEM in Vietnam, Economic Policy in South Africa, KIPPRA
in Kenya, etc.)
• Regional Network of Agricultural Policy Research Institutes (ReNAPRI)
Pillar 1 - Potential partners

▪ Establish clear pathways to impact
• Leveraging new technologies
o Digital Green and the Ethiopian Extension Service
o Program on Bio-Safety (PBS)
• Facilitating social change
o Foundation for Ecological Security
o Self-Employed Women’s Association
• Assessing country resilience
o National Economic Development Agency of the Philippines
o Southern Africa and the Global Commission on Adaptation
Pillar 3 – Partnerships for impact

The Potential of BIG
Data Timothy S. Thomas
Research Fellow, International Food Policy Research Institute (IFPRI)
tim.thomas@cgiar.org
Nairobi, Kenya
February 7, 2019

What is Big
Data?
• Definition is not agreed upon
• Large datasets that create challenges for storing and processing on
single computers
• Controversial example: harvested Facebook data used to influence
elections
• For our purposes: Main type will be remotely sensed data or raster
data with multiple layers
• Could include much more: e.g., cellphone users voluntarily submitting
photos of land cover and land use

Why Now for Big
Data?
• The number of satellites are growing exponentially
• 5 Spot satellites (ESA)
• 2 LandSat satellites (NASA)
• 2 MODIS satellites (NASA)
• 2 CBERS satellites (Chinese-Brazilian)
• High resolution: GeoEye-1, QuickBird, WorldView 1-4, IKONOS, Pléiades,
KOMPSAT & TripleSat
• Planet has launched 298 satellites, 150 of which are currently in orbit
collecting over 300 million square kilometers of imagery daily (3 m).
• The resolution of satellite imagery is improving
• Potential of drones / UAVs (unmanned aerial vehicles)

Not just for researchers: ICT can help get sustained,
personalized information to farmers: Extension Services

30-40%
increase in yields
30-45x
return in farmer income /
dollar invested
20-25%
increase in
farmer income
10x
cost savings for public
systems
>50%
greater adoption
rates
Preliminary data shows that successful ICT-enabled
Remote Advisory Services (RAS) could drive
SOURCE: Yield, income, ROI and cost targets are aspirational targets estimated for RAS investments
based on evidence from existing models and dimensions of BMGF proposed investment. Dalberg
study provides detailed data and methodology on impact and cost-effectiveness of RAS models.

An Example Using Big Data: Climate
Trends 30year trend in temperature change
for mean daily maximum
temperature for the warmest month
of the year, 1980-2010, 0C
Notes:
• Aggregated daily maximum temperature
data (AgMERRA) at each point to
monthly values and then found the
warmest month for each year.
• Ran regression at each point on trend
line.
• Only reported points with a trend that
was statistically significant at 90%.

Another Example of Big Data: Climate
ModelsChange in mean annual rainfall, 1960-1990 to 2040-2069, millimeters
GFDL HadGEM IPSL MIROC
Source: From CMIP5, using downscaling found in Muller and Robertson (2014).
Notes: Assumes RCP8.5.

Another Example of Big Data: Modeled Cropland
(SPAM: Spatial Production Allocation Model)
Percent of total land area in rainfed maize Yield of rainfed maize, circa 2005, kg/hect
Source: You
et al. (2014)

Another Example of Big Data: Climate Impact
on Agriculture
Percent yield
change from
climate change
for rainfed maize,
median results of
4 climate models,
1960-1990 to
2040-2069
Notes: Masked
out areas where
SPAM showed
rainfed maize was
less that 1% of the
pixel

Another Example of Big Data: Land
CoverMODIS 2013 CCI 2015

Potential Use of Big Data: Agricultural
Production Statistics
Problem
•Do not have a very clear picture where each crop is grown
•Do not know how much is produced each year
•Cannot easily project the harvest
Why this is important
• Help improve food security
• Help governments and donors respond to food crises
• Help farmers find markets and get better prices
• Help consumers get better prices
• Help better formulate agricultural policy
• Improve agricultural research focus on new crop varieties

AGRA’s
Technologies for Agricultural
Transformation

Typical “Green Revolution” vs.
Sub-Saharan Africa’s Immense Diversity
• 49 Countries
• Variable agro-ecologies
• 17 Major Food Crops (maize, sorghum, rice, millet, beans, cowpea, banana,
cassava, sweet potato, Irish potato, tef, barley, groundnut, fonio, faba bean,
yams, taro)
• High vulnerability to shocks arising from crop disease, drought, climate
change, political crises/conflicts and economic volatility.

4
The Technologies and Services AGRA strives to deliver at farm level
• Improved Seed – catalyzer of technological change at farmer level.
• Soil Fertility and Improved Fertilizers – building the soil, feeding the
crop, including micro-nutrients.
• Extension – giving all farmers an opportunity to increase yields and
profitability.
• Input Supply and Agro-Dealer Development – removing the barrier of
physical access to new technologies
• Markets – helping farmers meet market demand and standards;
growing SME grain traders.
• Inclusive Finance – improving access to capital for growth among
African agri-businesses.
Taking a
systems
approach in
partnership
with public
and private
actors

6
Soil Fertility & Fertilizer Systems Interventions
(i) Awareness Dissemination
VBAs, Demos,
smallerpacks,radio ICT
Platforms;
Key players: Agrodealers,
NGO’s,
Fertilizer companies.
(i) Enablers
(a) Physical Access;
Key players;
Hub and retailagro-
dealers,
(b)Financial access;
Key players,
Credit, Risk,Sharing
facilityofftakers.
(i) Commercialization&
Distribution
Key players; fertilizercompanies
Financing partners,
banks, AECF,AFAP
for capital and working capital for
feeder materials andoperations),
hub agro-dealers,
retail agro-dealers.
(i) Product Development
Key playersinclude;NARS,
Fertilizer companies e.g.
Yara, OCP, Minjigu, MEA,AFAP
(ii) Validation Trials:
Crop response and omission trials
Key players: NARS, CGIARs,
NGOs, Fertilizer
.
(i)Soil Testing & Mapping
Key Players:
National Agriculture
Research (NARS),
CGIAR
Private sector such as
Soildoc,soil cares,AfSIS)
(ii.)Synthesis of existing soil
databases
Existing soildatabases
a b c d e
Research & Development Technology
Dissemination Supply chain &
Management
Farmer Access
Policy - Release of new blends, quality control
Financing - Actors in the fertilizer chain includingfarmers

7
Input Distribution Interventions
Input Supply
Companies
•Supply
Seeds/Fertilizer/other
inputs
•Promotion and demand
creation
Hub Agro dealers Retail / Rural
Agro dealers
Avail improved inputs to SHFs, especially in
rural areas
• Increase awareness and adoption of new
technologies
• Primary commodity aggregation, storage &
PHH
• Linking SHFs to structured markets
• Other farm & PH
services – spraying,
shelling, etc
• Supply Seeds/Fertilizer/other inputs at
•
Large
• Increase awareness and adoption of
new technologies
• Commodity aggregation, storage &
PHH
Commodity off taker
• Commodity aggregation, storage and
PHH
• Advance cash to SME aggregation to
procure produce

Private Sector-Led Extension
using the Village-based Advisor Approach
VBAs are:
✓ typically hard-working, selfless farmers
✓ selected by, and therefore trusted by, farmers in
their villages.
VBAs are taught:
✓ how to reach and teach all farmers in their
villages, including women and youth;
✓ good crop/soil management and crop protection;
✓ how to produce quality seeds;
✓ post-harvest handling, grain quality standards;
✓ how to earn fees from input supply, aggregation
of farmers’ produce and related services.
Many VBAs graduate into village-based agro-dealers or agents for companies. This
motivates them to continue offering services to farmers after the end of a project.

9
Create a conducive environment for national and regional trade
• Promote and encourage policies favoring trade
• Promote and encourage transparent and all inclusive evidence based decision by
governments
• Develop common framework and message for the coalition of partners with which to
engage government and agree on shared priorities
Competitive, resilient and inclusive regional commodity markets and value
chains
• Cross border trade
• Structured Trading
Enhance support service markets/support functions.
• Support SMEs financially/ technical support
• Develop digital platform to enhance trade
• Promote post harvest management technologies
Markets Systems Interventions

11
11
▪ Crop disease
▪ Drought
▪ Climate change
▪ Political crises/conflicts
and Economic shocks
(such as price volatility)
▪ Floods
▪ Commodity price instability
▪ Civil unrest
▪ Environmental degradation
▪ Soil fertility decline
▪ Poor infrastructure
▪ High rates of unemployment
Resilience Interventions
Prevent, Anticipate, Prepare for, Cope with, recover fromshocks
Absorptiv
e capacity
• Assets (on andoff
farm)
• Access to other
assets (social
safety net - formal
and informal)
• Agricultural
Practices that
promoteincreased
environmental
assets
• Income and
access to food
(Diversification)
Adaptive
capacity
• Assets
(Agricultural/Non
Agricultural)
• Crop diversification
(inter-cropping,
rotation)
• Use of new
technologies
(improved seed,
blendedfertilizers)
• Use of appropriate
practices
(conservation and
climate smartagric.,
post-harvest
handling)
• Diversified markets
• Innovative financial
instruments, including
insurance
Transformativ
e capacity
• Market-ledagric.
services
• Functioning
partnerships
• Access to basic
services (Education,
health, market, Credit,
etc.)
• Institutional linkages
across sectors -
access to socialsafety
nets and agric.(formal
and informal)
• Enablinginstitutional
environment
(mitigation &
adaptation)
• Transformation of
Governance(formal
and informal)

12NAI-SRF-ManagementUpdate-20121206-PP Copyright© 2012MonitorCompanyGroup, L.P.— Confidential
In the last 11 years…….still counting.
12
15,000 FOs strengthened
5.4 million farmers aware of ISFM and 50%
of them using
600 SMEs trained and aggregated
607,000 MT of produce
Catalyzed changes in country and regional
policies
114 seed companies -602,000 MT of seed
produced; over 30,000 agro-dealers developed
Over 643 crop varieties released.
683 graduate students trained

The Knowledge Lab on Climate Resilient Food Systems: An analytical support facility
to achieve the SDGs
Margaret Karembu, Ph.D.
Director, ISAAA AfriCenter
mkarembu@isaaa.org
7th February, 2019
The Potential of Bio-innovation

Africa Population 1.216 Billion
Of these…
233 Million in sub-Saharan Africa
are Hungry/Undernourished
Food, Do we have Enough?
Crop production must increase by >70% to
feed 2.5 Billion people by 2050

Yet, we have Innovations that can
make a real Difference…

Genome Editing
Drones for Agriculture
Nanotechnology
Robotics for Agriculture
Emerging Technologies: It’s a
fast-moving world

Agricultural Biotechnology
In 2017:
67 countries adopted biotech crops
24 planted
43 imported

Climate-Smart Agriculture
Biotech crops:
→Drought-tolerant
→Salt-tolerant
→Disease-resistant
→Insect-resistant
→Water-use efficient
→Engineered Nitrogen symbiosis
→Nutrition-enhanced (Biofortification) Photo credit: geneticliteracyproject

Biotech crops and traits in the pipeline
β-carotene-enriched
Fusarium wilt, sigatoka and
bunchy top-R and β-carotene-
enriched Insect resistant
Mosaic and brown streak-R
Delayed ripening
Drought-T and yield enhancement
Less Gluten

More diverse offerings to consumers in 2017
Canada, Gen 1 and 2
Innate potatoes, 40 has.
USA, Arctic apples, 101 has
Costa Rica, Pink
Pineapple, 25 has
Bangladesh, Bt eggplant,
2,400 hectares
HarvXtra Low Lignin Alfalfa,
80,000 has (USA),
3,000 has (Canada
Canada, AquaBounty Salmon
4.5 tons

Non-browning mushrooms:
knock out of ppo gene, in the
market
Altered starch composition:
deletion of wax gene
High oil yield: gene knock
out
Reduced lignin:
Gene knock-out
Northern blight resistance:
allele replacement Reduced black spot: knock-
out ppo5 to reduce
Biotech Products Developed through New Breeding
Techniques

How has Agri-biotech Impacted Women?
✓Time-labor saving in weeding and spraying
✓Protection from harmful chemicals
including their children
✓Better quality environment
healthier foods
✓Facilitated women into gaining advanced
skills and releasing time to grow additional family food crops

Levelofdevelopment
Level of Functionality
Degree of Functionality:
Twists and Turns (Ref F.Nangayo 2017)
Long
Tedious
Painful
Many
extraneous
factors!
SEC
L&R
Co-existence
EU FACTOR

Epicenter
(5 people;
$350K Annual budget)
Europe Node
Highly Networked World
Africa Node
Myths and misinformation diffuse fast!
Example: The Seralini Study…
Information
“Alie can travel half way around the world while the truth is putting on its
shoes.”― Mark Twain (November 30, 1835 – April 21, 1910)
TODAY?
5 seconds…half of the world

Creating:
✓Fear
✓Anxiety
✓Outrage
✓Mistrust
Communication Challenge in Post-truth Era
>>Mass media sensationalism
RISK PERCEPTION VS
REAL RISKS

Conclusion
WII-FM (Shared values!)
✓ISAAA’s global knowledge sharing
initiative on Agri-biotech applications
✓Has constructed a GMO Approval
Database to document global regulatory
approvals of biotech crops in real time
✓Collaboration – African Women for
Biosciences (AWfB)
Partnership in expanding global database with
Emerging Technologies regulatory approvals?

Subscribe to…
➢A monthly e-newsletter (with >2,000 readers in
Africa & beyond)
➢Summarizes biosciences developments in Africa
➢Provide ag-biotech experts to write opinion pieces
➢Provide ag-biotech experts to feature in research mini-
documentaries
➢Support ONE section to share Climate-Smart
Technologies MONTHLY

Thank you!
Invites you to
subscribe for
Crop Biotech
Updates at:
www.isaaa.org/subscribe/ke

Powering the Rural Transformation
Claudia Ringler
International Food Policy Research Institute
Nairobi, February 7, 2019

Rural energy use changes with economic development
Barnes & Floor 1996

No Agricultural Transformation without a Supporting
Energy Sector
1) Competition between domestic and productive uses of energy
(esp. biomass) in some contexts (e.g. Ethiopia)
2) Energy as a requirement for agricultural intensification and to
support nutrient-dense crops (irrigation, mechanization,
fertilizer)
3) Electrification as a potential catalyst of supply chain
development for nutrient-dense but highly perishable irrigated
crops (vegetables and fruits)

Energy transitions affect not only agriculture but
also the environment profoundly
1) Access to clean energy for all reduces pressure on deforestation which in turn
affects agro-ecosystems, gendered time allocation and—through affecting
climate change—everyone on the globe
2) Energy access not only increases agricultural productivity, but reduces
pressure on natural resources through enabling precision-agriculture practices
(laser land leveling, soil moisture sensors, etc.) and reduces postharvest
losses through cooling, storage and transportation of perishable products
3) Access to clean energy, without a strong policy environment, can lead to
further environmental degradation (unchecked irrigation development,
groundwater depletion, overapplication of chemicals)
4) Many agricultural mitigation activities are either highly water intensive
(biofuels) or increase the risk of water depletion and degradation (solar-
irrigation)

Agricultural intensification is hampered by a lack
of energy supply for irrigation and fertilizer
0.46
0.05
0.11
0.37
0.86
0.04
0.07
0.13
0.06
0.02
0.72
0.19
0.00
0.10
0.20
0.30
0.40
0.50
0.60
0.70
0.80
0.90
Bucket Manual pump Gravity Motorized pump
(electric, petrol, diesel,
solar)
Shareofplots
Method to Obtain Water
Ethiopia Ghana Tanzania
Source: IFPRI-ILSSI Datasets, endline

Large-scale
3.2 million ha
Small-scale
14.8 million ha
Total
18.0 million ha
Source: IFPRI
Agricultural transformation will accelerate in areas
where electricity and irrigation systems are jointly sited
Irrigation potential

(a) Maize & flood irrigation (b) Vegetables & drip irrigation
Relative potential of diesel versus solar
depends on climate, crops, irrigation source
& technology and energy technology cost
Source: IFPRI

Agricultural transformation in Africa accelerates water pollution
and associated treatment costs (Ex. nitrogen loadings, absolute
2005, % growth to 2050) → need for policy instruments
Source: Xie and Ringler (2017).

What are the key energy technologies for agricultural
transformation in Africa that need to be better assessed?
▪ Solar irrigation * Cold storage * Mobile phone chargers
▪ Cooking solutions * Agro-processing * Other rural industries
(f.ex. biogas) * Health and other rural
▪ Moisture sensors services
▪ Ag chemicals
PRODUCTION POST-
HARVEST
RURAL OFF-
FARM

Leveraging new technology:
The potential of index insurance
Berber Kramer
Research Fellow, International Food Policy Research Institute (IFPRI)
The Knowledge Lab on Climate Resilient Food Systems: An Analytical Support Facility to Support the SDGs
IFPRI – AGRA workshop, Nairobi, February 7th, 2018

Presentation outline
1. How can insurance make food systems more resilient from climate change?
2. Challenges in the provision of insurance for improved risk management
3. Opportunities for satellite and smartphone-based near-surface remote sensing
4. Priority research areas in leveraging such technology

Why insurance for climate-resilient food systems?
Insurance
Ex post: Insurance payouts
Timely inflow of cash, continued investment
Ex ante: Risk reduction, confidence
Improved lending, resilient agricultural investments

Traditional indemnity-based insurance: Costly to supply
▪ High administrative costs relative to the amounts that smallholder farmers seek to insure
▪ Asymmetric information driving up insurance premiums or crowding out markets entirely:
o Moral hazard—reduced prevention as insurer cannot observe effort
o Adverse selection—selection of clients with higher expected payouts)
Index-based insurance: Difficult to generate demand and awareness
▪ Examples: Weather index-based, NDVI-based, area-yield index-based
▪ Often low demand due to basis risk, poor understanding, and limited engagement
▪ Historical data limitations and setting up data infrastructure can be expensive
Challenges in the provision of agricultural insurance

Basis risk is a widespread phenomenon in insurance
Low payout-yield correlation:
1. No payout triggered, but
farmer suffers damage: worse
outcome than if farmer would
not have paid premium
2. Payout triggered, but farmer
does not suffer damage:
raising expected payouts
unnecessarily
Source: Clarke, Mahul, Rao and Verma (2012). Weather based crop insurance in
India. World Bank Policy Research Working Paper5985
Can we leverage technology for index insurance to have the envisioned impacts?

Remote sensing through high-resolution satellite imagery
▪ Promising area with many institutions working in this space, including CGIAR (radar / weather
data, soil moisture, vegetation indices (NDVI, EVI) and flood indices)
▪ Basis risk however can remain a challenge (e.g. heat stress during flowering phase of winter
wheat)
▪ Satellite imagery offers limited transparency / tangibility (for farmers and insurance providers)
Mobile phones and smartphone technology
▪ Reducing administrative costs and crowdsourcing of information (e.g. varieties, sowing dates)
▪ Potential to provide complementary advisory services at low cost
▪ Ground pictures of insured crops, taken by farmers themselves, to improve engagement,
reduce basis risk and allow for better monitoring
Technology to address these challenges

Picture-Based Insurance (PBI): Seeing through a farmer’s eyes
✓ Taking advantage of increasing smartphone penetration in
rural areas
✓ Easy-to-understand, high farmer engagement, and reduced
basis risk
✓ Augmenting information flow to the insurer, which can be
used for monitoring and improving satellite-based indices

Research priorities
1. How to generate ground data for development and validation of insurance indices?
2. Bundling with agricultural inputs, extension, credit, aggregators, social protection?
3. What are the risks of using technology? Asymmetric information, consumerprotection
4. Impacts, particularly for groups with lower technology access/acceptance?

For more information:
Project notes and more available at: https://www.ifpri.org/project/PBInsurance
THANK YOU!

CanadaIDRC ICRDI
Internat ional Development ResearchCentre
Centre de recherches pour le developpement international
Knowledge. Innovation. Solutio
ns.
Savo
ir.
Innovation. Solutio
ns.

Gender, Social Change and Climate Resilience: Perspectives
from IDRC’sWork
Jemimah Njuki, PhD
Senior Program Specialist
Agriculture and Food Security

Interior slide
Gender, climate adaptation and resilience

Framework for a gender transformative, and climate
resilient food system

Key research question: Can a more
gender transformative approach that
addresses the underlying causes of
gender inequality lead to more
sustainable social change, food and
nutrition security and climate resilience
Integrating gender in the Farmer Field
and Business School Curriculum
• Gender dialogues on decision
making, workload sharing, GBV
• Engaging men and boys, and
traditional leaders for gender
equality
• Access to and ownership of land
• Changing harmful social norms
• Women’s leadership
Gender transformative approaches in agriculture

• Value chain to facilitate the development of business cases for risk sharing and investment for
women
• Value chain analysis reveals ‘double vulnerability’, -impacts occur simultaneously at the
business and household level and ca be interconnected.
• Create new products and services, develop new markets and develop new funding schemes
and finance mechanisms for men, women and youth
• Research shows women entrepreneurs more likely to engage in sustainable adaptation but
need to address structural disadvantages
Pathways to Resilience in Semi Arid Economies

National Steering Committee
District
District
Environment
Committee
Sub-
county
Sub-countylevel
meetings
Village
1. Climate Change Dept 1. Climate awareness
2. UNMA information
3. Wetlands Management 2. Forecasts
4. Water Resources 3. Wetland management info
Directorate 4. Water management info
1. Production 1. Agricultural advisories
2. Natural Resources 2. Environmental management
3. Water 3. Water harvesting
4. Commerce 4. Market information
5. Community Dev 5. Support and link with HHs
6. Communications 6. Overall communication
1. Community 1. Market data collection
Development Officers 2. Weather data collection
2. Weather datarecorders 3. Support project activities in
3. Local councilmembers the sub-county
1. Farmers groups
2. Local councilmembers Receive and share adaptation
3. Community leaders
(such asreligious
leaders
information with households
in the village
Village meetings;
farmer’sgroups
Level Institution Primary Role Instrument
Climate Change Adaptation and ICT (CHAI)
Project supported UNMA to produce
timely seasonal forecasts localized to
sub-county level. (prior 10 day
forecasts every 2 weeks)
Timely delivery of localized climate
information -reduced crop loss and
damage by 67% ($226 - $325 per
household per year).
Tosupport the generation, dissemination and use of adaptation information, the project
brought together national, district and village level institutions. This process was incorporated
into the routine activities of participating institutions such as the UNMA, the Climate Change
Department, and district government departments

Jemimah Njuki, PHD
International Development Research Centre
Agriculture and Food Security Program
jnjuki@idrc.ca

Information, innovation and behavior:
powering ICT-mediated extension
David J Spielman

Knowledge is power… its absence is
impoverishing
▪ Day to day, we all make decisions under constrained circumstances
o In the absence of critical information
o Failing to notice important details
o Believing things that are not true
o Relying on rules of thumb
o Reverting to our personal preferences
Poverty often exacerbates these circumstances

Late adopters
Early adopters
Innovators
time
0%
100%
Laggards
Rogers’ (1962)
adoption curve
These constraints are common in
smallholder agriculture

ICTs can enable information sharing and
behavioral change
Appeal Customizability Consistency Cost Context

ICTs are more than a pretty face
Hyperlocalization Mediation
Back-end analytics
Augmentation

And their proof is in the pudding
ICT design elements
▪ Video-enabled extension
▪ Interactive voice response services
▪ SMS reminders
▪ Tablet-based mediation
▪ Portable video projection
▪ App-based services
▪ ICT service hubs
▪ Group-based mediation
▪ Individualized mediation
What
works?
For
whom?
In what
context?
At what
cost?

Study focus: Ethiopia
Teff
Wheat
Maize
Row planting
Lower seed rate
Urea side dressing

Study focus: Uganda
Maize
Quality inputs
Improved management
Business orientation

Crop ITT
↑ over
control
Control
mean
Teff 0.06*** 36% 0.16
Wheat 0.04* 20% 0.17
Maize 0.04* 5% 0.65
60%
50%
40%
30%
20%
10%
0%
70%
Teff Wheat Maize
Control
Video
Ethiopia: Adoption, row planting

Crop ITT
↑ over
control
Control
mean
Teff 0.08*** 22% 0.37
Wheat 0.08*** 25% 0.33
Maize 0.03 - 0.51
60%
50%
40%
30%
20%
10%
0%
70%
Teff Wheat Maize
Control
Video
Ethiopia: Adoption, urea side dressing

Uganda: Intra-HH information sharing
Messenger
Male Female Couple
Recipient
Male
385 385 369
Female
385 385 369
Couple
342 342 369

Uganda: Women’s empowerment
Messenger
Male Female Couple
Recipient
Male
385 385 369
Female
342 342 369
Couple
342 342 369

Conclusion
Outcomes may vary
But small design attributes
In how we use ICTS
can influence the effectiveness and inclusivity
of agricultural extension

The Future of African Agriculture
Assessing Country Resilience
Knowledge Lab for Climate Resilient Food Systems
Prepared by the Global Futures and Strategic Foresight Group
7 February 2019

African Population in Global Perspective
(UN medium variant forecast)
3

Key Drivers: Sub-Saharan Africa Population and Income Scenarios
4

Takeaway Points
1. Africa is globally important and becoming much more so.
• Rising populations and incomes combined with high food shares and relatively high
income elasticities of demand make Africa particularly important for food and
agriculture.
2. While differences across population, emissions and atmospheric
concentrations of GHGs, and income scenarios are present by
2050, they become enormous by 2100.
6

Recent Trends in AfricanAgriculture
7

Africa has the fastest growth in cereal production of any continent
since the early 1990s
8

The growth in African cereal production over the last
decade was helped by high area growth
Source: FAOSTAT (FAO 2018).
Average for 2012-2015
Annualized growth
rates 2002-2005 to
2012-2015
Region Tons Hectares
Yield
(kg /
hect)
Product
ion
Har-
vested
area Yield
World 2,737,337,452 716,115,547 3,822 2.32 0.58 1.74
Africa 180,059,533 112,607,418 1,599 3.12 1.35 1.77
Americas 698,420,833 128,128,299 5,451 2.35 0.48 1.86
Asia 1,334,600,630 337,212,821 3,958 2.61 0.67 1.95
Europe 484,461,045 119,481,865 4,055 1.33 -0.12 1.45
Oceania 39,795,411 18,685,144 2,130 1.53 -0.12 1.66
9

With Northern Africa excluded, SSA cereal yields roseat
2.1% per year, higher than any other continent
Average for 2012-2015
Annualized growth
rates 2002-2005 to
2012-2015
Region or country Tons Hectares
Yield
(kg /
hect)
Product
ion
Har-
vested
area Yield
Africa 180,059,540 112,607,422 1,599 3.12 1.35 1.77
Sub-Saharan Africa 141,451,409 99,644,682 1,420 3.59 1.47 2.12
Northern Africa 38,608,131 12,962,740 2,978 1.56 0.47 1.09
Eastern Africa 47,959,387 31,766,940 1,510 5.43 1.74 3.68
Middle Africa 9,417,656 9,270,609 1,016 5.03 3.41 1.62
Southern Africa 28,926,097 12,339,261 2,344 2.62 -0.60 3.22
Western Africa 55,148,269 46,267,872 1,192 2.49 1.55 0.94
Source: FAOSTAT (FAO 2018).
10

Sub-Saharan Africa is essentially maize self-sufficient, but
Northern Africa imports 60% of its maize
Source: FAOSTAT Commodity Balance
This is the first time since the mid-1980s that SSA has been essentially
food self-sufficient in maize
Net
Continent Production Net Exports
Exports /
Produc-
tion
Net
Imports /
Demand
Food /
Demand
Feed /
Demand
Other /
Demand
Loss /
Demand
Africa 65,601,552 -11,730,873 NA 15.7% 55.8% 31.5% 1.3% 9.0%
Northern Africa 7,714,343 -11,587,846 NA 60.0% 34.9% 54.3% 2.0% 7.9%
Sub-Saharan Africa 57,887,209 -143,027 NA 0.3% 63.1% 23.5% 1.1% 9.4%
Eastern Africa 16,480,248 -463,143 NA 3.1% 75.7% 11.5% 0.1% 8.7%
Middle Africa 3,190,925 -423,214 NA 12.7% 61.1% 20.5% 0.0% 12.1%
Southern Africa 21,457,518 1,038,063 4.8% NA 62.2% 29.2% 0.3% 6.7%
Western Africa 16,758,518 -294,733 NA 1.7% 53.3% 27.9% 3.2% 12.7%

Maize Yield Gaps
Source: http://ebrary.ifpri.org/utils/getfile/collection/p15738coll2/id/128747/filename/128958.pdf
12
There is also substantial scope for area expansion, including irrigated area.

Tanzania: Sesame seed production and yield
0
200
400
600
800
1000
12001000
900
800
700
600
500
400
300
200
100
0
1961
1963
1965
1967
1969
1971
1973
1975
1977
1979
1981
1983
1985
1987
1989
1991
1993
1995
1997
1999
2001
2003
2005
2007
2009
2011
2013
2015
Production,000tons
Harvestedarea,000ha
Area harvested, 000 ha Production, 000 tons
0.3 0.3
0.3
0.4
0.6
1.0
0
0.2
0.4
0.6
0.8
1
1961-70 1971-80 1981-90 1991-00 2001-10 2010-16
Yield,tons/ha
13

Takeaway Points
3. African agriculture has become much more dynamic in recent decades.
4. Regional differences are important.
5. Ample scope exists to expand production, especially in SSA, through
yield increase, area increase, and/or irrigation expansion making Africa
globally important in terms of global food supply.
14

Quantitative Foresight Modeling Approach
and Key Assumptions
15

Modeling Approach:
Quantitative Foresight Modeling – IFPRI’s IMPACT Model
▪ Linked climate, water, crop and economic
models
▪ Estimates of production, consumption,
hunger, and environmental impacts
Adapted from: Robinson et al. (2015) "The International Model for Policy Analysis of Agricultural Commodities and Trade
(IMPACT); Model description for version 3". IFPRI Discussion Paper. IFPRI: Washington, DC.
16
Projections
out to 2050

Key Assumptions:
Scenario set up for foresight modeling to address key dimensions
across population and income
Primary scenarios
▪ REFERENCE:
• Climate future follows RCP8.5-HadGEM
• Population follows UN medium variant
• Per capita GDP matched to middle-of-the-road SSP2 projections including
feedback from a broader economy model of climate change impacts
▪ PESSIMISTIC (same as REFERENCE except):
• Africa population follows UN high variant
• African per capita GDP reduced by 10%
▪ OPTIMISTIC (same as REFERENCE except):
• Africa population follows UN low variant
• African per capita GDP increased by 10%
17

Key Drivers: Climate Change
18

Key Assumptions:
Scenario set up for foresight modeling to address key dimensions
across population and income
Primary scenarios
▪ REFERENCE:
• Climate future follows RCP8.5-HadGEM
• Population follows UN medium variant
• Per capita GDP matched to SSP2 projections including feedback from a
broader economy model of climate change impacts
▪ PESSIMISTIC (same as REFERENCE except):
• Africa population follows UN high variant
• African per capita GDP growth reduced by 10%
▪ OPTIMISTIC (same as REFERENCE except):
• Africa population follows UN low variant
• African per capita GDP growth increased by 10%
19

Key Drivers: Sub-Saharan Africa Population and Income Scenarios
20
Note that, in GDP terms, the scenarios offset. (GDP=GDPpc*Pop)

Another Key Driver: Agricultural Productivity
21
Productivity growth has two
components:
1) An intrinsic productivity
growth rate (IPR).
2) A yield response factor
contingent on prices.

Key Driver: Agricultural Productivity
22
Productivity growth has two
components:
1) An intrinsic productivity
growth rate (IPR). Fixed
across scenarios.
2) A yield response factor
contingent on prices.
Varies endogenously by
scenario.

23ASF F&V STAPLES CASH
REFERENCE
RANK 2010 2050
SSA 1 Wheat Vegetables
2 Rice Tropical Fruit
3 Dairy Beef
4 Vegetables Dairy
5 Tropical Fruit Banana
Top 5 net imports by value (sum of individual countries’ net imports,
includes intra-African and international trade)
REFERENCE
RANK 2010 2050
SSA 1 Cacao Vegetables
2 Tropical Fruit Yams
3 Beef Cacao
4 Vegetables Tropical Fruit
5 Cotton Plantain
Top 5 net exports by value:
individual countries regional aggregate
REFE
R
ENCE
RANK 2010 2050
SSA 1 Cacao Cacao
2 Cotton Other
3 Other Cotton
4 Beef Tea
5 Tea Groundnut

Agricultural Trade Takeaway Points
6. Income growth and urbanization drive demand, production, and trade—
dominating climate change effects to 2050.
7. Higher value products become much more important in production and
trade with intra-regional trade playing a large role.
8. Traditional cash crop exports (cacao etc.) continue to dominate SSA’s
agricultural exports to the rest of the world.
24

25
SSA
Maize production, consumption, and net trade (million metric tons)
Largely used for human consumption in SSA, but also growing needs
for supplying feed markets
-Centers of bubbles show indexed area (horizontal) and
yield (vertical) growth to 2050 in Africa for REFERENCE
(2010 = 1.0)
-Bubble sizes scaled to total regional production in 2050
-One-to-one line (red) for reference
Expansion of
maize production
dominated by
yield growth

26
SSA
Rice production, consumption, and net trade (million metric tones)
A major grain of increasing interest to African consumers AND
producers
Expansion of
rice production
dominated by
yield growth
-Centers of bubbles show indexed area (horizontal) and
yield (vertical) growth to 2050 in Africa for REFERENCE
(2010 = 1.0)
-Bubble sizes scaled to total regional production in 2050
-One-to-one line (red) for reference
13 December 2018

Population undernourished for Sub-Saharan Africa (PoU*Pop)
13 December 2018 27

Staples Production Takeaway Points
9. Staple crop production expands driven principally by yield growth
(despite the strongest possible climate change scenario) but also
substantial area expansion.
10.This growth in staple crop production is not enough to (i) satisfy demand
growth resulting in a negative net trade balance and (ii) drive down the
absolute number of people at risk of hunger.
13 December 2018 28

10 Takeaway Points
1. Africa is globally important in food demand and becoming much more so.
2. Differences across scenarios for population, income, and climate become enormous by 2100.
3. African agriculture has become much more dynamic in recent decades.
4. Regional differences are important.
5. Ample scope exists to make Africa globally important in food production.
6. Income growth and urbanization dominate climate change effects to 2050.
7. Higher value products become more important in production and trade with intra-regional trade playing
a large role.
8. Traditional cash crop exports continue to dominate SSA’s agricultural exports to the rest of the world.
9. Staple crop production expands driven principally by yield growth but also substantial area expansion.
10. This growth in production will not satisfy demand or drive down the number of undernourished people.
29

Climate Change and Energy
Yohannes Gebretsadik
International Food Policy Research Institute and AGRA
Nairobi , Kenya
Feb 7 2019
1

Hydropower resource in Africa
2Source: International Hydropower Association | Hydropower Status Report 2018
Operating 35,000 MW
Under construction 17,000 MW
Planned 77,375 MW
Technical Potential 1,800 TWh/year

Climate Change impacts on Water resources
3
Major
existing HP
Capacity
(MW)
Aswan Dam 2100
Merowe 1250
Roseires 280
Tana Beles 460
Tekeze 300
Bujagali 250
Nalubaale 380
Under
Construction
GERD 6000
Change in Runoff across Climate scenarios for main Nile flow at Aswan
Burundi
Egypt
Eritrea
Ethiopia
Kenya
Rwanda
Tanzania
Sudan
Uganda

Climate Impact- Major sub-basins
4

Remarks
Climate Change impact on hydropower generation vary by location
… Change in average Energy generation
… More extreme events more risk
Adaption
… to mitigate energy shortage
… to utilize opportunities
5

..a basin full of potentials and yet with substantial unmet needs
Access to clean drinking water
• Rural: 31 % to 72 %
• Urban: 63 % - 93 %
Food in-security
Electricity consumption
• < 160 kwh/capita
• World average: 2800
Share of
undernourished
people by sub-
region (FAO)
> 450,000
GWh/y

….facing rapid changes..
Rapid population growth
doubling every 20 – 25 years;
Fast growing economies
→ rapidly growing demands for energy, water
In a shared river basin with scarce, finite water resources
withambitiousnationalplansforwaterinfrastructure…
3,949,469
1,510,376
227,430
11,500
88,850
2,677,822
66,949 12,016
EG ET KN R W SS SU TN UG

The Strategic Water Resources Analysis
8
Key question: how to meet growing demand for
water, food and energy upstream and
downstream sustainably? How can NBI support
inter-riparian dialogue to achieve this?
Objective: inform riparian dialogue on selected (current
and emerging) challenges of transboundary water
resources management at basin and sub-basin levels
through scenario and tradeoff analyses.

Energy vs Other Demands for water: Nile
• substantial increase in irrigation water demand; for some projections > 40 % points;
9

• In the Nile Basin, if future planned WR investments are not
coordinated and optimized basin-wide, there are risks of
failing to meet the growing water demand; the deficit can grow
to over 50 percent of available water supply
=> shortage in food
=> shortage in energy
• Climate change scenarios analyzed indicate greater need for
adaptive management of the water resources to reduce
vulnerability
10
Key findings

How to utilize resource sustainably?
1. Diversity sources of water
2. Diversify energy sources: hydro, solar,
wind, geo-thermal
3. Enhance productivity of rain-fed
agriculture
4. Sustainable expansion and more efficient
water use in irrigated agriculture
5. Invest in information infrastructure
6. Put in place effective transboundary
policy and water management regimes;
7. Further develop human and institutional
capacity;
Infrastructure
Institutions
Information
Coordinated investments

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