This document provides a progress report on work related to global futures and strategic foresight (GFSF) at the International Livestock Research Institute (ILRI). It highlights completed work updating parameters for livestock technologies in several countries. It outlines plans to further improve the IMPACT modeling system by validating livestock parameters and testing scenarios related to breeds, feeds, vaccines and policies. Challenges include funding cuts but opportunities exist through collaborations exploring climate change and food-feed interactions.

1. Progress Report on GFSF work at ILRI
Presented By
Dolapo Enahoro
Global Futures and Strategic Foresight Extended Team Meeting
Abitart Hotel, Rome
25 – 28 May, 2015

2. Modeling (>30% commitment)
 Dolapo Enahoro, Agricultural Economist
 Signe Nelgen, Policy Economist
 Mohamadou Fadiga, Agricultural Economist
Technologies platform (~5% time commitment)
 Ben Lukuyu (Feed Nutritionist)
 Henry Kiara (Epidemiologist)
 Julie Ojango (Genetics/Breeds Scientist)
GFSF Team at ILRI
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3. Road Map
 Overview of GFSF work at ILRI
 Highlights of completed work
 2015 updates
 Ongoing work and 2015 plans
 Prospects and challenges
 Discussion

4. Overview of GFSF Work at ILRI
Technologies
Parameterization
Livestock
Systems
Characterization
Mega-drivers,
scenarios of
investment and policy
IMPACT Model
application
Livestock
Module
Improvement
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Livestock Value
Chain Analysis
Outputs

5.  Global livestock production systems characterization (Herrero
et al., 2012)
 Promising Technologies reports (2012, 2013)
 Analysis of options for livestock development in selected
regions (McDermott et al, 2013)
 Analysis of livestock futures (Herrero et al., 2013)
 Dialogue on livestock policy analysis and modeling (Accra
Conference, November 2013)
 ILRI, IFPRI, IIASA, CIRAD, AfDB, OIE, GALVmed, ACET,
academia, government, civic society represented
 http://www.pim.cgiar.org/2013/11/18/mainstreaming-
livestock-value-chains-conference-highlights/
 Improving livestock’s specification in the IMPACT model
(Msangi et al., 2014)
Highlights of Completed Work
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6.  Report on cattle breeds and technologies in dairy systems
(Ojango and Wasike, January 2015)
 Burkina Faso, Kenya, Tanzania
 India
 Nicaragua
 Reports on livestock feeds’ use and availability and feed
technologies (consultant-led study, March 2015)
 Burkina Faso, Ethiopia, Tanzania, Uganda
 India, Vietnam
 Nicaragua
 Reports on cattle ECF and small ruminant PPR diseases
and vaccines development (consultant-led study, May 2015)
 Burundi, Kenya, Tanzania, Rwanda, Uganda
 Congo (Dem, Rep.,), South Sudan
 Malawi, Mozambique, Zambia, Zimbabwe
2015 Update: Parameters of Livestock Technologies
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7. 7
Table 1. Milk productiona
performance in
Tanzania
Country Production system Genotype Ave. DMY
Tanzania
Mixed
Crossbred
cattle,
Mpwapwa
5.42
Extensive
Tanzania
shorthorn
zebu x Exotic
crosses
3
Medium scale
dairy
Exotic x
indigenous
crosses
7
Smallholder
system
Exotic x
indigenous
crosses,
purebred
exotic
5.6
a
Ave. DMY= average daily milk yield in litres
Extensive
rangeland/
Mixed Crop-
Livestock
system
98%
Intensive
system
2%
Figure 2. Cattle population by production system,
Tanzania
Source: Ojango et al., in prep.
Update: Some data on Livestock breeds

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Update: Some data on Cattle ECF disease
Figure 3: Map of Africa showing countries in which ECF is endemic
Country Morbidity Case fatality
(%) (%)
Congo (DRC) 0.58 10.26
Kenya 35.25 5.98
Mozambique 1.96 67.57
South Sudan 5.06 34.38
Sudan 4.62 40.63
Tanzania 1.51 10.69
Uganda 16.3 12.35
Zambia 6.68 19.78
Zimbabwe 1.1 32.76
Source: Franco-Dixon et al., in prep.
Table 2: ECF morbidity and mortality

9.  Follow-up on improved livestock specification work
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2015 Update: IMPACT-Livestock Model Improvement
Source: Msangi et al., 2014

10. 2015 Plans: Parameters of Livestock Technologies
 Update database of livestock productivity and production
parameters and ensure IMPACT-compatibility
 Apply data to validation exercise on IMPACT model
(livestock) parameters
 Data will be applied to livestock scenarios testing in IMPACT
 Single technology runs in multiple countries
 Joint technology runs where appropriate
(Examples):
• Livestock breeds and feed improvement in India
• Breed, feed and vaccine development in Tanzania
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11. 2015-6 Plans: IMPACT Livestock Model application
 Model testing and validation
 Context-setting to livestock value chains (LVC) targeting
 Scenarios development in consultation with experts on:
• Genetics, feeds, animal health and other technologies
(ongoing)
• Livestock value chain activities and development
• Livestock-environment interactions
• Climate Change effects on livestock production
• National policies influencing livestock development and
how these are evolving
 Improve welfare indicators and interpretation of the results to
better reflect
• Livestock’s role in pro-poor development
• Country-specific gender and agriculture relations
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12.  Renewed interest in foresight analysis and in its role in R&D
and investment decision-making
 Global funding cuts pose practical challenges to project
operation
 Active collaboration on scenarios development holds much
promise for quality of our outputs
 Joint testing of food-feed grain variety improvements
 Joint modelling of CC effects on food-feed sources and
interactions with livestock
Prospects, Challenges and Ideas to Explore
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13. Discussion
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14. Acknowledgements
The GFSF project at ILRI has benefited from the support of :
• The Bill and Melinda Gates Foundation
The CGIAR Research Programs on:
• Policies, Institutes and Markets
• Climate Change, Agriculture and Food Security
• Livestock and Fish
And from research collaboration with:
• IFPRI IMPACT Team
• P. Havlik (International Institute for Applied Systems Analysis, IIASA)
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