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Foresight modeling to guide Sustainable Intensification
of Smallholder Systems
Dolapo Enahoro
Agricultural Economist, ILRI...
Road Map
 GFSF project and quantitative modeling
approach
 Overview of results and relevance to
smallholder agriculture
...
Background to CGIAR foresight analysis project
 Growth in human population, rising
incomes, natural resource degradation,...
GFSF approach to quantitative modeling
System of linked simulation models of global agriculture
• IMPACT multi-market econ...
IMPACT Model System
Climate models
Macro-
economic
trends
Crop models
Water
demand
trends
Hydrology, water
basin managemen...
Projections for Agricultural Commodities
IMPACT projections to 2050
(Rosegrant et al.,):
• Expansion in demand for meat,
d...
Results from Analysis of Promising Technologies
New virtual crops under a drier
future scenario (Robinson et al.,):
• Clim...
Relevance to Sustainable Intensification and
Smallholder Agriculture
Foresight Assessments useful for:
 discussion on pat...
Limitations of the global modeling framework
Generally:
• Expected loss of technical detail on production processes
• Dich...
Improving capacity of the modeling framework
Ongoing
 Model and data validation including using micro/meso data
 Expande...
BioSight Project on Sustainable Intensification
• Funded by CGIAR research program on Policies, Institutes and Markets
• C...
Discussion
 What can global foresight analysis contribute to systems research
relevant to sustainable intensification and...
Thank You!
GFSF Project is implemented by:
CIAT, CIMMYT, CIP, ICARDA, ICRISAT, ICRAF, IITA, IFPRI, ILRI,
IRRI, IWMI, World...
The presentation has a Creative Commons licence. You are free to re-use or distribute this work, provided credit is given ...
BioSight Project on Sustainable Intensification
• Funded by CGIAR research program on Policies, Institutes and Markets
• S...
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Foresight modeling to guide sustainable intensification of smallholder systems by Dr. Dolapo Enahoro, PIM/ILRI

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International Conference on Integrated Systems

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Foresight modeling to guide sustainable intensification of smallholder systems by Dr. Dolapo Enahoro, PIM/ILRI

  1. 1. Foresight modeling to guide Sustainable Intensification of Smallholder Systems Dolapo Enahoro Agricultural Economist, ILRI International Conference on Integrated Systems International Institute for Tropical Agriculture, Ibadan, Nigeria March 3 - 6, 2015
  2. 2. Road Map  GFSF project and quantitative modeling approach  Overview of results and relevance to smallholder agriculture  Limitations of the global modeling framework  Introduction of BioSight project
  3. 3. Background to CGIAR foresight analysis project  Growth in human population, rising incomes, natural resource degradation, and Climate Change pose challenges to global food security  Integrated modeling tools useful to assess the challenges and technology, policy and other options needed  The Global Futures and Strategic Foresight (GFSF) project provides a platform of foresight analysis useful to research, donor and policy communities  12 participating CG centers, led by IFPRI
  4. 4. GFSF approach to quantitative modeling System of linked simulation models of global agriculture • IMPACT multi-market economic model; Livestock, Fish modules • Water model • Crop simulation models (DSSAT) Long-run ex ante scenario analysis • Demand, supply and trade of agricultural commodities • Technology, investment, policy options • Climate Change effects and adaptation strategies  Quantification of qualitative scenarios with regional stakeholders  Global economic assessments of Promising Technologies • High yield, drought, heat tolerance traits in virtual crop varieties • Breed, feed and animal health solutions to livestock yield gaps
  5. 5. IMPACT Model System Climate models Macro- economic trends Crop models Water demand trends Hydrology, water basin management and stress models IMPACT multi- country, multi- market Outputs Source: Rosegrant et al., 2014 trade prices production yields harvested area
  6. 6. Projections for Agricultural Commodities IMPACT projections to 2050 (Rosegrant et al.,): • Expansion in demand for meat, dairy, cereals, livestock feeds • Higher prices of major agricultural commodities Livestock systems characterization (Herrero et al.,): • Mixed, industrial systems growing faster than pastoral • Implications for biophysical and socio-economic balances and trade-offs
  7. 7. Results from Analysis of Promising Technologies New virtual crops under a drier future scenario (Robinson et al.,): • Climate Change (CC) impacts are negative under baseline scenario • All PTs have beneficial effects on crop yields in the CC scenario • The beneficial effects strong for maize, potato, groundnut • Implications for livestock- oriented systems (not tested) • Global effects minimal in line with assumptions on adoption • Expanded (testing of) adoption of adaptation strategies important
  8. 8. Relevance to Sustainable Intensification and Smallholder Agriculture Foresight Assessments useful for:  discussion on pathways to food security given megatrends  assessing systems and regions for growth potential and response to shocks e.g., through improved production system characterization  testing the roles and ex ante impacts of candidate technologies, investments, policies  Virtual cultivars assessed under PT platform applicable to smallholder agriculture in the selected countries and regions  some trade-off assessment relevant at the macro-scale • regional competition for biomass as food, feed, energy stock • economic benefits to consumers and producers
  9. 9. Limitations of the global modeling framework Generally: • Expected loss of technical detail on production processes • Dichotomy between theory and empirics can be more marked • Data availability, consistency and aggregation issues may be more pronounced Specific to model application: • Focus on international trade and relevant commodities • Joint (production and consumption) decision-making of smallholder systems not modelled • Important crop-livestock interactions ignored • Gender dimensions largely difficult to capture
  10. 10. Improving capacity of the modeling framework Ongoing  Model and data validation including using micro/meso data  Expanded region and commodity sets  Enhanced supply-side specification to reflect heterogeneity (e.g., of livestock production systems) Proposed  Strengthen links to methodologies and tools better able to make use of micro-data (example, BioSight project)  Adapt agronomic modeling tools used to simulate virtual crops so they can better capture intensification strategies (especially w.r.t. crop-livestock linkages)
  11. 11. BioSight Project on Sustainable Intensification • Funded by CGIAR research program on Policies, Institutes and Markets • Combines biophysical and economic analysis to directly address key synergies and trade-offs of alternative ag intensification strategies • Links methodologies addressing intensification of crop and livestock production systems with environment impacts • Uses household-specific micro-data (from AfricaRISING or other); • To include aquaculture & agro-forestry production systems • Scope of analysis: farm-level mostly, with possibilities to aggregate up • Focus is on the short-to-medium term
  12. 12. Discussion  What can global foresight analysis contribute to systems research relevant to sustainable intensification and smallholder agriculture?  What can it not contribute?  What roles are there for a platform like the Global Futures and Strategic Foresights project?
  13. 13. Thank You! GFSF Project is implemented by: CIAT, CIMMYT, CIP, ICARDA, ICRISAT, ICRAF, IITA, IFPRI, ILRI, IRRI, IWMI, Worldfish; In partnership with Univ. of Florida, NARs
  14. 14. The presentation has a Creative Commons licence. You are free to re-use or distribute this work, provided credit is given to ILRI. better lives through livestock ilri.org
  15. 15. BioSight Project on Sustainable Intensification • Funded by CGIAR research program on Policies, Institutes and Markets • Scope of analysis: farm-level mostly, with possibilities to aggregate up • Combines biophysical and economic analysis to directly address key synergies and trade-offs of alternative ag intensification strategies • Links methodologies addressing intensification of crop and livestock production systems with environment impacts • Uses household-specific micro-data (from AfricaRISING or other); • Quantitative analysis set-up allows for modular linkage of production response to household consumption & economic behavior • Partnering with CG (and non-CG) analysts to create actionable policy recommendations around sustainable agricultural intensification • Plan to expand to include aquaculture & agro-forestry prodn systems • Focus is on the short-to-medium term

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