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Foresight modeling to guide sustainable intensification of smallholder systems

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Foresight modeling to guide sustainable intensification of smallholder systems

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Presented by Dolapo Enahoro (ILRI) at the international conference on Integrated Systems Research for Sustainable Intensification in Smallholder Agriculture, Ibadan, Nigeria, 3-6 March 2015.

Presented by Dolapo Enahoro (ILRI) at the international conference on Integrated Systems Research for Sustainable Intensification in Smallholder Agriculture, Ibadan, Nigeria, 3-6 March 2015.

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Foresight modeling to guide sustainable intensification of smallholder systems

  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  Background to GFSF project  Approach to quantitative modeling in GFSF project  Some results and relevance to sustainable intensification of agricultural systems  Limitations of the global modeling framework  Links to farm level approaches and introduction of BioSight project  Discussion
  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-country, multi-market economic model • Water model (hydrology, water basin management, crop water stress) • Crop simulation models (DSSAT); • Livestock, Fish modules Long-run ex ante scenario analysis • Demand, supply and trade of agricultural commodities • Technology, investment, policy options • Climate Change effects and adaptation strategies 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. 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.,): • Significant (growing?) yield gaps • Mixed, industrial systems growing faster than pastoral • Implications for biophysical and socio-economic balances and trade-offs
  6. 6. 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
  7. 7. Relevance to Sustainable Intensification and Smallholder Agriculture Foresight Assessments useful in:  discussion on pathways to food security in the future  bridging local and global dynamics e.g., through the improved disaggregation plus international trade features of the models  testing the roles and ex ante impacts of candidate technologies, investments, policies  Virtual cultivars assessed under PT platform directly applicable to smallholder agriculture in the selected countries and regions  assessing systems and regions for growth potential and response to shocks e.g., through improved production system characterization  some trade-off assessment relevant at the macro-scale • regional competition for biomass as food, feed, energy stock • natural resource issues related to intensification • economic benefits to consumers and producers
  8. 8. 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; resources and coordination typically more involving Specific to model applicability: • Focus is on international trade and relevant commodities • Joint (production and consumption) decision-making characteristic of many smallholder systems not captured • Important crop-livestock interactions, production-environment linkages not captured • Gender dimensions largely difficult to capture
  9. 9. Improving capacity of the modeling framework Ongoing  Model and data validation including using micro/meso data  Expanded country, region and commodity sets  Enhanced supply-side specification to better 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)
  10. 10. 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 and links 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 • Scope of analysis: farm-level mostly, with possibilities to aggregate up • Plan to expand to include aquaculture & agro-forestry prodn systems • Focus is on the short-to-medium term • Partnering with CG (and non-CG) analysts to create actionable policy recommendations around sustainable agricultural intensification
  11. 11. Discussion  What can global foresight analysis contribute to the research for impact agenda on sustainable intensification of agriculture?  What can it not contribute?  What role is there in the research for impact portfolio on Sustainable Intensification and Smallholder Agriculture, for a platform like the Global Futures and Strategic Foresights project?
  12. 12. Global Futures and Strategic Foresights Project is supported by: Bill and Melinda Gates Foundation CGIAR research program on Climate Change, Agriculture and Food Security (CCAFS) CGIAR program on Policies, Institutions and Markets (PIM) In Collaboration with: The University of Florida; national research systems (various) Acknowledgements
  13. 13. Thank You! GFSF Project is implemented by: CIAT, CIMMYT, CIP, ICARDA, ICRISAT, ICRAF, IITA, IFPRI, ILRI, IRRI, IWMI, Worldfish
  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

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