Quantitative foresight modeling to inform prioritization - Keith Wiebe
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1. The Global Futures and Strategic Foresight program aims to improve quantitative modeling tools to inform priority setting in the CGIAR through scenario analysis and impact assessment. 2. The program involves all 15 CGIAR centers and other partners in building an integrated modeling framework and stronger community of practice for foresight. 3. The objectives are to improve modeling tools, strengthen the foresight community, improve assessments of alternative global futures, and inform research, investment, and policy decisions through collective scenario analysis.
Quantitative foresight modeling to inform prioritization - Keith Wiebe
- 1. Quantitative foresight modeling to inform prioritization Keith Wiebe, IFPRI and GFSF ISPC, Rome, 15 September 2015
- 2. Outline • Introduce the Global Futures & Strategic Foresight (GFSF) program • Provide an update on discussions with partners and donors • Reflect on how we might help inform decision making in the CGIAR
- 3. Key points • Not one center alone, but all 15 CGIAR centers (and other partners) • Not just individual technologies, but broader scenarios • Not model results alone, but as one input among several to inform decision making by others • Not one-time results, but building capacity and a framework to continue assessing options over time
- 4. Objectives 1. Improved system of integrated biophysical and economic modeling tools 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
- 5. All models are wrong, but some are useful -- George Box and Norman Draper (1987)
- 6. 1. Improved modeling tools • Complete recoding of IMPACT version 3 • Disaggregation geographically and by commodity • Improved water & crop models • New data management system • Modular framework • Training
- 7. 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, …
- 8. • Role of agricultural technologies • Africa regional reports • Analyses by CGIAR centers • CCAFS regional studies • AgMIP global economic assessments 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
- 9. Source: Nelson et al., PNAS (2014) 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
- 10. Promising CGIAR technologies Crop Center Trait Countries (Region) Final Adoption Maize CIMMYT Drought tolerance Angola, Benin, Ethiopia, Ghana, Kenya, Malawi, Mozambique, Uganda, United Republic of Tanzania, Zambia, Zimbabwe (M1) 30% Heat tolerance Bangladesh, India, Nepal, Pakistan (M2) 30% Wheat CIMMYT Drought tolerance Iran, Turkey (W1) 35% Heat tolerance India, Pakistan (W2) 30% Drought and heat tolerance Argentina, South Africa (W3) 30% Potato CIP Drought tolerance Bangladesh, China, Kyrgyzstan, India, Nepal, Pakistan, Tajikistan, Uzbekistan (P1) 4-40% Heat tolerance 4-40% Drought and heat tolerance 4-40% Sorghum ICRISAT Drought tolerance Burkina Faso, Eritrea, Ethiopia, India, Mali, Nigeria, Sudan, United Republic of Tanzania (S1) 20-80% Groundnut ICRISAT Drought tolerance Burkina Faso, Ghana, India, Malawi, Mali, Myanmar, Niger, Nigeria, Uganda, United Republic of Tanzania, Viet Nam (G1) 40-60% Heat tolerance 40-60% Drought and heat tolerance, high yielding 40-60% Cassava CIAT Mealybug control methods China, India, Indonesia, Lao People’s Democratic Republic, Myanmar, Thailand (C1) NA Source: Islam et al. (draft)
- 11. Yield impacts of selected technologies under climate change (percent difference from 2050 CC baseline without the new technologies) Source: Islam et al. (draft)
- 12. 4. Informing decision making • National partners • Regional organizations • International organizations and donors • CGIAR • Centers • CRPs • System?
- 13. Discussions with donors and partners • IFAD proposal (February 2015) • PIM, Gates, CCAFS (on-going support) • GFSF partners (continuing engagement) • AgMIP partners (continuing engagement) • USAID? (under discussion)
- 14. Scenarios • Baseline • Changes in population, income, technology • Shared Socioeconomic Pathways (SSPs) • Changes in climate • Representative Concentration Pathways (RCPs) • Drawing on work with AgMIP
- 15. 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 eq. (ppm)Radiative forcing (W/m2) Population (billion) GDP (trillion USD, 2005 ppp)
- 16. Climate change impacts in 2050 Climate change impacts on global yields, area, production, consumption, exports, imports and prices of coarse grains, rice, wheat, oilseeds and sugar in 2050 (% change relative to 2050 SSP2 baseline values) Source: Wiebe et al. (Environmental Research Letters, 2015)
- 17. Scenarios • Baseline • Changes in population, income, technology • Shared Socioeconomic Pathways (SSPs) • Changes in climate • Representative Concentration Pathways (RCPs) • Drawing on work with AgMIP • Alternative • Broadly reflective of alternative CGIAR options? • Different geographic emphases? • Different commodity group emphases? • Other criteria? • How many?
- 19. Model improvements under way • Livestock and fish • Nutrition and health • Variability • Poverty • Land use • Environmental impacts
- 20. SLO 1: Reduced poverty IDO Sub-IDO IMPACT Model capability Increased resilience of the poor to climate change and other shocks Reduced production risk Consideration of variability and impact of extreme events on crop yields, production and market prices Enhanced smallholder market access Reduced market barriers Current model includes marketing margins and subsidies/taxes, with updated data. Model does not include different farm sizes. Increased incomes and employment Increased value capture by producers More efficient use of inputs Soft-linking IMPACT to a global CGE model Water, fertilizers as a result of changes in technologies Increased productivity Closed yield gaps through improved agronomic and animal husbandry practices Increased access to assets, including natural resources Reduced pre- and post- harvest losses, including those caused by climate change Major focus of the current model Changes in investments in irrigation reflected; some investments in land restoration reflected; More detailed welfare analysis feasible with a linked global CGE model. Some pest management loss reductions as they relate to climate change can be reflected
- 21. SLO 2: Improved food and nutrition security and health IDO Sub-IDO IMPACT Model capability Increased productivity (see SLO 1) (see SLO 1) Increased dietary quality for vulnerable groups Increased availability of diverse, nutrient-rich foods Increased access to diverse nutrient rich foods Estimates of the impact on population at risk of hunger and number of malnourished children. Supply of nutrients is included as a separate module linked to the current model. Trade of nutrient-rich foods is part of the model Improved food safety Not included in the model. Not included in the model. Improved human and animal health through better agricultural practices Improved water quality IMPACT has an associated water quality model for N, P and BOD
- 22. SLO 3: Improved natural resource systems and ecosystem services IDO Sub-IDO IMPACT Model capability Natural capital enhanced and protected, especially from climate change Land, water and forest degradation(including deforestation minimized and reversed Enhanced conservation of habitats and resources IMPACT has an associated water quality model for N, P and BOD; separate linked models for carbon stock and GHG emissions and land use change available. Changes in agricultural land area is part of the model. No work on habitat quality, however. Enhanced benefits from ecosystem goods and services More productive and equitable management of natural resources Agricultural systems diversified and intensified in ways that protect soils and water Separate linked models will be used to estimate impacts on water use and water quality, land use change, carbon stock and greenhouse gas emissions, and biodiversity Major focus of the current model together with linked modules More sustainably managed agro- ecosystems Increased resilience of agro- ecosystems and communities, especially those including smallholders Enhanced adaptive capacity to climate risks Reduced net GHG emissions from agriculture, forests and other forms of land use Linked module available to compute GHG emissions from agro-ecosystems and land-use change and other sustainability indicators (see previous IDO). Consideration of resilience to extreme events and policy responses (e.g., use of buffer stocks).
- 23. To conclude • Summary – GFSF, discussions, how to contribute? • Conclusions – 4 key points • Collective effort • Appropriate scale of analysis • One input among many, to inform • On-going effort • Institutional considerations & managing expectations • Questions • What scenarios? (baseline and alternative) • What indicators? (IMPACT standard, IDOs, sub-IDOs) • What process? (scenario definition, discussion of results)