Mark W. Rosegrant IFPRI Washington DC, USA

1. Scenario Development for International Assessment of Agricultural Science and Technology for Development (IAASTD) Mark W. Rosegrant IFPRI Washington DC, USA

2. Overview of the Talk • What is IAASTD? • What are scenarios and why use them? • Proposed approach for IAASTD scenarios • Overview of IMPACT global food and water model • Knowledge, Science and Technology (KST) in scenario modeling Page 2

3. IAASTD: Overarching Question “How to reduce hunger and poverty, improve rural livelihoods, and facilitate equitable, environmentally, socially and economically sustainable development through access to, and use of agricultural knowledge, science and technology”? Page 3

4. IAASTD: Four Broad Questions • What are the challenges that can be addressed through agricultural KST? • What are the likely positive and negative consequences of agricultural KST? • What are the enabling conditions required to optimize the uptake and diffusion of agricultural KST? • What investments are needed to help realize the potential of agricultural KST? Page 4

5. IAASTD Characteristics Structural features: • Intergovernmental process, with a multi-stakeholder Bureau • Co-sponsored by seven international agencies – FAO, GEF, UNDP, UNEP, UNESCO, World Bank, and WHO • Based on an international consultative process and well-defined user needs • Prepared and peer-reviewed by hundreds of experts from all stakeholder groups Substance features • Multi-thematic (nutritional security, livelihoods, human health, environmental sustainability) • Multi-spatial using a consistent framework • Multi-temporal (now to 2050) employing plausible futures • Integrates indigenous and institutional knowledge • Assesses scientific knowledge and the effectiveness of institutions and policies Page 5

6. IAASTD Conceptual Framework • Human Impacts on: • Incomes and employment • Hunger • Human health • Resilience and vulnerability • Social and Gender Equality • Economic diversification • Rural livelihoods • Quality of natural environment • Social Stability • Indirect change drivers • Economic • Demographic (urbanization, migration) • Socio-political (policies and institutions) • Cultural and ethical (values) • Global KST • Direct change drivers • Biodiversity loss • Volume and pattern of demand • Consumption patterns • Labor availability • Land and water availability • Agricultural policy and regulatory environment • GHG emissions and Climate change • Farmers decisions • Agricultural goods and Services • Food production • Fiber, oils, material • Biomass/energy • Medicines • Landscape and environmental management • Carbon sequestration • Agro-ecosystem function • Agricultural KST • New knowledge (including policies) • New technologies (biological and non-biological) • Harnessing/Maintenance/adaptation • of indigenous knowledge • Effective knowledge exchange systems • KST system responsiveness & adaptability • KST system accountability

7. What are Scenarios and Why Use Them? • Scenarios are stories about the future with a logical plot and narrative governing the manner in which events unfold • Purpose of scenarios: • Information dissemination • Scientific exploration • Decision-making tool • Types of scenarios • Exploratory vs. anticipatory scenarios • Baseline vs. policy scenarios • Qualitative vs. quantitative scenarios, or a combination Page 7

8. IAASTD Approach to Scenarios • Structured accounts of possible futures • Describe futures that could be, rather than futures that will be • Alternative, dynamic stories that capture key ingredients of our uncertainty about the future of our study system • Constructed to provide insight into drivers of change, reveal the implications of current trajectories, and illuminate options for action • Encompass quantitative models and realistic projections, but much of their value lies in incorporating both qualitative and quantitative understandings of the system and in forcing people to evaluate and reassess their beliefs and assumptions about the system • What are the consequences of plausible changes in development paths for hunger, poverty alleviation, human health, and the environment? Page 8

9. Scenario Development Process for IAASTD • Procedure builds from MA approach and Intergovernmental Panel on Climate Change (IPCC) methodology • Integrates qualitative and quantitative scenarios • Qualitative – understandable way to communicate complex information, considerable depth, comprehensive feedback effects and incorporate a wide range of views about the future • Quantitative – check the consistency of qualitative scenarios, provide relevant numerical information and “enrich” qualitative scenarios by trends and dynamics Page 9

10. Scenario Development Framework • Two essential activities • Formulation of alternative scenario storylines • facilitates internal consistency of different assumptions • takes into account broad range of elements and feedback effects • Quantification • helps provide insights into those processes where sufficient knowledge exists to allow modeling • takes into account interactions among various drivers and services Page 10

11. Proposed IAASTD Procedure for Developing Scenarios – Three Phases Page 11

12. Proposed IAASTD Procedure for Developing Scenarios – Three Phases Page 12

13. Proposed IAASTD Procedure for Developing Scenarios – Three Phases Page 13

14. Drivers and Outputs • Population development – total population and age distribution in different regions • Economic development – assumed growth of GDP per region and changes in economic structure • Technology development – covers many model inputs such as rate of improvement in the efficiency of domestic water use, or the rate of increase in crop yields • Demand—dietary preferences and dynamics of change • Human behavior –willingness of people to invest time or money in energy conservation or water conservation • Institutional factors – existence and strength of local, national, and global institutions to promote education, international trade and international technology transfer • International technology transfer – represented directly (e.g. trade barriers, import tariffs) or indirectly (e.g. income elasticity for education) Page 14

15. Four Forward-looking Scenarios Environmentally reactive Order from Strength Global Orchestration globalized fragmented Techno Garden Adapting Mosaic Environmentally pro-active Page 15

16. Global Orchestration Focus on macro-scale policy reform for environmental sustainability Page 16

17. Order from Strength Retreat from global institutions, focus on national regulation and protectionism Page 17

18. Adapting Mosaic Retreat from global institutions, focus on strengthened local institutions and local learning Page 18

19. Techno Garden Emphasis on development of technologies to substitute for ecosystem services Page 19

20. Model Outputs Provisioning Services - Food (meat, fish, grain production) - Fiber (timber) - Freshwater (renewable water resources & withdrawals) - Fuel wood (biofuels) Regulating - Climate regulation (C flux) - Air quality (NOx, S emissions) Supporting primary production IMPACT World food production Model Inputs Demographic Economic Technological AIM Global change IMAGE 2 Global change WaterGAP World water resources Storylines Global Orchestration, Techno Garden, etc. Modeling to Quantify Parts of the MA scenarios

21. Population Growth

22. Income Growth (GDP/cap/year)

23. Sample Qualitative Scenarios for IAASTD • Intensive agriculture – emphasis on • Intensive agriculture • Economic growth • Public goods • Low input agriculture • Low-input agricultural technology • Adaptive ecosystem targeting • Agricultural science and technology targeted to ecosystems • Indigenous technology and participatory breeding • Rates of change in dietary preferences • Convergence to Western diets, decline in Western meat demand, acceptance of biofortication Page 23

24. KST within a Policy Modeling Framework • “K” - different from “S” and “T” - latent and not easily measured • KST - hard to separate due to obvious feedbacks • Observing “S” & “T” • in cross-section can be used to construct a “possibility frontier” – additional models • observe over time to identify trends and underlying drivers Page 24

25. How to Account for Knowledge • Knowledge - embodied in • education (for the general population) • agricultural extension • Indigenous knowledge • Agricultural extension - has direct effects on crop productivity and yields • Education – • enhance overall labor productivity (not only in agriculture) • positive effects in nutrition outcomes (through malnutrition work) Page 25

26. Should we Endogenize Science and Technology ? • Keeping ST exogenous - allows one to look at clear counter-factual comparisons and scenarios • Endogenizing ST – may restrict the range of investment scenarios that can be examined • Not clear if necessary length of data over time is available to properly specify an endogenous relationship for Science and Technology Page 26

27. Science and Technology in Scenarios SUPPLY SIDE • Changes in rainfed and irrigated area growth for crops • Changes in rainfed and irrigated yield growth for crops • Changes in numbers and yield growth for livestock • Changes in production growth for 4 types of fisheries commodities (high value vs. low value) Page 27

28. Science and Technology in Scenarios DEMAND SIDE • Changes in dietary preferences over time (leading to changes in kilocalorie composition) – disaggregation to the potential impact of micronutrient breeding Page 28

29. Science and Technology in Scenarios ALSO • Estimation of the impact of • biosafety and biotechnology regulations and phyto-sanitary restrictions • changes in supply and demand on child malnutrition • crop yields from climate change • Subsidies, taxes, tariffs and other trade restrictions Page 29

30. Spatially Disaggregating Impact of KST-related investments on productivity growth, can be better captured with the following disaggregations: • Greater spatial resolution for production of food and water allocations • Disaggregation of crop categories to explicitly model dryland crops • Differentiation between high and low-input rain-fed agriculture • Disaggregation among GMO and non-GMO options Page 30

31. The Education-Nutrition Relationship in IMPACT-WATER • Malnourished children are projected as follows: • %MALt= - 25.24 * ln (PCKCALt) - 71.76 LFEXPRATt • - 0.22 SCHt - 0.08 WATERt • NMALt = %MALt x POP5t • %MAL = Percent of malnourished children • PCKCAL = Per capita calorie consumption • SCH = Total female enrollment in secondary education as a % of the female age-group • LFEXPRAT = Ratio of female to male life exp. at birth • WATER = Percent of people with access to clean water • NMAL = Number of malnourished children, and • POP5 = Number of children 0 to 5 years old Page 31

32. How to Account for Investments • Current model framework examines the impact of investments made in • Roads • Irrigation • Schools • Safe water • Agricultural technology • Can further disaggregate agricultural technology investments to account for GMO and non-GMO technologies, drought/salt tolerant variety breeding, etc. Page 32