Rosegrant Scenarios final

IAASTD SCENARIO WORKING GROUP --- STATUSMay 3, Bangkok meeting: 

IAASTD SCENARIO WORKING GROUP --- STATUS May 3, Bangkok meeting

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Scenario Chapters and Names Suggestions for AM+ and GO+ Chapter 4 - Framework Chapter 5 – Storylines for Future Scenarios Detailed chapter outline - Ch 6 Brief model descriptions & model interactions Quantitative output indicators First set of results of reduced set of models OUTLINE

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SCENARIO CHAPTERS Chapter 4 – Framework: Drivers, Plausible Futures, & Modeling Tools Chapter 5 - Storylines (to 2050) Chapter 6 - Storyline/scenario outputs & analyses, interpretation and synthesis of outputs

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GO : Policy and Markets AM : Local Learning TG : Green Technologies OS : Self Sufficiency / Sovereign Interest SCENARIO NAMES (suggested)

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SUGGESTION FOR AM+ AND GO+ GO+ Implementation of CC policies & other policies to reverse environmental degradation better distribution, even more inverse on health & education more infrastructure lower meat demand Environmentally and equity conscious growth Labor compacts Certification Reduced meat elasticities AM+ Implement highest GDP and lowest POP [or TG] Trade liberalization? Higher AST [agricultural productivity growth] More rapid technology development without environmental degradation

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AM+ and GO+ might converge in some key outputs while retain individual flavours To accomplish this in both storyline and quantification - important to track key indicators for human well-being environmental outcomes SUGGESTION FOR AM+ AND GO+

Chapter 4 : Framework: 

Chapter 4 : Framework Provide a basis to the scenario work Rationale for choices made in Chapter 5, 6 Assessing literature on trends that directly or indirectly influence agriculture development/AKST (drivers)

Lay out of Chapter 4: 

Lay out of Chapter 4 4.1 Scenario-based assessment Why? Uncertainty does not allow us to make forecast – but still exploring trends under ‘what if’ conditions is very relevant Why use MA scenarios as a basis Most up-to-date global scenario assessment Comprehensive scenarios MA found agriculture to be one of the most important factors both in improving human-wellbeing and causing ecological stress

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What are the consequences of plausible changes in development paths for ecosystems and their services over the next 50 years and what will be the consequences of those changes for human well-being?

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Development & Sustainability Goals • Decreased hunger and poverty • Improved nutrition and human health • Sustainable economic development • Enhanced livelihoods and equity • Environmental sustainability Indirect Drivers • Economic (demand, markets,..) • Demographic (urbanization,..) • Education, Culture, Ethics • Sociopolitical • Infrastructure • Science and Technology • Agricultural KS&T Direct Drivers • Availability, & management of natural resources, inc. land and water, and biodiversity • Climate change • Labor • Energy • AKST use Access, control & distribution - Extension / Dissemination - Credit/Capital/Assets - Access/Knowledge markets - Inputs, such as agro - Strategies and interventions Research Policy IPR Local & institutional generation of AKST Strategies and Interventions Strategies and Interventions Strategies and interventions chemicals CONCEPTUAL FRAMEWORK

Lay out of the chapter: 

Lay out of the chapter 4.2 Development of indirect drivers Economic Population Socio-political Education Science and Technology development 4.3 Development of direct drivers Consumption patterns Land use Natural resources Energy Climate change and air pollution 4.4 Development of agricultural production systems and AKST adaptation 4.5 Review of available tools for modelling

Identify and contrast characteristics of Agriculture-Food Systems and AKST in four scenarios to 2050: 

Identify and contrast characteristics of Agriculture-Food Systems and AKST in four scenarios to 2050 Characteristics of 2 Axes Major actors and organizations Typical structures Key characteristics of AKST Other issues Chapter 5: Storylines for Future Scenarios

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Global Regional Proactive Reactive Trade Liberalization, Decreases in Agricultural Protectionism Trade Restrictions, Maintaining national or regional protections Adapting Mosaic Techno Garden Global Orchestration Order from Strength

Major Actors : 

Major Actors Global Regional Proactive Reactive International market focus Multinational corporations and cooperatives International market focus Multinational corporations Small startups International regulators Focus on national and trading block markets State trading companies National corporations Focus on local & regional markets Small businesses & coops Coordination through networks

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Global Regional Proactive Reactive Structure Focus on food High factor productivity Vertical integration from farm to table High supply chain efficiency Low diversity in production systems Focus on food and food security Lower factor productivity Lower supply chain efficiency due to emphasis on security Less diversity and quality in available food products Focus on ecosystem services Payments for ecosystem services Vertical integration High supply chain efficiency More diversity in production systems Focus on ecosystem services & food quality Local adaptation provide ecosystem services Horizontal supply integration through local/regional markets Diversity in production systems & higher quality in available food products

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Focus on efficiency Major driver is market incentives for food Multinationals conduct applied R&D,extension Public-private partnerships for upstream research Strong IP protection Knowledge generation through formal research structures Focus on systems Major driver is quality of life Decentralized organizations partner with local producers, processors, sellers IP protection relaxed Knowledge generation through action and adaptive research AKST Global Regional Proactive Reactive

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AKST Focus on technology Major driver is market incentives for ecosystem services Global networked research organizations conduct upstream research on ecosystem services Strong IP protection but more emphasis on public goods Start up companies do development, new product extension Focus on productivity Major driver is food self-sufficiency National universities & governments conduct basic & applied research & extension Fewer resources IP protection weakened Knowledge generation through formal research structures Global Regional Proactive Reactive

Other Issues, Storylines: 

Other Issues, Storylines What happens to small farmers Innovations Incorporating more regional specificity Cross cutting issues Shocks Climate change

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DETAILED OUTLINE, CHAPTER 6 6.0) Quantification of Drivers and Qualitative/Quantitative Modeling Tools Chosen 6.1) Implications of AKST Across the Scenarios 6.2) Implications for Human Well-Being, Poverty and Equity 6.3) Implications for HWB - Hunger and Food Security 6.4) Implications for HWB - Water [maybe delete] 6.5) Implications for Environmental Sustainability 6.6) Synergies and Tradeoffs - Sensitivity analysis for GO/AM based on synergy and trade-off description

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BRIEF MODEL DESCRIPTION Exogenous variables – population, world economy, agricultural economy (from IMPACT) Other variables – yield gap, food and feed demand (from IMPACT), livestock (regional; IMAGE gets animal production from IMPACT) Output – land-use, crop productivity (7 types), potential productivity Model related – pasture land, forestry model iteration, soil degradation, biofuels, fertilizer, biodiversity IMAGE MODEL

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BRIEF MODEL DESCRIPTION Based on optimization, market clearing Regions linked through trade and investment flows (18 regions) Emissions (CO2, methane, NOX) by source (fertilizer use, livestock, agriculture) Land-use allocated by demand (18 agro-ecological zones in GTAP) Outputs – emissions by source, land-use allocated by demand GTEM-CGE MODEL

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BRIEF MODEL DESCRIPTION Inputs – agricultural crops, prices, trade, output at the global level for each sector (public, private, services, fertilizer, other manufacturing) Exogenous – rural poor non-agricultural/agricultural, urban poor, non-poor non-agricultural/agricultural, urban non-poor Shocks – labor supply, agricultural productivity, investments Outputs – casual and agricultural workers (M and F), GDP, supply of labor, gender distribution GENDER-CGE MODEL (G-CGE, India)

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BRIEF MODEL DESCRIPTION Overview Currently linked with GTAP Several iterations to other CGE and Partial equilibrium models Better than GTAP as it is more disaggregated 19 commodities 31 regions Input variables - land-use changes/agricultural land-use from IMAGE, wages, fertilizer (international and domestic) from GTEM, international community agricultural prices, GDP and technology factor from IMPACT, fisheries (total fish from fish model), no fisheries, rural-urban projections from IIASA Output - crop production figures to IMPACT, production, trade, demand/ disaggregated demand, domestic price, regional incomes CAPSIM MODEL

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BRIEF MODEL DESCRIPTION Detailed partial equilibrium model of agricultural sector with exogenous capital growth Highly disaggregated agricultural commodities (39 commodities: including cereals, soybeans, roots & tubers, meats, milk, eggs, oils, oilcakes & meals, sugar & sweeteners, fruits & vegetables, and fish) Disaggregated spatial allocation of crop production at sub-national level (281 units) Details on physical use of land and water, trade policies, with resulting international trade World food prices are determined annually at levels that clear international commodity markets Iterative year-by-year demand, supply, trade equilibration Output indicator – calorie availability, PC malnutrition, PC water consumption, yield growth and total production, area IMPACT-WATER MODEL

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BRIEF MODEL DESCRIPTION Overview Ecosystem based model 2 phased, 19 FAO areas (no political boundaries associated with the regions) 42 trophic groups per area Input data – trophic level, existing databases on marine mammals, FAO landings database, fish product demand, changes in prices, CC, DD from IMPACT Output - fish production in the 19 FAO areas, total landings, value of landings, labor, landing diversity indicators, marine trophic index [later?] Notes: Model is driven by “effort” (synonymous with demand) Demand figures obtained from IMPACT - knowing where demand may be would allow EO to change effort in one on the 19 areas ECO-OCEAN MODEL

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Land use change Population Macroeconomy AKST Investments Energy/Biofuels Fertilizer Food Supply, Demand, Trade Productivity Human Well- being Water Other inputs Climate Biodiversity (pollinators) Ozone (tropospheric) Acidification N-deposition CAPSIM – Partial ag eq model, China CGE-G – Gender-differentiated CGE, India IMAGE – Integrated Assessment Model IMPACT-W Partial ag eq model and water simulation GTEM – Global CGE Livestock growth models GTM – Forest land use and timber demand ECO-Ocean Fisheries model Environ-mental Outcomes Forest

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MODEL OUTPUT INDICATORS

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MODEL OUTPUT INDICATORS

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MODEL OUTPUT INDICATORS

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Drivers: Review of drivers, decision on what can be quantified/remains qualitative; Population and Income Growth [from MA]; technology change, based on MA used for first set of results; Results: Based on two global models (IMPACT and IMAGE) KEY QUANTIFIED DRIVERS & SELECTED RESULTS

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Population Growth

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Per Capita Income Growth

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Meat Production - GO and TG Scenarios

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Grain Production - GO and TG Scenarios

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Meat Demand - GO and TG Scenarios

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Total Per Capita Grain Demand and Food Grain Demand - GO and TG Scenarios

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World Food Prices – GO and TG Scenarios

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World Food Prices – GO and TG Scenarios

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World Food Prices – GO and TG Scenarios

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IMAGE as part of quantitative group Change in GDP, population & others (i.e. scenario assumptions) MA (but possibly checked by CGE) IMPACT

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MODEL OUTPUT INDICATORS

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MODEL OUTPUT INDICATORS

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MODEL OUTPUT INDICATORS Taken from IMPACT

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GO TG Low climate sensitivity High climate sensitivity

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GO TG Low climate sensitivity High climate sensitivity Temperate cereals India (climate impacts)