1. INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE FROM GLOBAL TO LOCAL: MODELING LOW EMISSIONS DEVELOPMENT STRATEGIES Dr. Alex De Pinto - Senior Research Fellow Dr. Tim Thomas - Research Fellow Dr. Man Li - Research Fellow Dr. Ho-Young Kwon - Research Fellow Ms. Akiko Haruna - Research Analyst

2. Low Emission Development Strategies  Globally, agriculture is responsible for 10 – 14% of GHG emissions and largest source of no-CO 2 GHG emissions.  Countries can choose among a portfolio of growth-inducing technologies with different emission characteristics.  We believe that is less costly to avoid high- emissions lock-in than replace high-emissions technologies. EFFORT TO ENCOURAGE LEDS.

3.  Main goal of USAID funded project: Create a tool for the objective evaluation of LEDS involving agriculture and forestry sectors.  Analysis and modeling based on IFPRI expertise and in-country knowledge coming from existing country programs in the CGIAR system and other local institutions  LEDS project includes four countries: Colombia, Vietnam, Bangladesh, Zambia Low Emission Development Strategies

4.  Since countries are part of a global economic system, it is critical that LEDS are devised based both on national characteristics and needs, and with a recognition of the role of the international economic environment.  Output Ex-ante evaluation of policy reforms, infrastructure investments and/or new technologies on the economy, land-use, emissions and sequestration trends. Consistent with global outcomes. Low Emission Development Strategies

5. Technical Approach  Combines and reconciles Limited spatial resolution of macro-level economic models that operate through equilibrium-driven relationships at a subnational or national level with Detailed models of biophysical processes at high spatial resolution.  Essential components are: a spatially-explicit model of land use choices which captures the main drivers of land use change IMPACT model: a global partial equilibrium agriculture model that allows policy and agricultural productivity investment simulations Crop model to simulate yield, GHG emissions, and changes in soil organic carbon Output: spatially explicit country-level results that are embedded in a framework that enforces consistency with global outcomes.

6. Pag e 6 IFPRI’s Approach: Modeling and Data

7. MODELING FRAMEWORK 7 LAND USE MODEL Satellite data Ancillary data: Pop, road, institutional factors, crop suitability, topography, climate condition, soil property Geographically disaggregated changes (pixel or municipio level) in land uses Geographically disaggregated changes (pixel or municipio level) in land uses IMPACT World Macroeconomic scenario: e.g., GDP and pop growth GCM scenario: e.g., precipitation and temperature Data on C stock; Livestock emissions; GHG emissions from crop production. Ag census data Country-level Changes in Cropland Area Pasture Area Country-level Changes in Cropland Area Pasture Area CROP MODEL GCM scenario (climate and weather); agronomic practices and use of inputs BASELINE

8. MODELING FRAMEWORK Data on C stock; Livestock emissions; GHG emissions from crop production. CROP MODEL GCM scenario (climate and weather); agronomic practices and use of inputs BASELINE Policy scenario: Ex. land use allocation targets, infrastructure, adoption of low-emission agronomic practices Land-Use CHANGE CROP MODEL POLICY SIMULATION POLICY SIMULATION Economic trade-offs Change in carbon stock and GHG emissions.

9. INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE The IMPACT Model

10.  Global, partial-equilibrium, multi-commodity agricultural sector model  Global coverage over 115 countries or regions.  The 115 country and regional spatial units are intersected with 126 river basins: results for 281 Food Producing Units (FPUs).  World food prices are determined annually at levels that clear international commodity markets

11. Global Food Production Units (281 FPUs)

12. The IMPACT Model  Economic and demographic drivers GDP growth Population growth  Technological, management, and infrastructural drivers Productivity growth Agricultural area and irrigated area growth Livestock feed ratios Changes in nonagricultural water demand Supply and demand elasticity systems Policy drivers: commodity price policy (taxes and subsidies), drivers affecting child malnutrition, and food demand preferences, crop feedstock demand for biofuels

13. The IMPACT Model  Output: Annual levels of food supply International food prices Calorie availability, and share and number of malnourished children Water supply and demand For each FPU: area and yield for each considered crop  Prices are used to determine where, due to changes in relative profitability, are going to occur,  Crop area predicted by IMPACT are spatially allocated by using the land use model

14. Pag e 14 Model of Land Use Choices

15. Cocoa Coffee Palm Plantain Other Perennials Model Structure: Two-level Nested Logit Pasture Forest Perennial Crops Annual Crops ForestOther Uses Cassava Maize Potato Rice Sugar Cane Other Annuals

16. Model Specification, Upper Level  Choice variable: land use at municipio level  Explanatory variables Population density in 2005 Travel time to major cities Elevation Terrain slope Soil PH Annual precipitation Annual mean temperature Cattle density Meat price

17. Model Specification, Lower Level  Lower level, choice variable: crop shares in provinces: Crop suitability Crop price Soil PH Elevation Slope Precipitation Temperature

18. INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE WHAT TO DO WITH THIS INFORMATION

19. Country-specific Analyses  Unique characteristics require country-specific solutions  Each country has its own political conditions that determine available options  Extensive meetings with ministry officials, policy-makers, producer organizations, farmer organizations, “stakeholders”. Pag e 19

20. Policy Analysis – An Example from Vietnam  Vietnam focused on food security: Rice production  Commitment to forest protection

21. Baseline Scenario Price Changes 2010-2030 (IMPACT) Source: IMPACT. Price (USD/ton) a Yield (ton/ha) b Area growth (%) c 20092030Growth (% )20092030Growth (%) Bean 52357710.16%0.951.016.69%8.67% Cassava 547335.54%16.8020.4021.40%1.40% Cotton 898113226.02%1.331.5717.78%0.00% Groundnuts 51257712.73%2.092.4115.25%-0.63% Maize 537439.01%4.105.7439.93%1.73% Irrigated Rice 13316725.89%5.195.9013.69%-1.71% Rainfed Rice 13316725.89%2.873.2713.69%-1.71% Soybean 15419828.60%1.461.41-3.13%-2.18% Sugar cane 131727.32%58.7766.3412.88%43.68% Sweet potato 43353122.72%8.2612.2548.33%-3.33% Coffee 80689711.39%2.082.226.69%8.67%

22. Land use conversion: Change in Agricultural land. Year 2010 – 2030 Land use conversion: Change in Agricultural land. Year 2010 – 2030 Land Use 2010-2030 Baseline Scenario

23. Policy Analysis – An Example from Vietnam Land use policy scenario from Decision No. 124/QD-TTg and Decision on 3119/QD-BNN-KHCN and alternative agricultural management practices Scenario 1Total forest cover increased to 45% of land area by 2030 Scenario 2 Cropland allocated to Rice cultivation kept constant at 3.8 million hectares. Scenario 3Adoption of Alternate Wet and Dry (AWD) in rice paddy: Scenario 4 Replace conventional fertilizer in rice paddy with ammonium sulfate. Scenario 5Introduce manure compost in rice paddy in place of farmyard manure.

24. Policy Simulation Comparison Pag e 24 Change C Stock (Tg CO 2 eq) Change in GHG Emissions (Tg CO2 eq) Change in Total Revenue (Billion USD) Total forest cover increased to 45% of land area by 2030 513.8-114.4-6.6 Cropland allocated to Rice cultivation kept constant at 3.8 million hectares. 69.73-68-1.8 Adoption of Alternate Wet and Dry (AWD) in rice paddy: 0-1550-2.7 Introduce manure compost in rice paddy. 0-260-5.3 Replace conventional fertilizer in rice paddy with ammonium sulfate. 0-1021.2

25. Policy Analysis – An Example from Colombia  Country has not tapped its full agricultural potential due to internal conflict  Extensive amount of land used “inefficiently” for cattle production  Substantial investments in the oil-palm production sector

26. Baseline Scenario Price Changes 2010-2030 (IMPACT) WORLD Price growth 2010-2050 (%) COLOMBIA Area growths 2010-2050 (%) CACAO 53% 7% COFFEE 46% 3% PALM 107% 16% PLANTAIN 25% 14% YUCA 89% 11% MAIZE 100% 6% POTATO 33% 11% RICE 62% 10% SUGAR CANE 186% 57% MEAT 24% MILK 24%

27. Land Use 2010-2030 Baseline Scenario Projected changes in forest and pasture areas at municipality level, 2010–2030

28. Land use policy scenario from identifies after consultation with stakeholders Scenario 1Reduction of pastureland by 10 million hectares Scenario 3Total halt to deforestation in the Amazon Scenario 4Total land allocated to palm production reaches a total of 1.3 million hectares Policy Analysis – An Example from Colombia

29. Change in C stock (Tg C) Total change in GHG emission (Tg CO 2 eq) Total change in revenues (US$ billion) Reduce pasture by 10 million hectares Cropland 144 26.718 Livestock -1,297 -184-8 Forest 895 -- Other 660-- Total 402-15710 Zero deforestation in the Amazon Cropland 4 -0.8-0.2 Livestock -97 -16 Forest 245 -- Other -41-- Total 111-17 Increase area allocated to oil palm by 1.5 million hectares Cropland 18 24.5-18 Livestock -10 0 Forest -7 -- Other -11-- Total -1124-18

30. Policy Simulation Comparison Pag e 30

31. Lessons Learned  Adoption of desirable agricultural practices need to be evaluated with respect to other relevant land uses.  Best opportunities to increase resilience and reduce emissions might come from working at the landscape level.  Policies need to take into account the worldwide economic landscape and the pressures deriving from world markets. Pag e 31

32. Lessons Learned  Models must be Open (new data), Transparent (trust), and adaptable (to country specific needs).  Modelling skills are transferable  Close collaboration with local agencies, research institutions, ministries, is the key to success. Pag e 32