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

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.

 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

 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

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.

Pag e 6 IFPRI’s Approach: Modeling and Data

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

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.

INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE The IMPACT Model

 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

Global Food Production Units (281 FPUs)

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

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

Pag e 14 Model of Land Use Choices

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

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

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

INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE WHAT TO DO WITH THIS INFORMATION

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

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

Baseline Scenario Price Changes (IMPACT) Source: IMPACT. Price (USD/ton) a Yield (ton/ha) b Area growth (%) c Growth (% ) Growth (%) Bean % %8.67% Cassava % %1.40% Cotton % %0.00% Groundnuts % %-0.63% Maize % %1.73% Irrigated Rice % %-1.71% Rainfed Rice % %-1.71% Soybean % %-2.18% Sugar cane % %43.68% Sweet potato % %-3.33% Coffee % %8.67%

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

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.

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 Cropland allocated to Rice cultivation kept constant at 3.8 million hectares Adoption of Alternate Wet and Dry (AWD) in rice paddy: Introduce manure compost in rice paddy Replace conventional fertilizer in rice paddy with ammonium sulfate

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

Baseline Scenario Price Changes (IMPACT) WORLD Price growth (%) COLOMBIA Area growths (%) 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%

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

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

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 Livestock -1, Forest Other Total Zero deforestation in the Amazon Cropland Livestock Forest Other Total Increase area allocated to oil palm by 1.5 million hectares Cropland Livestock Forest Other Total

Policy Simulation Comparison Pag e 30

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

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