1. Soil carbon in dynamic land use optimization models Uwe A. Schneider Research Unit Sustainability and Global Change Hamburg University

2. Topics I Land use models I Land use models II Linking biophysical and economic models II Linking biophysical and economic models III Soil carbon in economic models III Soil carbon in economic models IV FASOM IV FASOM

3. I Land use models

4. Research Questions Economic Sustainability Economic Sustainability –Food –Energy –Commodities Environmental Sustainability Environmental Sustainability –Air –Water –Soil –Climate –Ecosystems Policy analysis Policy analysis –Economic potential –Impacts

5. Focus of land use models Technologies (Species, Tillage, Planting, Fertilizing, Protection, Harvesting) Technologies (Species, Tillage, Planting, Fertilizing, Protection, Harvesting) Economics (Market Prices, Trade, Income) Economics (Market Prices, Trade, Income) Environment (Resources, Emissions, Sinks, Wildlife, Climate) Environment (Resources, Emissions, Sinks, Wildlife, Climate)

6. Land use estimation Storylines Storylines Statistics Statistics Optimization Optimization

7. Optimization Constrained welfare/profit maximization Constrained welfare/profit maximization Normative economics (positive economics via calibration) Normative economics (positive economics via calibration) Application to structural change beyond historical observations Application to structural change beyond historical observations

8. Land use optimization Find welfare maximizing land management Find welfare maximizing land management s.t.resources technologiesmarketspolicies

9. Linear Program

10. II Linking biophysical and economic models

11. Why linkage? Standalone biophysical models simulate environmental impacts of land management but don’t explain why a certain land management is chosen Standalone biophysical models simulate environmental impacts of land management but don’t explain why a certain land management is chosen Standalone economic models explain land management adoption but cannot internalize environmental impacts Standalone economic models explain land management adoption but cannot internalize environmental impacts

12. Challenges Spatial resolution (field vs. globe) Spatial resolution (field vs. globe) Temporal resolution (days vs. decades) Temporal resolution (days vs. decades) Technological resolution Technological resolution Environmental resolution Environmental resolution

13. Types of Linkage (Problems) A. Economic model  Biophysical model (no adaptation, no feedback) B. Biophysical model  Economic model (curse of dimensionality) C. Iterative link (costly, ITR) D. Fully integrated model (computational limits)

14. Economic model  Biophysical model Determine land use trajectory with economic model for different scenarios Determine land use trajectory with economic model for different scenarios Simulate environmental impacts for each scenario Simulate environmental impacts for each scenario Adaptation of land management to environmental policies ignored Adaptation of land management to environmental policies ignored Feedback of changing environment on adaptation ignored as well Feedback of changing environment on adaptation ignored as well

15. Biophysical model  Economic model Simulate environmental impacts for all possible land use choices Simulate environmental impacts for all possible land use choices Enter environmental impacts in economic model Enter environmental impacts in economic model Set values for environmental impacts (environmental policies) Set values for environmental impacts (environmental policies) Find welfare maximizing levels Find welfare maximizing levels

16. Curse of Dimensionality? 20 Crops 20 Crops 5 Management options per crop 5 Management options per crop 100 Regions 100 Regions 5 Soil Types per region 5 Soil Types per region 50,000 Land use alternatives

17. Curse of Dimensionality? 20 Crops 20 Crops 5 Management options per crop 5 Management options per crop 100 Regions 100 Regions 5 Soil Types per region 5 Soil Types per region 20 Periods 20 Periods 5*E42 Trajectories (independent sites) 1*E94 Trajectories (dependent sites)

18. III Soil carbon in economic models

19. Soil carbon and economics Productivity impact of soil carbon (yields, suitability) Productivity impact of soil carbon (yields, suitability) Economic potential of carbon sinks for climate change mitigation Economic potential of carbon sinks for climate change mitigation Carbon sinks vs. bioenergy vs. biodiversity vs. traditional markets Carbon sinks vs. bioenergy vs. biodiversity vs. traditional markets

20. Soil Carbon Determinants Crop Choice Crop Choice Tillage Tillage Irrigation Irrigation Fertilization Fertilization Residue Mgt Residue Mgt Soil Carbon Soil Carbon SoilCarbonChange

21. Soil Organic Carbon (tC/ha/20cm) 5 10 15 20 25 30 35 40 45 0 10 20 30 40 50 Time (years) Wheat-Lucerne 3/3 Wheat-Lucerne 6/3 No-till wheat-fallow Tilled wheat-fallow

22. Simple Multi-Period Land Use Model Indexes: t = time, r = region, i = soil type, u = management Data:  = interest rate, v = net benefit, l=land endowment Variables: X = land use

23. Explicit Land Use Trajectories Indexes: r = region, i = soil type, u d = management path

24. Implicit Land Use Trajectories Assume that management history is manifest in current soil carbon levels Assume that management history is manifest in current soil carbon levels Divide soil carbon range Divide soil carbon range Implement Markov Chain Implement Markov Chain

25. Markov Process Indexes: t = time, r = region, i = soil type, u = management o,ố = soil carbon state  = transition probability from old state ố to new state o

26. Soil Carbon Transition Probabilities SOC1SOC2SOC3SOC4SOC5SOC6SOC7SOC8 SOC10.810.19 SOC21 SOC30.090.91 SOC40.310.69 SOC50.5 SOC60.740.26 SOC71 SOC80.040.96 No-till wheat-Fallow

27. 5 10 15 20 25 30 35 40 45 0 10 20 30 40 50 Time (years) Wheat-Lucerne 3/3 Wheat-Lucerne 6/3 No-till wheat-fallow Tilled wheat-fallow Soil Organic Carbon (tC/ha/20cm)

28. Curse of Dimensionality? 20 Crops 20 Crops 5 Management options per crop 5 Management options per crop 100 Regions 100 Regions 5 Soil Types per region 5 Soil Types per region 20 Periods 20 Periods 5E42 Trajectories (independent sites) 1E94 Trajectories (dependent sites)

29. Curse of Dimensionality? 20 Crops 20 Crops 5 Management options per crop 5 Management options per crop 100 Regions 100 Regions 5 Soil Types per region 5 Soil Types per region 20 Periods 20 Periods 1E6 Variables (No Soil Carbon) 1E7 Variables (Markov process with 10 states) 5E42..1E94 Variables (Explicit Path)

30. Extensions? Markov chains are applicable to relatively independent environmental qualities (humus, salt, contamination) Markov chains are applicable to relatively independent environmental qualities (humus, salt, contamination) Method not suitable for complex environmental properties (climate) Method not suitable for complex environmental properties (climate)

31. IV Forest and Agricultural Sector Optimization Model FASOM

32. Overall Objective Portray agricultural and forest commodity markets and internalize all land use externalities Analyze Policies Integrate Synergies, Trade-offs

33. Markets Soil ClimateWildlife Land use decisions Water Farmers

34. Model Structure Resources Land Use Technologies Processing Technologies ProductsMarkets Inputs Limits Supply Functions Limits Demand Functions, Trade Limits Environmental Impacts

35. Economic Surplus Maximization Implicit Supply and Demand Forest InventoryLand Supply Water Supply Labor Supply Animal Supply National Inputs Import Supply Processing Demand Feed Demand Domestic Demand Export Demand CS PS

36. Spatial Resolution Soil texture Soil texture Stone content Stone content Altitude levels Altitude levels Slopes Slopes Soil state Soil state Political regions Political regions Ownership (forests) Ownership (forests) Farm types Farm types Farm size Farm size Many crop and tree species Many crop and tree species Tillage, planting irrigation, fertilization harvest regime Tillage, planting irrigation, fertilization harvest regime

37. Altitude: 1.< 300 m 2.300-600 m 3.600-1100 m 4.>1100 m Texture: 1.Coarse 2.Medium 3.Medium-fine 4.Fine 5.Very fine Soil Depth: 1.shallow 2.medium 3.deep Stoniness: 1.Low content 2.Medium content 3.High content Slope Class: 1.0-3% 2.3-6% 3.6-10% 4.10-15% 5.… Homogeneous Response Units DE13 DE12 DE11 DE14

38. Climate Change Mitigation 0 100 200 300 400 500 020406080100120140160180200 Carbon price ($/tce) Emission reduction (mmtce) CH4 N2O Ag-Soil sequestration Afforestation Biofuel offsets

39. Soil Carbon Potentials 0 100 200 300 400 500 020406080100120140160 Carbon price ($/tce) Soil carbon sequestration (mmtce) Technical Potential Economic Potential Competitive Economic Potential

40. Biofuel Potentials 0 100 200 300 400 500 050100150200250300350 Carbon price ($/tce) Emission reduction (mmtce) Technical Potential Economic Potential Competitive Economic Potential

41. Afforestation Potentials 0 100 200 300 400 500 050100150200250300 Carbon price (Euro/tce) Emission reduction (mmtce) Technical Potential Economic Potential Competitive Economic Potential