1. Petr Havlík & Michael Obersteiner + >30 collaborators International Institute for Applied Systems Analysis (IIASA), Austria International Livestock Research Institute (ILRI), Kenya University of Natural Resources and Applied Life Sciences, Vienna (BOKU), Austria University of Hamburg, Sustainability and Global Change (FNU), Germany Soil Science and Conservation Research Institute, Bratislava, Slovakia Global Perspectives on Agriculture and Forest Mitigation with Emphasis on Induced Land Use Change Forestry and Agriculture GHG Modeling Forum, September 27, 2011, West Virginia

2. 2  In low stabilization scenarios LULUCF becomes the single most important GHG emitter by mid-century  For efficient mitigation policy design global and comprehensive tools needed  Global- Design of globally consistent national baselines - Accounting for potential international leakage effects  Comprehensive - Capture co-benefits and leakages across sectors linked through land

3. 3 Outline I. GLOBIOM Presentation II. LULUCF Assessments III. For further discussion… IV. Conclusions

4. 4 I. GLOBIOM Presentation

5. 5 Global Biosphere Management Model Basic resolution: 28 regions

6. 6 Supply functions implicit: production system 1 (grass based)  productivity 1 + constant cost 1 production system 2 (mixed)  productivity 2 + constant cost 2 Demand functions explicit: linearized non-linear functions Partial equilibrium model (endogenous prices) Agriculture: major agricultural crops and livestock products Forestry: traditional forests for sawnwood, and pulp and paper production Bioenergy: conventional crops and dedicated forest plantations Recursively dynamic (10 year periods) Maximization of the social welfare (PS + CS)

7. International trade Spatial equilibrium model Trade flows between individual regions (BACI database, CEPII) Homogeneous goods assumption - Within a region imported and domestically produced goods are valued equally  no mutual trade - Differences in prices between regions are due to external trade costs Trade costs Trade barriers (MacMap database, ITC/CEPII) +Transport cost (Hummels, 2001) +Calibration

8. 8 Output: Production Q - land use (change) - water use - GHG, - other environment (nutrient cycle, biodiversity,…) Consumption Q Prices Trade flows Main exogenous drivers: Population GDP Technological change Bio-energy demand (POLES team) Diets (FAO, 2006)

9. 9 Wood Processing Bioenergy Processing Livestock Production Unmanaged Forest Managed Forest Short Rotation Tree Plantations Cropland Grassland Other Natural Vegetation Energy products: Ethanol (1 st gen.) Biodiesel (1 st gen.) Ethanol (2 nd gen) Methanol Heat … Forest products: Sawnwood Woodpulp Livestock: Cattle meat & milk Sheep & Goat meat & milk Pork meat Poultry meat & egg Crops: Barley Corn Cotton … Supply chains

10. 10 Land Simulation Units (SimU) = HRU & PX30 & Country zone Source: Skalský et al. (2008) > 200 000 SimU

11. 11 Weather Hydrology Erosion Carbon sequestration Crop growth Crop rotations Fertilization Tillage Irrigation Drainage Pesticide Grazing Manure Processes Major outputs: Crop yields, Environmental effects (e.g. soil carbon, ) 20 crops (>75% of harvested area) 4 management systems: High input, Low input, Irrigated, Subsistence Cropland - EPIC

12. Relative Difference in Means (2050/2100) in Wheat Yields [Data: Tyndall, Afi Scenario, simulation model: EPIC]

13. 13 Forests – G4M Step 1: Downscaling FAO country level information on above ground carbon in forests (FRA 2005) to 30 min grid Source: Kindermann et al. (2008)

14. 14 Forests – G4M Step 2: Forest growth functions estimated from yield tables Major outputs: Mean annual increment Tree size Sawn wood suitability Harvesting cost

15. 15 Livestock Production System Approach Livestock

16. 16 Livestock Production System Parameters Livestock Input parameters Cut&Carry Grains Stover Grazing Occasional Bovines Sheep & Goat Pigs Poultry Output parameters Bovine Milk & Meat Shoat Milk & Meat Pig Meat Poultry Meat & Eggs CH4 Manure

17. 17 Herrero, Havlik et al (PNAS forthcoming) Non-CO2 intensity of milk production

18. 18 II. LULUCF Assessments

19. 19 Model cluster approach

20. 20 G4M - Spatially explicit results

21. Recent applied projects (Highlights) DG Climate Action: EU LULUCF Reference Level for Forest Management accounting Baseline runs for the construction of country specific Reference Levels Accounting of emissions from FM will compare development of emissions from forestry against RL - Reviewed by UNFCCC DG Climate Action: EU Roadmap for moving to a low-carbon economy in 2050 - Contribution to the impact assessment DECC (UK, Depatment of energy and climate change), DEA (Dannish Energy Agency) – Global Forestry Emissions Projections and Abatement Costs – Feeding MACCs for forestry activities into GLOCAF model World Bank: Congo Basin WWF Living Forest Report Packard Foundation: USA climate policies international leakage 21

23. DO NOTHING scenario – Projected forest area

24. DO NOTHING scenario – Projected tropical deforestation

25. TARGET Zero Net Deforestation and Forest Degradation by 2020 (ZNDD) REDD policy scenario

26. Diet ShiftBioenergy PlusPro-NaturePro-Nature Plus Alternative futures scenarios

27. Diet ShiftBioenergy PlusPro-NaturePro-Nature Plus

28. Diet ShiftBioenergy PlusPro-NaturePro-Nature Plus

29. Diet ShiftBioenergy PlusPro-NaturePro-Nature Plus Kapos et al. (2008)

30. Total land cover change (2010-2050)

31. Agricultural commodity prices compared to DO NOTHING

32. Agricultural input use compared to DO NOTHING

33. 33 A Roadmap for moving to a competitive low carbon economy in 2050

34. 34 GLOBAL – GHG emissions from agriculture and gross deforestation Global baseline - globally no additional climate action is undertaken up to 2050. The EU implements the climate and energy package but nothing additional is undertaken. Global Action - global action that leads to a reduction of global emissions of 50% by 2050 compared to 1990

35. 35 EU27 – Alternative LULUCF emission pathways

36. 36 Packard: International leakage effects of US biofuels policies Total LUC Fertilizer use LivestockSub-TOTAL Fossil fuel replacement TOTAL BioenScen_50-32176914783182-2662916 BioenScen_75-30179214463178-3962781 BioenScen_100-24183014403223-5312692 BioenScen_1258188914323337-6682669 BioenScen_15012195614323412-8102602 US cumulative GHG emissions from agriculture and LUC over 2000-2050 [MtCO2eq] preliminary results

37. 37 Total LUC Fertilizer use LivestockSub-TOTAL Fossil fuel replacement TOTAL BioenScen_5011556167852027848619-132947290 BioenScen_7511666168322031548814-147647338 BioenScen_10011745169032032248970-162847342 BioenScen_12511859169732033649167-178147386 BioenScen_15011985170772036049422-194147482 Packard: International leakage effects of US biofuels policies World cumulative GHG emissions from agriculture and LUC over 2000-2050 [MtCO2eq] preliminary results

38. 38 III. For further discussion…

39. W. Africa 1966 – pastoral system 2004 – crop-livestock system Courtesy of B. Gerard What is the potential contribution of LPS change to food security, land sparing and GHG reduction?

40. 40 Total abatement calorie cost (TACC) curves for different policy options by 2030 Herrero, Havlik et al (PNAS forthcoming)

41. 41 IV. CONCLUSIONS

42. 42  Bottom-up modeling of global agriculture and forestry sectors becoming feasible through integration of economic and bio-physical models  REDD still appears as the low hanging fruit  Sustainable intensification can provide benefits in terms of food security, reduced LUC, and GHG emissions  Not only intensification but also reduction of yield volatility can act as land sparing measure in view of extreme weather events  Large uncertainties in very basic datasets need to be properly handled…

43. 43 Thank you! havlikpt@iiasa.ac.at www.globiom.org