Global Perspectives on Agriculture and Forest Mitigation: Induced Land Use Change Insights

1. Global Perspectives on Agriculture and Forest Mitigation with Emphasis on Induced Land Use Change PetrHavlík & 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 Forestry and Agriculture GHG Modeling Forum, September 27, 2011, West Virginia

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. Outline • GLOBIOM Presentation • LULUCF Assessments • For further discussion… • Conclusions

4. I. GLOBIOM Presentation

5. Global Biosphere Management Model Basic resolution: 28 regions

6. 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) 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

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

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

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

11. Cropland - EPIC Processes • Weather • Hydrology • Erosion • Carbon sequestration • Crop growth • Crop rotations • Fertilization • Tillage • Irrigation • Drainage • Pesticide • Grazing • Manure 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

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

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

15. Livestock Livestock Production System Approach

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

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

18. II. LULUCF Assessments

19. Model cluster approach

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

23. DO NOTHING scenario – Projected forest area

24. DO NOTHING scenario – Projected tropical deforestation

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

26. Alternative futures scenarios Diet Shift Bioenergy Plus Pro-Nature Pro-Nature Plus

27. Diet Shift Bioenergy Plus Pro-Nature Pro-Nature Plus

28. Diet Shift Bioenergy Plus Pro-Nature Pro-Nature Plus

29. Diet Shift Bioenergy Plus Pro-Nature Pro-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. A Roadmap for moving to a competitive low carbon economy in 2050

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. EU27 – Alternative LULUCF emission pathways

36. Packard: International leakage effects of US biofuels policies preliminary results US cumulative GHG emissions from agriculture and LUC over 2000-2050 [MtCO2eq]

37. Packard: International leakage effects of US biofuels policies preliminary results World cumulative GHG emissions from agriculture and LUC over 2000-2050 [MtCO2eq]

38. III.For further discussion…

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

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

41. IV. CONCLUSIONS

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