1. BIOMASS CARBON ACCOUNTS FOR EUROPE AND GLOBALLY IN GLOBIOM Nicklas Forsell & Stefan Frank, Michael Obersteiner, Petr Havlík….. IIASA – International Institute for Applied Systems Analysis 1

2. A global model with the possibility to zoom in one region 2 30 Regions are interconnected through international trade Regional zooming allows detailed spatial representation of land (50x50km) and introduction of regional policies

3. 306/03/2014

4. Simulation Units (SimU) –HRU –50x50km grid –Country boundaries Source: Skalský et al. (2008) GLOBIOM – Spatial resolution > 200.000 SimUs 4

5. International trade Bi-lateral trade of agricultural, livestock and forestry products is considered between regions Trade is both taken into account in terms of biomass sources as well as semi-finished products  Corn  Wheat  Sugar  Vegetable oils  etc.  Timber  Sawnwood  Plywood  Wood pellets  etc.  Beef  Pork  Eggs  Milk  etc. 5

6. GLOBIOM – EU HRU distribution 6 SimU:  Country  NUTS2  Land cover  HRU:  Elevation  Slope  Texture  Depth to rock  Stone content in subsoil  River catchments  Irrigation 379.220 SimUs

7. Main differences GLOBIOMGLOBIOM-EU Land coverGLC 2000Corine Crop areasFAOEUROSTAT (CAPRI database) Crop sectorFAOEUROSTAT (CAPRI database) Production quantitiesFAOEUROSTAT (CAPRI database) Demand quantitiesFAOEUROSTAT (CAPRI database) PricesFAOEUROSTAT (CAPRI database) Mean annual incrementG4MG4M/MS submissions Soil organic carbon accounting -JRC/EPIC Crop rotations-EPIC Tillage systems-EPIC Spatial SimU gridCountry + gridCountry + NUTS2 7

8. Economic modeling and dynamics Main model outputs – Production Q – Consumption Q – Prices – Trade flows – Land use change – GHG emissions Main input drivers – Population growth – GDP growth – Technological change – Bio-energy demand – Diet patterns 8  Optimization problem: Maximize consumer and producer surplus  Recursive dynamic: solution computed every 10-year period and transmitted to the next period 20002010202020302040…

9.  Production and consumption of food, feed, and fiber commodities  Bilateral trade  Input requirements (fertilizer, water…)  Calorie consumption  Land use and land use change  Conversion of highly biodiverse areas  …. 4  Carbon stock development (soil and biomass)  Forests  Cropland, grassland  Lignocellulosic crops  Other natural vegetation  HWP stocks  Non-CO2 emissions  Fertilizer  Livestock (manure, enteric fermentation)  Rice Commonly reported variables

10. G4M – Global Forest Model Estimates the impact of forestry activities on potential carbon stocks and increments of woody biomass Estimates forest area change, carbon sequestration and emissions in forests, impacts of carbon price and supply of biomass for bio-energy and timber

11. Input Output  NPP – Yield description  Temperature  Precipitation  Forest cover - Species composition  Stocking Biomass  Age structure  Slope  Management target  Increment  Biomass 4  Stocking biomass  Increments  Harvests  Sawn wood  Rest wood  Harvesting costs  Species composition change

12. Global scale species distribution:  Evergreen, Deciduous, Needle- leaved, Broadleaved Global scale species regions:  Boreal, Temperate, Tropical, Subtropical Forests EU scale species distribution:  Pine, Spruce, Beach, Pinus Pinaster, Fir, Oak, Birch, and Larch tC/ha/year MAI potential estimates

13. Forest area and carbon sequestration 7 Estimates the forest land use change (afforestation, deforestation) and impact of forest management Is calibrated to historic data (2000-2010) reported by Member States and FAO FRA Historical trends as well as driver developments (wood prices, crop price, carbon price, land use cost) can be used G4M estimates:  Forest area change (afforestation/deforestation)  Full Carbon Accounting  Impacts of carbon incentives (e.g. avoided deforestation)  Mean annual increment  Forest age structure development  Final harvesting and thinning intensities

14. Globally consistent carbon accounting 14 SectorSourceGHGReference Forest sector Deforestation (biomass, soil) CO 2 Gallaun et al. 2010 scaled to total biomass using Kindermann et al. (2008) Afforestation (biomass, soil) CO 2 Gallaun et al. 2010 scaled to total biomass using Kindermann et al. (2008) Forest management (biomass) CO 2 G4M estimate of change in forest age structure, management intensity Harvested wood products CO 2 IPCC Tier 2 Agri- cultural sector Cropland management (soil, biomass) CO 2 EPIC model (Williams, 1995), Lugato/Jones map for carbon stocks Grassland management (soil, biomass) CO 2 Ruesch and Gibbs (2008), UNFCCC Short rotation plantations (biomass) CO 2 Havlik et al. (2011) Land use change Conversion of other vegetation types (biomass) CO 2 Ruesch and Gibbs (2008), Kindermann et al. (2008)

15. Biomass carbon

16. Soil carbon accounting cropland SOC dynamics captured explicitly in GLOBIOM ~300.000 carbon response functions estimated using EPIC Tillage systems, crop rotations, soil conditions etc.

17. Soil carbon stocks Source: Lugato et al. (2013) Source: Jones et al. (2005)

18. Forest Management Reference Level EU wide reporting together with EFI and JRC Used by 14 MS for UNFCCC reporting

19. EU Reference Scenario

20. EC: Reference scenario Harvest removals increase over time Increment of forests peak and decline due to aging

21. EC: Reference scenario Forest sector main driver of LULUCF sink Increasing demand for wood  declining forestry sink Additional carbon sequestration due to perennial crops 21 LULUCF sink is maintained until 2050 BUT declines steadily

22. LULUCF mitigation potential 22 Preliminary results

23. Discussion & conclusions Globally consistent modelling & accounting approach across various sectors and scales Takes into account domestic and foreign impacts on biomass carbon stocks GLOBIOM is used by EC for various impact assessments and vetted by member states Flexible model structure allows for easy enhancement & reporting Extension feasible e.g. implementation of additional biodiversity map/indicators

24. www.iiasa.ac.at www.globiom.org

25. Protected areas

26. Biodiversity hotspots