www.joanneum.at/CarboInvent

1. CarboInvent: Methods for quantifying forest carbon budgets B. Schlamadinger & W. Galinski3. USDA Symposium on GHGs in Agric. and ForestryBaltimore, 21-22 March, 2005 www.joanneum.at/CarboInvent

2. Forests in the Kyoto Protocol • Afforestation, Reforestation, Deforestation • Forest Management IPCC Good Practice Guidance LULUCF A) Detect lands subject to these activities B) Estimate C stock changes and GHG emissions on these lands • Projects (JI, CDM)

3. CarboInventMulti-source inventory methods for quantifying carbon stocks and stock changes in European Forests • 14 participants, 10 countries • November 2002 - October 2005 Joanneum Research Austria (coordination) EFI Finland JRC European Community University College Dublin Ireland METLA Finland Inst Forest Ecosystem Res Czech Republic PIK Germany Hung. Forest Res Inst Hungary Ghent Univ Belgium Fed Forest Res Inst Austria Swed Univ of Agr Sci Sweden Univ of Hamburg Germany CREAF Spain Univ of Padua Italy

4. Objectives • Identify / develop / test methods for improved estimates of C stock changes for UNFCCC and KP reporting • establish database of BEFs and biomass equations for major EU forest types • develop methods for soil C assessment to be combined with forest inventories over large spatial scales • develop multi-source (RS, soils, forest inventory) methods for assessing C stock changes including their regional distribution and uncertainties • apply in test sites and suggest upscaling methods to national level

5. BEF Biomass expansion factors at stand levelDatabase: in preparation

6. Results – biomass estimation www.metla.fi/hanke/3306/tietokanta.htm

8. Test country Sweden: Purpose

9. Increase in soil C from north to south

10. Remote sensing applications • Stratification • K Nearest Neighbours (kNN) Method • Interpolation / extrapolation of forest inventories with time • Mapping aerial extent of severe damages • Monitoring Afforestation / Reforestation / Deforestation • (Direct estimation of biomass carbon stocks)

11. Classification of Remote Sensing ImageryExample: Forest Area

12. Disturbances (feed into both bottom-up and top-down approaches) Ground view Windthrow

13. Disturbances (feed into both bottom-up and top-down approaches) RS view

15. Inventory data Dry wood density Biomass allocation Errors of drain biomass (harvest residues) Carbon content Drain from EFISCEN Result distributions for the amount of soil carbon, changes in carbon, soil respiration Result distribution for biomass carbon Results – Top-down approachUncertainty analysis Errors in the amounts of litter for three different litter types (input to soil model) Errors of living biomasses by component Errors related to the parameters in the soil model Errors of source data and models Errors of biomass turnover rates

16. Results – Top-down approach Uncertainty of carbon stock and stock change estimates for Finland. Uncertainty of 1990 biomass carbon stock CV%=2.12 640 MtC 720 MtC Uncertainty of biomass carbon sink 2010-1990 CV%=25.1 50 MtC 150 MtC Vilén, T, Peltoniemi, M. & Meyer, J. Comparable uncertainty estimates of stocks and long-term sinks of biomass and soil carbon in an inventory based method combining a soil model for some European countries.Manuscript in preparation.

17. Carbon Budget “Bottom-up” Integration Remote Sensing Carbon estimates (without soil) per plot Soil data BEF (field and default) Plot data

18. Test sites

19. Joint Implementation projects

20. Results – CDM: Keep it simple!

21. Linking temporary credits to emissions trading • CDM projects result in temporary credits • Not exchangeable with other emissions allowances • Separate the liability from credit • Combine with the later part of credit stream from “energy projects” • Objective: facilitate linking of sinks offset projects with EU Emissions Trading System

22. Workshop, May 2-4Graz / Austria Land-use Related Choices under the Kyoto Protocol Obligations, Options and Methodologies for Defining “Forest” and for Selecting Activities under Kyoto Protocol Article 3.4