1. Ecosystems component – Cropland Activity Pete Smith & Martin Wattenbach Professor of Soils & Global Change School of Biological Sciences, University of Aberdeen, Scotland, UK E-mail: pete.smith@abdn.ac.uk CarboEurope-IP Annual Meeting, Poznan, Poland, October 2007

2. Are croplands as big a source of C as we thought?

3. http://www.abdn.ac.uk/modelling/cropwebpage/cropwebpage4IE.htm CarboEurope-IP Cropland sites

4. The sites – status of work CountrySite name Site n° Site short name Germany Gebesee 3 DE-Geb Germany Klingenberg 8 DE-Kli FranceGrignon 12 FR-Gri DenmarkRisbyholm42DK-Ris SpainEl Saler-Sueca 56 ES-Es2 BelgiumLonzee 73 BE-Lon UKEast Saltoun76 UK-Esa IrelandCarlow80IE-Car1 Switzerland Oensingen 103CH-Oen2 MAIN SITES Flux data for 2004, 2005, 2006. all years simulated, additional data required Flux data for 2004, 2005. not simulated, essential soil data requested Flux data for 2005. simulated, additional data required Flux data for 2004, 2005. not simulated, essential soil data requested. Flux data for 2004, 2005, 2006. 2005 simulated, climate data requested Flux data for 2004, 2005, 2006. all years simulated, more data required Flux data for 2004, 2005. not simulated, essential climate, soil data requested Flux data for 2004, 2005 all years simulated, first results Flux data for 2005, simulated, first results from MSc thesis

5. Ancillary sites – work status CountrySite name Site n° Site short name FranceLamasquèrexxFR-Lam ASSOCIATED SITES Flux data for 2005. not simulated, essential data required Flux data for 2005 - Molenweg ? not simulated, essential data required. Flux data for 2004, 2005, not simulated, essential data required FranceAuradéxxFR-Aur Flux data for 2005. not simulated, essential data required NetherlandsCabauw67NL-Cab1 Italy Borgo Cioffi26It-Bci

6. Using models to interpret EC data from croplands

7. What are the uncertainties associated with the simulation of cropland ecosystems at site level ? Input parameters and variables Uncertainty site scale Fertilization (Nitrogen) +/- 10% each application Temperature+/- 1°C Precipitation+/- 5% Global radiation+/- 5% Clay content+/- 10% Initial soil carbon+/- 10% siteNEE measured kgC ha -1 best estimate run kgC ha -1 Mean value of the Monte Carlo simulation kgC ha -1 Oensingen 2004 585167356675 The discrepancy between simulated mean value from the Monte Carlo runs and the annual value obtained from a single run using the best estimates. suggest that using the best estimate may not lead to the most probable model result. Input distribution Monte Carlo – multi model run DNDC* model * DeNitrification-DeComposition model Output distribution

8. Change in cropland SOC – climate&NPP&technology Climate only J.U. Smith et al. (2005)

9. Change in cropland SOC – climate&NPP&technology Climate&NPP&technology J.U. Smith et al. (2005)

10. Summary First results are promising – fungicide effect seems to be real Would be interesting to check other sites Data availability is crucial for model applications –Climate, soil and management data are the essential basis Next step are: –uncertainty analysis –Up-scaling for regions and Europe –Comparing NEE, NEP, NBP, NPP, GPP etc. for sites

11. An advertisement for the cropland parallel session – synthesis papers and more… Werner Kutsch – How does the soil C status among of croplands affect fluxes? Christine Moureaux – The C balance of full crop rotational cycles Gary Lanigan – The impacts of single and extreme events on the cropland C balance Eric Ceschia - Full C balance at plot scale NBP estimates across cropland sites Martin Wattenbach – A multi-cropland-site / multi-model comparison – preliminary findings John Tenhunen - Model-based parallel analyses of grass and cropland NEE Pete Smith - Possibilities for C / GHG mitigation in agricultural lands Franco Miglietta – Cropland soils: the big uncertainty