1. 1 1) Federal Institute for Geosciences and Natural Resources (BGR) 2) INTERRA 3) Geological Survey of Denmark and Greenland (GEUS) Rainer Baritz 1, Dietmar Zirlewagen 2, Vibeke Ernstsen 3 Relevance of GEMAS for soil property mapping

2. 2 Introduction  GEMAS samples were taken from agricultural surface-close soil layers (Ap 0-20 cm, Grazing land 0-10 cm);  Parameters also include TOC, pH, P, CEC;  “Standard results“ are provided as geostatistical maps;  The main objective of GEMAS is to collect information about the spatial distribution pattern of trace elements in the rooted zone of soil;  Soil organic matter and acidity are important to interpret the potential of soil to store and release heavy metals.

3. 3 Questions Technical questions:  What is the possible contribution of GEMAS to soil monitoring?  How can GEMAS information be integrated into different soil inventories?  How can the representativity from GEMAS be assessed? Criteria?  Are there alternative upscaling methods?

4. 4 Upscaling method

5. 5 Spatial Regression  Stepwise multiple linear regression combined with geostatistics/kriging;  Covariates as possible impact factors on the target variables (TOC, pH, P);  Stratification is important to optimise upscaling models.

6. 6 Upscaling method Database  Biogeographical regions, soil regions, N deposition data (EMEP);  DEM 90m/Relief parameters (aspect, slope, curvature, topographic wetness index, potential direct radiation, etc.);  Parent material (ESDB, 2004);  Land cover CORINE 2000 and 2006, and at GEMAS points  LUCAS 2003 crop types (CEC, 2003);  Climate (WORLDCLIM).

7. 7 Upscaling method Stratification Stratum 1: Sweden Norway and Finland (‘Boreal’) Stratum 2: United Kingdom and Ireland Stratum 3: Eco-Regions (DMEER) with Code- Numbers 56, 27, 10 (‘High Mountainous’) Stratum 4: the remaining European target area (‘European continent’)

8. 8 Total organic carbon

9. 9 TOC [%] agricultural soil (From Baritz et al., 2014, Fig. 6.4B, p.123)

10. 10 Influence of predictors [All_TOC]

11. 11 TOC Stratum 1: Sweden, Norway and Finland (‘Boreal’) Stratum 2: British Isles and Ireland Stratum 3: Eco-Regions (‘High Mountainous’) Stratum 4: remaining Europe ‘(European continent’) TOC and crop types (From Baritz et al., 2014, Fig. 6.5, p.124)

12. 12 LUCAS 2003 and soil texture (ESDB, 2004) (From Baritz et al., 2014, Table 6.3, p.127)

13. 13 pH (CaCl 2 ) Soil acidity

14. 14 pH (CaCl 2 ) agricultural soil

15. 15 Validation and uncertainties

16. 16  Despite low sampling density (1 sample site/2500 km 2 ), the sample size was large enough to separate a training, and a validation set both representing well the predictive population;  Split of the data; random split inside large-scale squares stratified biogeographical region;  Regional models are derived from the training data;  Prediction error is then compared to the results from running the training set-based models with the validation data. Validation Method Germany: 357,104 km 2 total, 187,291 km 2, agriculture (1 site/600 km 2 ) Europe:10.5 million km 2 ; agriculture: 1 site/2333 km 2 (parts of Eastern Europe and Balkans not covered)

17. 17 Results Spatial distribution of the inaccuracy (standard error) Spatial distribution of the residuals

18. 18 Outlook

19. 19  Include N and CEC, include soil texture data;  Re-upscale with the new parent material map;  Condense regionally, then also improve stratification;  Interpret covariates;  Include integrated evaluations (e.g., potential heavy metal release relative to SOM and acidity). Outlook

20. European Soil Database 201 classes (aggregated from 671 initial classes) New BGR parent material map (From Günther et al., 2013, Fig. 2, p.299 & Baritz et al., 2014, Fig. 6.2, p.120)

21. 21 BGR GEMAS: N=310 (completely sampled and analysed soil profiles) BGR soil profiles: N=1567 (agricultural land) Regional studies + = Representative data set for higher resolution evaluations, 2.5 D

22.  The quality of the GEMAS inventory (analysis, georeferencing) is high so that satisfactory regression models can be built (950 plots for the ‘learning’ data set; stratification is important.  Option: Integration into a larger soil monitoring and soil quality assessment scheme (country-level/Europe).  Added value to facilitate a closer exchange between geoscientists and soil scientists. Conclusions

23. 23 Thank you for your attention! rainer.baritz@bgr.de d.zirlewagen@interra.biz‎ ve@geus.dk References

24. SLIDES 7, 9, 11, 12, 20: Baritz, R., Ernstsen, V. & Zirlewagen, D., 2014. Carbon concentrations in European agricultural and grazing land soil. Chapter 6 In: C. Reimann, M. Birke, A. Demetriades, P. Filzmoser & P. O’Connor (Editors), Chemistry of Europe's agricultural soils – Part B: General background information and further analysis of the GEMAS data set. Geologisches Jahrbuch (Reihe B 103), Schweizerbarth, 117-129. SLIDE 6: CEC (Commission of the European Communities), 2003. The LUCAS survey. European statisticians monitor territory. Theme 5: Agriculture and fisheries, Series Office for Official Publications of the European Communities, Luxembourg, 24 pp. Corine land cover 2000 (CLC2000) seamless vector database. http://www.eea.europa.eu/data-and-maps/data/corine-land-cover-2000- clc2000-seamless-vector-database http://www.eea.europa.eu/data-and-maps/data/corine-land-cover-2000- clc2000-seamless-vector-database Corine Land Cover 2006 (CLC2006)s eamless vector data. http://www.eea.europa.eu/data-and-maps/data/clc-2006-vector-data-versionhttp://www.eea.europa.eu/data-and-maps/data/clc-2006-vector-data-version ESDB, 2004. The European Soil Database distribution version 2.0. European Commission and the European Soil Bureau Network, CD-ROM, EUR 19945, http://eusoils.jrc.ec.europa.eu/ESDB_Archive/ESDB_Data_Distribution/ESDB_data.html.http://eusoils.jrc.ec.europa.eu/ESDB_Archive/ESDB_Data_Distribution/ESDB_data.html SLIDE 9: Baritz, R., Ernstsen, V. & Zirlewagen, D., 2014. Carbon concentrations in European agricultural and grazing land soil. Chapter 6 In: C. Reimann, M. Birke, A. Demetriades, P. Filzmoser & P. O’Connor (Editors), Chemistry of Europe's agricultural soils – Part B: General background information and further analysis of the GEMAS data set. Geologisches Jahrbuch (Reihe B 103), Schweizerbarth, 117-129. SLIDE 17: Baritz, R., D. Zirlewagen and E. Van Ranst (2006). Methodical standards to detect forest soil carbon stocks and stock changes related to land use change and forestry – landscape scale effects. Final report Deliverable 3.5-II. Multi-source inventory methods for quantifying carbon stocks and stock changes in European forests (CarboInvent) EU EVK2-2001-00287. SLIDE 20: Günther, A., Van Den Eeckhaut, M., Reichenbach, P., Hervás, J., Malet, J.-P., Foster, C. & Guzzetti, F., 2013. New developments in harmonized landslide susceptibility mapping over Europe in the framework of the European Soil Thematic Strategy. Proceedings Second World Landslide Forum, 3-7 October 2011, Rome. In: C. Margottini, P. Canuti, K. Sassa (Editors), Landslide Science and Practice. Springer-Verlag, Berlin, Vol. 1, 297-301. doi: 10.1007/978-3-642-31325-7_39.