Soil associations, soil mapping units and carbon demand index avalues in Thuringia, Saxony-Anhalt and Saxony

1. Table: Soil associations and soil mapping units (including their clay and silt contents) in the study area (according to the Revised FAO Legend (1990)). The Table shows the areas that the six soil associations and their assigned soil mapping units cover in the investigated regions of the three German Federal States of Thuringia, Saxony-Anhalt and Saxony. The table also includes information about the clay and silt contents of these soils, which is necessary for the assessment of the soil organic matter (Franko et al., 2011). This high degree of soil information is necessary because it allows a spatial differentiation in the landscape (not all soil associations are homogeneous) - which is important with regard to the designation of hot spots of high carbon demand. Large parts of the arable land in the study area are located on loess sediments. Soils in loess areas – where also chernosems can be found - cover 31.9% of the study area. All of these soils show high clay and silt contents, reaching from over 50 to 90%. The regional pattern of soil texture has been taken from the German soil map (BUEK1000; scale 1:1,000,000; Hartwich et al., 1998), which includes 72 soil mapping units in total. The mapping units are summarized to seven soil associations. This is a genetic-oriented approach, where the soils are grouped due to their different parent material and conditions relevant for soil formation (topography, climate, etc.) in the corresponding landscape.49 of these 72 different soil mapping units can be found in our study area. Each soil unit has been assigned a characteristic soil profile (“Leitprofil”) where soil texture was derived by using the guidelines for soil mapping (Eckelmann et al., 2005). References: Eckelmann. W., Sponagel, H., Grottenthaler, W., Hartmann, K.-J., Hartwich, R., Janetzko, P., Joisten, H., Kühn, D., Sabel, K.-J., Traidl, R. (2005): Bodenkundliche Kartieranleitung. 5. verbesserte und erweiterte Auflage, Schweizerbart'sche Verlagsbuchhandlung, Stuttgart. Franko, U., Kolbe, H., Thiel, E., Ließ, E. (2011): Multi-site validation of a soil organic matter model for arable fields based on generally available input data. Geoderma 166, 119-134. Hartwich, R., Behrens, J., Eckelmann, W., Haase, G., Richter, A., Roeschmann, G., Schmidt, R. (1998): Bodenübersichtskarte der Bundesrepublik Deutschland. Bundesanstalt für Geologie und Rohstoffe, Hannover. 2. Figure: CDI (Carbon Demand Index) values for the soil mapping units within the study area. We define a Carbon Demand Index (CDI) as a factor that relates the required C demand for a sustainable SOM reproduction in future (Crep(future) ) to the carbon reproduction flux in the past (Crep(past)): Crep(future) = CDI*Crep(past) (1) that can be calculated from the turnover conditition in future (BATfuture) and past (BATpast) values: CDI= BATfuture/BATpast (2) The distribution of the CDI data is nearly Gaussian. Using the breaks of the 1st and 3rd quartile we can identify 3 classes: low: (CDI The Biologic Active Time (BAT) quantifies for a given time interval the site specific impact on turnover activity (Franko et al. 1997, 2007, Kuka et al. 2007, Smith et al. 2007). Here we used the simplified meta-model after Franko and Oelschlägel (1995) which has been successfully validated with the CCB model using datasets from long term experiments in Europe (Franko et al., 2011). References: Franko, U. and Oelschlägel (1995): Einfluss von Klima und Textur auf die biologische Aktivität beim Umsatz der organischen Bodensubstanz. Arch. Acker- Pfl. Boden 39, 155-163. Franko, U., Crocker, G.J., Grace, P.R., Klír, J., Körschens, M., Poulton, P.R., Richter, D.D. (1997): Simulating trends in soil organic carbon in long-term experiments using the CANDY model. Geoderma, 81, S. 109-120. Franko, U., Kuka, K., Romanenko, I.A, Romanenkov, V.A. (2007): Validation of the CANDY model with Russian long-term experiments. Reg. Environ. Change 7, 79-91. Franko, U., Kolbe, H., Thiel, E., Ließ, E. (2011): Multi-site validation of a soil organic matter model for arable fields based on generally available input data. Geoderma 166, 119-134. Kuka, K., Franko, U., Rühlmann, J., (2007): Modelling the impact of pore space distribution on carbon turnover. Ecol. Model. 208 (2-4), 295-306 Smith, P., Smith, J. U., Franko, U., Kuka, K., Romanenkov, V. A., Shevtsova, L. K., Wattenbach, M., Gottschalk, P., Sirotenko, O. D., Rukhovich, D. I., Koroleva, P. V., Romanenko, I. A., Lisovoi, N. V. (2007): Changes in mineral soil organic carbon stocks in the croplands of European Russia and the Ukraine, 1990-2070; comparison of three models and implications for climate mitigation Regional Environmental Change 7 (2), 105-119