Agricultural Soil Inventory enables improvements to national GHG emission reporting in Germany
The agricultural sector and land use of agricultural soils in the LULUCF sector are responsible for 11 % of total German greenhouse gas emissions. Drained peatlands are a major source of CO2, which accounts for approximately one third of these emissions, from only 6 % of the agricultural land area. However, CO2 emissions from mineral soils currently have high uncertainty in the German LULUCF inventory and the impact of measures aiming at carbon sequestration by improved agricultural management practices cannot currently be reported.
The Thünen Institute uses a Tier-2 approach to estimate annual SOC stock changes in mineral soils for the German LULUCF inventory. In order to better represent mitigation and carbon sequestration efforts, the long-term roadmap aims to switch to a Tier-3 modelling approach. A representative SOC stock baseline is necessary as a first step and therefore, after completion of the second German forest soil inventory, the Federal Ministry of Food and Agriculture tasked the Thünen Institute to conduct the first comprehensive inventory of agricultural soils. From 2009 to 2018, cropland and grassland soils at more than 3000 representative locations (8×8 km grid) were sampled to a depth of 100 cm. A unique feature of the German agricultural Soil Inventory is that the preceding ten years of management data were surveyed and evaluated for all sampling sites. This includes information on crop rotations, fertilizer inputs, yields and tillage for croplands as well as stocking density, fertilization and cutting frequency for grasslands.
On mineral soils, croplands (n=2204) had an average SOC stock of 61±25 (0-30 cm) and 96±48 Mg C ha-1 (0-100 cm), while grasslands (n=704) stored on average 88±32 (0 – 30 cm) and 135±70 (0-100 cm) Mg C ha-1. The 146 sampled organic soil profiles had an average SOC stock of 528±201 Mg C ha-1 (0-100 cm). A machine learning approach was used to predict the most important drivers of SOC stock on the national scale. Neither climate nor management variables are among the most important predictors, which does however not imply that management is irrelevant for SOC dynamics – the opposite is the case. However, on a national scale it is mainly soil properties that explain the variability in SOC stocks. The most important soil properties are C:N ratio, clay content and groundwater level; topsoil SOC stocks are also driven by land use (cropland vs. grassland). The reason for the high importance of soil C:N ratio is the abundance of so called “black sands” in the North West of Germany, which are mainly podzols with a peat or heathland history, low pH values and a large proportion of undecomposed, recalcitrant plant material.
Results of soil analyses and profile descriptions are made available on an open data repository. The agricultural soil inventory will be repeated in 2023-2028 at the same representative locations to enable assessing the temporal developments of SOC stocks. Average baseline SOC stocks are already integrated into LULUCF reporting. As a next step, it is planned to use stratified SOC stocks for more reliable estimates of land use change effects. This follows the logic that the average SOC stock difference between croplands and grasslands cannot be fully ascribed to land use, but is also driven by soil properties. Finally, machine learning is currently also applied for SOC stock regionalization to derive a reliable, high resolution SOC map of Germany that is needed for higher Tier approaches.
Figure 1: Soil sampling with interested audience.
Figure 2: Spatial distribution of topsoil (0-30 cm) organic carbon stocks (adapted from Poeplau et al. 20205).
 Poeplau, C., Jacobs, A., Don, A., Vos, C., Schneider, F., Wittnebel, M., Tiemeyer, B., Heidkamp, A., Prietz, R., Flessa, H., 2021. Stocks of organic carbon in German agricultural soils—Key results of the first comprehensive inventory. Journal of Plant Nutrition and Soil Science.