Simulation of soil organic carbon changes in Slovak arable land and their environmental aspects

Abstract

One of the key goals of the Thematic Strategy for Soil Protection is to maintain and improve soil organic carbon (SOC) stocks. A decline of SOC stocks is politically perceived as a serious threat to soil quality and functions. A suitable tool for acquiring the information on SOC stock changes is modelling. The RothC-26.3 model was applied for long-term modelling (1970–2007) of the SOC stock in the topsoil of croplands of Slovakia. Simulation results show a gradual increase in the SOC stock in the first phase of modelling (1970–1995) mainly due to higher carbon input in the soil. A significant linear correlation (r = 0.4**, n = 275) was found between carbon input and the final simulation of SOC stock. A close relationship between the SOC stock and soil production potential index representing the official basis for soil quality assessment in Slovakia was also determined and a polynomial relationship was found which describes the relation at the 95% confidence level. We have concluded from the results that balanced or positive changes in the SOC stock dynamics that are important for sustainable use of soils could be influenced positively or negatively in Slovakia by political decisions concerning the soil management. Moreover, the soil production potential index can be used as soil quality information support for such decision-making.

How does national SOC monitoring on agricultural soils align with the EU strategies? An example using five case studies

“…Similarly, in Slovakia, SOC concentration data of individual monitoring intervals are available for estimating nationwide SOC stocks on agricultural land. Related to that, SOC data from individual soil monitoring localities were used to test the RothC model in predicting SOC stocks on the national (Barančíková et al, 2010, 2012) and regional level (Skalský et al, 2020). More recently, regional estimates of topsoil SOC stocks using SOC data from the 2018 sampling together with stratified predictors (altitude, land cover, topsoil texture and soil type) was done for the 78 administrative regions, provided the most up‐to‐date regional figures on the state of topsoil SOC in agricultural soil of Slovakia (Skalský et al, 2024).…”

Land Cover and Land Use Change-Driven Dynamics of Soil Organic Carbon in North-East Slovakian Croplands and Grasslands Between 1970 and 2013

“…Although information on the large-scale SOC stock temporal dynamics driven by land cover land use changes is limited by available data with appropriate spatial and temporal resolution, the process-based models combined with spatially explicit quantitative data on topsoil SOC, weather and land use prove effective in overcoming this problem (as in Alvaro-Fuentes et al, 2011;Gottshalk et al, 2012;Barančíková et al, 2012;Ma et al, 2016;Kaczynski et al, 2017).…”

“…For this purpose, the RothC turnover model (Coleman, Jenkinson, 2014) is most commonly used in SOC management studies because it can be run on single-site basis or integrated with geographical data sets to provide spatially explicit estimates for regions, countries and the world (Falloon, Smith, 2012;Campbell, Paustian, 2015;Gottshalk et al, 2012;Wang et al, 2016;van Wesemael et al, 2010;. This model was successfully used in reconstructing the 1970-2010 Slovak crop and grasslands topsoil SOC stock development trajectory and also for estimating the current SOC levels on a national scale (Barančíková et al, 2010(Barančíková et al, , 2012. However, these authors record that the results provide only approximate SOC stock estimates because of limitations in the spatial resolution of gridded data (10x10 km) on organic carbon inputs from management, the monthly weather records and the initial 1970's SOC stock estimated from the soil map and profile data from the Slovak National agricultural soils inventory used to run the RothC model.…”

“…However, these authors record that the results provide only approximate SOC stock estimates because of limitations in the spatial resolution of gridded data (10x10 km) on organic carbon inputs from management, the monthly weather records and the initial 1970's SOC stock estimated from the soil map and profile data from the Slovak National agricultural soils inventory used to run the RothC model. This research also neglects marginal cropland and grassland areas and does not consider land cover change during the simulation period (Barančíková et al, 2012.…”