Modelling soil carbon trends for agriculture development scenarios at regional level - Kaczynski, Radoslaw; Siebielec, Grzegorz; Hanegraaf, Marjoleine C.; Korevaar, Hein (Geoderma, 2017)
There is an increasing demand for evaluating the impact of specialization in agriculture on soil carbon balance. The main aims of the study were (1) to model the impact of long-term changes in agriculture on soil organic carbon (SOC) stocks at regional level using the Rothamsted C model (RothC), (2) validate these results by conventional SOC analysis, and (3) to compare impacts of “as was” and “mixed farming system” scenarios on SOC trends. The study area covered 1800km2 of Dolnoslaskie province, Poland. The significant changes have occurred in this area since 60's. The production system has changed from the mixed crop-animal farming to highly specialized crop production. We evaluated two scenarios. The starting point for both scenarios was the situation in 1960 (co-existing low intensity crop and animal production). The scenario S-1 reflected recorded changes in agriculture, namely slow transition into specialized and more intensive production with progressive simplification of crop rotation and decline in livestock density. Scenario S-2 constituted hypothetical continuation of the starting situation (i.e. low intensity crop and animal production). In the period 1960–2014 SOC accumulation was observed in “as was” scenario (S-1) in almost all locations of the area characterized by low initial SOC content. The model outputs were then validated using SOC measurements in samples collected in two periods: 1960–1970 and 2010–2014. The modelled SOC stock explained 56% of variability of the measured SOC stock. Comparison of S-1 and S-2 scenarios revealed that re-introduction of mixed farming with current intensity of agricultural production has capacity for further increasing SOC stocks in the region. •Soil carbon is accumulated under intensive crop production in low carbon soils.•Mixed farming systems provide potential for higher carbon sequestration.•Combining pedoclimatic and agronomy data enables SOC modelling at regional level.•Roth-C provides reliable long-term projections of SOC changes.