Modelling of soil organic carbon dynaMic on grassland under different ManageMent and cliMate scenarios

0Citations
Citations of this article
5Readers
Mendeley users who have this article in their library.

Abstract

Improperly used farming systems and agrotechnical practices with ongoing climate change can contribute to the reduction of the level of soil organic carbon (SOC) stocks not only in intensively cultivated arable soils but also in grasslands. One of the ways to track changes in the SOC stock is the use of mathematical models. The RothC model was validated at the locality Suchý vrch, which hosts long-term experiments on grassland. The soil type is sandy-loam textured Cambisol. Validation was done for the period 1993 – 2009 on grassland with various applications of mineral and organic fertilisers. Results of validation show that the RothC model appropriately predicts the development of grassland SOCs and can be used in forecasting SOC stock in the future. Five different management scenarios, with carbon input 2.3 to 6.4 t/ha and three climate scenarios (RCP 2.6, RCP 4.5, RCP 8.5) of the MPI climate model were used to track the changes of SOC stock on grassland in the period 2009 – 2100. Modelling results of SOC development show, that in the future, a relatively low-temperature increase (RCP 2.6) and a relatively high carbon input into the soil (6.4 t/ha) can ensure moderate carbon sequestration. However, between the low-carbon management scenarios (2.3 and 4.1 t/ha), SOC stocks are continuously decreasing in the RCP 2.6 climate scenario. At a significantly higher temperature (climate scenario RCP 8.5), that is expected in future, it will not be possible to maintain the current level of SOC stock not even at a high carbon input (6.4 t/ha).

Cite

CITATION STYLE

APA

Barančíková, G., Koco, Š., Halas, J., Takáč, J., Makovníková, J., & Kizeková, M. (2023). Modelling of soil organic carbon dynaMic on grassland under different ManageMent and cliMate scenarios. Agriculture (Pol’nohospodarstvo), 69(3), 105–117. https://doi.org/10.2478/agri-2023-0009

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free