Projection of Soil Organic Carbon Reserves in the Argentine Rolling Pampa Under Different Agronomic Scenarios. Relationship of these Reserves with Some Soil Properties

The Open Agriculture Journal 16 Apr 2015 RESEARCH ARTICLE DOI: 10.2174/1874331501509010030


The soil organic carbon (SOC) of the Argiudolls of the Argentine Rolling Pampa evolves rapidly. Currently, the soils richest in SOC are cultivated with intensified crop sequences (e.g. maize-double cropped wheat/soybean, MWS) under no tillage (NT) and the poorest ones with soybean monoculture (S) under NT. There are great uncertainties about the future projections of SOC reserves and soil fertility associated with changes in land use and management. The aim of this study was to predict soil fertility in 2032, by: a) validating the simple AMG model in long-term experiments of the Rolling Pampa, b) correlating the SOC and active carbon pools (SOCm and Ca, respectively) modeled for 2008 with some soil properties, and c) simulating the evolution of SOC reserves under different agronomic scenarios, using the AMG model, starting from rich and poor SOC soils of the Rolling Pampa. The AMG model was able to provide satisfactory simulation of the SOC reserves (R2 = 0.87) and showed good quality of fit between Ca and particulate organic carbon (POC) and SOCm and structural stability index (SSI), indicating that the AMG model could project SOC reserves and soil fertility. In rich SOC soils, the maintenance or increase in mean crop yields (MWS NT and MWS with high yields under NT, MWS opt., respectively) caused no changes, whereas the conversion to S under NT reduced the SOC reserves by 12%. Maize residue removal caused 4.5% SOC loss in MWS NT and no changes in MWS opt. In poor SOC soils, the continuity of S under NT and the conversion to MWS NT produced no changes; the passage to continuous or periodic shallow tillage caused 6% SOC loss; and the conversion to Miscanthus x giganteus produced an increase of 9% in SOC.

Keywords: Soil organic carbon, AMG model, agronomic scenarios, soil properties.
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