IPADS BALCARCE   29747
INSTITUTO DE INNOVACIÓN PARA LA PRODUCCIÓN AGROPECUARIA Y EL DESARROLLO SOSTENIBLE
Unidad Ejecutora - UE
artículos
Título:
The effect of agriculture on topsoil carbon stocks is controlled by land use, climate, and soil properties in the Argentinean Pampas
Autor/es:
NICOLAS, WYNGAARD; MERCEDES, EYHERABIDE; WALTER, CARCIOCHI; HERNÁN, ANGELINI; REUSSI CALVO, NAHUEL; CECILIA, CRESPO; GASTÓN, LARREA; SAINZ ROZAS, HERNÁN RENE
Revista:
CATENA
Editorial:
ELSEVIER SCIENCE BV
Referencias:
Lugar: Amsterdam; Año: 2022 vol. 212
ISSN:
0341-8162
Resumen:
The conversion of native grasslands into croplands with a high frequency of soybean (Glycine max L.) in croprotations has diminished soil organic carbon (SOC) stocks in the Argentinean Pampas. The aims of our study wereto determine the amount of SOC lost due to cultivation (dSOC) and to assess the main factors (land use, climate,and soil properties) associated with dSOC. We took paired topsoil samples (0 to 20 cm) from arable and pristinesoils (n = 465) and used a path analysis approach to evaluate the direct and indirect effect of different variableson dSOC. The selected variables were SOC in pristine soils (SOCPRIS), clay content, carbon input (Cinput), relativesoybean harvested area (Sb%), and mean annual precipitation and air temperature (PP and Temp, respectively).The percentage of sites with SOC < 20 g kg􀀀 1 was 29% in pristine soils and 66% in arable soils. The dSOC rangedfrom 0 to 82 Mg ha􀀀 1. Depending on the area, dSOC represented 25 to 36% of SOCPRIS stocks. The path analysisexplained 60% of the dSOC variation, and the main factor controlling dSOC was SOCPRIS (by direct effect andindirect effects through clay, PP, and Temp), followed by Sb%. The Sb% depended on the productive potential ofthe area (soybean yield) which was associated with Temp and PP. As a conclusion, in the analysed temperate andfully humid environments, soils with greater SOCPRIS and high soybean frequency in the crop rotations presenteda greater SOC depletion after conversion to agriculture. This information will be valuable when developingmodels to predict current and future SOC stocks.