Chemical and physical fractions of soil organic matter under various management regimes in Roraima, Brazil
Authors: Guardiola Marden Daniel Espinoza , Vale Júnior José Frutuoso , Silva Edmilson Evangelista da , Rossi Celeste Queiroz , Pereira Marcos Gervasio 
Published: September 2017

The crop-livestock integration (CLI) and crop-livestock-forest integration (CLFI) management systems, have been shown to be viable approaches for increasing carbon sequestration in soils, resulting in the improvement of physical and chemical soil attributes. The objective of this study was to evaluate the chemical attributes and organic matter in soils under Natural Forest (NF) converted to different uses and managed differently: rotational pasture area (PAST), crop-livestock integration (CLI), and crop-livestock-forest integration (CLIF). The research was conducted at the São Paulo farm, in Iracema, located in the south-central region of the state of Roraima, Brazil. The studied soil type was classified as Ultisol. Soil samples were taken by opening ditches and examining layers at 0.1-m depth intervals from surface to 0.60-m depth. Total organic carbon (TOC), chemical and granulometric fractionation of soil organic matter (SOM), oxidizable fractions, and light organic matter in water were analyzed. Our results showed low levels of the analyzed chemical elements, a characteristic of a soil with low natural fertility. This matches conditions inherent in source material, weathered by high rainfall, a warm and humid climate, and flat topographic relief. In the 0-0.1 m layer, the PAST and CLI systems had the highest TOC contents relative to the other systems studied. At other depths, there were no statistical differences among TOC levels. The highest concentration of C in the particulate fraction (POC) was noted in the surface layer in all management systems. The pasture system had the highest concentration POC in the top 0.10 m. Our results also showed that the upper 0.10 m of soil in NF contained the lowest content of organic carbon associated with mineral (MOC) relative to the managed agrosystems. In addition, humin provided the largest contribution to SOM in all evaluated management systems. The crop-livestock integration (CLI) and crop-livestock integration forest (CLIF) systems, emerged as a strong alternative to carbon incorporation and subsequently the improvement of physical and chemical soil attributes. The objective of this work to evaluate the chemical attributes and organic matter in soils under Natural forest (NF) converted into different use and management systems: pasture (PAST), crop-livestock Integration (CLI) and crop-livestock Integration forest (CLIF). The research was conducted at São Paulo farm in Iracema, located in the Center-South region of the State of Roraima, Brazil. The soil studied was classified as Argissolo Amarelo Distrófico. The samples were taken by the opening of trenches in layers of 0-0.10, 0.10- 0.20, 0.20- 0.40, and 0.40-0.60 m depth. Total organic carbon (TOC), chemical and granulometric fractionation of soil organic matter (SOM), oxidizable fractions and organic matter in water were analyzed. The results showed low levels of the analyzed chemical elements which characterizes soils with low natural fertility, which matches the conditions of the source material, high rainfall and regional temperature, as well as the flat local relief. In the 0-0.1 m layer, the PAST and CLI systems had the highest TOC contents when compared to the other systems studied, in the other depths there were no statistical differences between the TOC levels. The highest amount of C in the particulate fraction (COp) was verified in the surface layer in all evaluated management systems. The pasture area was the system with the greatest contribution of COp to the depth of 0-0.0 m. In relation to the carbon content associated with minerals (COam), the results showed that the depth of 0-0.05 m NF area presented the lowest levels when compared to the other systems. Regarding the humic substances, there was a larger contribution of humin in all evaluated systems.