Seasonality, soil attributes and root biomass in cerrado, cerradão and forest environments, western Amazon

ABSTRACT

The Amazon rainforest region presents a phytophysiognomy that ranges from savannas to cerrados, all of them intimately associated to climate and soil characteristics. Evidence has been given that plant growth and development are affected by soil quality and seasonality, thus making it crucial to understand them and how they are related to each other in order to grasp the dynamics of the whole ecosystem. In this context, the goal of this research was to assess how seasonality, soil attributes, and root system biomass are related in natural cerrado, cerradão, and forest areas in southern Amazonas State, in Brazil. Soil samples were collected during dry (June/2018) and rainy (December/2018) seasons from three different layers 0.00­0.05m; 0.05­0.15m, and 0.15­0.30m deep. In each area ten sampling points were randomly chosen. Two kinds of soil samples were collected the first using 4.0 cm height by 5.1cm internal-diameter soil sample rings; and the second were intact soil lumps. Physical and Chemical soil attributes assessed were macro-porosity (MaP), micro-porosity (MiP), total porosity (TP), soil density (SD), aggregates texture and stability (GMD and WAR), gravimetric humidity (HG), organic carbon (OC), exchangeable aluminum (Al3+), potential acidity (H+Al), sum of bases (SB), cation exchange capacity (CEC), and root biomass (RB). All data were analysed via Tukey t test and student T test to compare results between seasons and areas. Increasing vegetation density (cerrado < cerradão < forest) was followed by an increment in CEC and OC, showing the importance of these attributes to maintaining biodiversity in environments. In amazon cerrado, rainy season as well a sandier soil textures provided favourable conditions to the growth and development of plants' root system. Soil attributes were little affected by seasonality, that had greater effect on MiP, TP, SD, and OC, leading to lesser values for these variables during rainy season.