Using Soil Depth Functions to Distinguish Dystric from Xanthic Ferralsols in the Landscape

Abstract

The soil texture is a key parameter and is widely used as input in predictive models to estimate other soil properties. The general goal was creating numerical parameters to describe the variability of soil particle size (sand, silt, and clay) components using continuous depth functions to characterize Ferralsols from Guapi-Macacu watershed in Rio de Janeiro State (Brazil). The profile collection comprises fifteen profiles, seven classified as Haplic Ferralsols (Dystric) and eight as Haplic Ferralsols (Xanthic). The analysis was performed in the R software through “aqp” package (Algorithms for Quantitative Pedology) and using equal-area quadratic spline function. A numerical aggregation of soil texture components was used to build a mean, a median, and spline depth functions, fitting the dataset to six predefined depths (GlobalSoilMap project) and to most-likely horizon depths. The analysis revealed sand and silt content with decreasing values with soil depth and the opposite trend for clay. The topsoil layer (0–30 cm) had dominantly a clay loam texture (32–40 % clay; 49–53 % sand; and 15–20 % silt). The most-likely diagnostic B-horizon (45–150 cm depth) presented clayey texture (43–47 % of clay and 40–55 % of sand). Ferralsols usually have low silt contents; and the silt range was from 10 to 20 % in the soil profile collection. The organized data can be useful to many purposes, including profile database harmonization and soil classification.