Main Article Content
The purpose of this study was to spatialize the chemical and physical attributes of the soil in an agroforestry system in Seropédica, Rio de Janeiro, Brazil. Thirty-one soil samples were collected from 0–10 cm, 10–20 cm, and 20–40 cm depths, and each sampling point was georeferenced. The pH (in H2O), potential acidity (H+Al), calcium (Ca+2), magnesium (Mg+2), aluminum (Al+3), sodium (Na+), potassium (K+), phosphorus (P), organic carbon (C), cation exchange capacity of the soil (T value), base saturation (V value), total clay, total sand, silt, and density of fine roots were measured. The software ArcGIS 10.2 was used to perform the semivariogram analysis and the fitting of the models, and spatial interpolation was performed using a first-order trend ordinary kriging process with spherical, exponential, and Gaussian spatial models. Based on the results, only the exponential and Gaussian models were fitted to the variables, except for the Mg2+ and V value variables, which presented no spatial dependence, thus showing a pure nugget effect (PNE). Distribution maps were generated for the variables (except for those exhibiting PNE), which showed correlation between the variables pH and Al3+, organic carbon and cations, phosphorus and total clay, and silt and sand. Overall, geostatistics could be applied to spatialize the chemical and physical attributes of the soil in the agroforestry system, except in the case of Mg2+ and the V value.