Influence of spatial variability of soil chemical attributes on the nutritional status and growth of the rubber tree

Abstract

The productive potential of the rubber tree (Hevea brasiliensis) is dependent on its genetic composition, in addition to edaphoclimatic factors and management practices. However, as soil properties are not homogenous, knowing the spatial variability of soil attributes would be important to increase productivity and reduce production costs. In this context, the objective of this study was to determine the spatial variability of chemical attributes of the soil and its influence on the nutritional status and growth of rubber tree clones. Clones FX 3864, FDR 5788, CDC 312, and RRIM 600 were planted at Jaturnaíba Farm, in the municipality of Silva Jardim, Rio de Janeiro State, Brazil. The sampling sites were distributed at a spacing of 20 × 20 m on the northern and southern sides of the relief. The chemical attributes of the soil (pH, Ca2+, Mg2+, K+, P, Al3+, H+Al, sum of bases, cation exchange capacity, and base saturation) were evaluated at a depth of 0–20 cm in the different clone plantations. Additionally, the N, P, K, Ca, and Mg content as well as trunk circumference and total plant height, were also evaluated. Geostatistics was used to determine the spatial variability of the soil and clone attributes, while Ordinary Kriging was used to draw variability maps of the variables. A difference in the distribution of the variables, which was dependent on the slope of the relief, was detected through the maps. The southern side presented better conditions as some degradation was observed on the northern side. Certain soil characteristics influenced the distribution of the attributes of the planted clones; for example, the low concentration of Ca2+ in the soil caused Ca deficiency in the FX clone on the southern slope, indicating that liming did not supply enough nutrients for this clone. Our results showed that the variability in soil attributes influenced the nutritional status and growth of the rubber tree clones, indicating that variability maps can guide the planting and management of the rubber tree, providing more efficient management.