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Knowledge of the effect of soil nutrients, such as K and Na and their interaction with water availability, on the growth and wood properties of the eucalypts, is needed to increase the productivity of commercial plantation forests in Brazil that generate employment and taxes. The present study evaluates the apparent wood density (at 12% wood moisture) of Eucalyptus grandis trees at 12, 24, 36 and 48 months old under ambient and lower than ambient (66%) rainfall conditions and K and Na nutrient enrichment. The treatments were two water availability (100 and 66% of the rainfall) and the three nutrient treatments were: K (4.5 kmol/ha), Na (4.5 kmol/ha) and a control (natural conditions). The apparent wood density of samples at breast height (1.3 m) was determined by X-ray densitometry and digital images. Increased nutrients at all four ages and water availability at 36 and 48 months reduced apparent wood density in E. grandis trees, however, effects of nutrients are lower under water availability reduction. The radial profile of wood density was higher in four-year-old trees, but there was radial variation in apparent wood density at all ages. These findings predict that, under water stress, apparent wood density will not decline in commercial E. grandis plantations fertilized with potassium. The use of sodium, as a substitute of potassium, should consider their negative impacts on wood density of Eucalyptus grandis trees.

The saturated hydraulic conductivity, k sat , is a crucial variable to describe the hydromechanical behavior of soils. The value of k sat of lateritic soils that are typically found in tropical regions is highly affected by the soil's structure, void ratio, and fine particle aggregation. As a result, the determination of k sat in the field or in the laboratory is complex and involves greater variability, depending on the type of test and on the spatial location of sampling. This paper presents a study of k sat values of lateritic soils, analyzing them using Statistic, Multilayer Perceptron Artificial Neural Networks (ANN) and Decision Trees (CHAID). This study aims to support decision-making regarding the type of test and depth chosen for sampling in laterite soils and understanding the factors influencing the permeability of such soils. An extensive literature review on the k sat values of lateritic soils was performed, providing data for the establishment of a database comprise of 722 registries. According to agronomic and geotechnical soil classifications, the Brazilian lateritic soils presents a "moderate" hydraulic conductivity. A significant variation of permeability values along the depth was identified, particularly for depths between 0.1 and 0.2 m. Regarding the importance of testing variables, the ANN indicated a high dependency on the type of test. The decision tree divided field test and laboratory test automatically, inferring the relevance of the type of test to the determination of k sat ., (© 2022. The Author(s).)