The nature of the soil is shaped by the presence of roots and the soil microbiota. Bacteria, archaea and fungi profoundly alter plant growth and, in turn, depend on root exudation of carbon-rich and energy-yielding compounds. The microbial communities act as facilitators of plant processes by secreting plant growth regulators, solubilizing minerals, providing N for plant growth, altering plant immune responses and competing with plant pathogens. Characterizing and engineering the processes driven by the multiple microbial taxa that make [...] ABSTRACT The nature of the soil is shaped by the presence of roots and the soil microbiota. Bacteria, archaea and fungi profoundly alter plant growth and, in turn, depend on root exudation of carbon-rich and energy-yielding compounds. The microbial communities act as facilitators of plant processes by secreting plant growth regulators, solubilizing minerals, providing N for plant growth, altering plant immune responses and competing with plant pathogens. Characterizing and engineering the processes driven by the multiple microbial taxa that make

There has been limited research on the effect of eucalyptus harvest residue management on soil organic carbon (SOC) in subtropical environments. This research evaluated the effect on soil C indices of the following eucalyptus harvest residue managements: AR, with all forest remnants left on the soil; NB, where bark was removed; NBr, in which branches were removed; NR, which removed all residues; and NRs, which is same as NR but also used a shade net to prevent the litter from the new plantation from reaching the soil surface. C stocks within the soil depths of 0–20 cm and 0–100 cm increased linearly with the C input from eucalyptus harvest residues. In the layer of 0–20 cm, the lowest soil C retention rate was 0.23 Mg ha⁻¹ year⁻¹, in the NR treatment, while in the AR treatment, the retention rate was 0.68 Mg ha⁻¹ year⁻¹. In the 0–100 cm layer, the highest C retention rate was obtained in the AR (1.47 Mg ha⁻¹ year⁻¹). The residues showed a high humification coefficient (k₁ = 0.23) and a high soil organic matter decomposition rate (k₂ = 0.10). The carbon management index showed a close relationship with the C input and tree diameter at breast height.

The objective of this study is to evaluate the fit of Artificial Neural Networks (ANN) for height estimation and evaluation of the effects of consortium in a mixed-species plantation of Eucalyptus globulus (E) and Acacia mearnsii (A). The experiment was installed in 2005, on two farms in the municipality of Piratini - RS, where was planted the species Eucalyptus globulus (E) and Acacia mearnsii (A), in monoculture and mixed in simple lines (50%E:50%A - SL), and double lines (50%E:50%A - DL). The training and evaluation of the networks were made in R-project with the package neuralnet. All ANNs, from the simplest to the most complex, showed high values for Rŷy and low for Syx, BIAS and RMSE, with superior results in ANN 3, 4, and 6, which demonstrates that the information of DBHmin, DBHmean, and DBHmax were important stand attributes. Furthermore, the ANNs were able to capture the different growth patterns shown by the species in the different forms of consortiums, therefore is indicated for the height estimation in monocultures and mixed plantations of Eucalyptus globulus and Acacia mearnsii, and only one ANN would be necessary to represent the entire population.

Yerba mate is a forest species of both cultural and economic importance growing in the subtropical regions of South America, especially in the south of Brazil. Despite its importance, yerba mate has never received enough attention from researchers, so the nutritional sufficiency ranges and critical levels have not yet been determined. This research aimed to establish these parameters for yerba mate to enable its foliar diagnosis. A total of 167 leaf samples were collected from production fields located in the five yerba mate-growing regions in Rio Grande do Sul, and the leaf nutrients were determined by standard chemical methods. The yield of each production field was accessed, and the cutoff value separating low- and high-yield groups was calculated in 16.75 Mg ha⁻¹. The multivariate compositional nutrient diagnosis (CND) standards were determined, and nutrient interactions were estimated by correlation and principal component analyses. There was no positive correlation between any single nutrient and yield, even in the high-yield population, evidencing that a higher yield is the outcome of the balance among all nutrients. Excess of B occurred in one-third of the low-yield samples, while deficiency of Cu and K occurred in one-fourth of these samples. Finally, we established the adequate leaf nutrient levels for yerba mate.