ARTIFICIAL NEURAL NETWORKS (ANN) FOR HEIGHT ESTIMATION IN A MIXED-SPECIES PLANTATION OF Eucalyptus globulus LABILL AND Acacia mearnsii DE WILD

Abstract

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.

Effects of Intercropping between Morus alba and Nitrogen Fixing Species on Soil Microbial Community Structure and Diversity

“…Many early studies have shown that intercropping of nitrogen-fixing plants and other species can improve productivity [43,44]. Studies also found that intercropping with nitrogen-fixing plants can increase soil nitrogen content [45,46], thereby enhancing the accumulation of organic carbon and nitrogen in the ecosystem [28]. As a nitrogen fertilizer crop, the nitrogen content in Lb was significantly higher than in Ma.…”