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Models of individual trees are composed of sub-models that generally estimate competition, mortality, and growth in height and diameter of each tree. They are usually adopted when we want more detailed information to estimate forest multiproduct. In these models, estimates of growth in diameter at 1.30m above the ground (DBH) and total height (H) are obtained by regression analysis. Recently, artificial intelligence techniques (AIT) have been used with satisfactory performance in forest measurement. Therefore, the objective of this study was to evaluate the performance of two AIT, artificial neural networks and adaptive neuro-fuzzy inference system, to estimate the growth in DBH and H of eucalyptus trees. We used data of continuous forest inventories of eucalyptus, with annual measurements of DBH, H, and the dominant height of trees of 398 plots, plus two qualitative variables: genetic material and site index. It was observed that the two AIT showed accuracy in growth estimation of DBH and H. Therefore, the two techniques discussed can be used for the prognosis of DBH and H in even-aged eucalyptus stands. The techniques used could also be adapted to other areas and forest species., (Copyright © 2017 Elsevier B.V. All rights reserved.)

This paper describes the assessment of the SWAT hydrological model to reproduce continuous daily streamflow and simulate scenarios of forest management for a small catchment under tropical climate in Aracruz, Brazil. The main land use of the catchment consisted of eucalyptus cultivation. The SWAT parameters were calibrated and validated using daily hydrologic and meteorological data from 1997 to 2004. The statistical indices of SWAT validation (NS = 0.74, PBIAS = -14.34%, RSR = 0.51) show that SWAT performance was satisfactory in this application. Different land use and forest management scenarios were simulated with the aim of assessing their influence over the streamflow. The scenarios were: catchment under eucalyptus cultivation with three different forest managements and catchment under the native forest (Atlantic Rainforest). The scenarios simulations did not show significant changes in the long-term average streamflow. Minimum, maximum, and average annual streamflows were higher for eucalyptus scenarios compared to the native forest scenario. These results should be carefully applied to other watersheds as they reflect soil, landscape, and climate characteristics, as well as the geographic location, size, and use of water of the plantings and other vegetation.