Use este identificador para citar ou linkar para este item: http://repositorio.ufla.br/jspui/handle/1/31893
Título: Análise econômica da rotação florestal de povoamentos de eucalipto utilizando a simulação de Monte Carlo
Título(s) alternativo(s): Economic analysis of rotation forest of eucalyptus stands using Monte Carlo simulation
Palavras-chave: Economia florestal
Simulação de Monte Carlo
Eucalipto - Rotação econômica
Forest economics
Monte Carlo simulation
Eucalyptus - Economic rotation
Data do documento: Out-2017
Editor: Universidade Federal de Santa Maria
Citação: GONÇALVES, J. C. et al. Análise econômica da rotação florestal de povoamentos de eucalipto utilizando a simulação de Monte Carlo. Ciência Florestal, Santa Maria, v. 22, n. 4, p. 1339-1347, out./dez. 2017.
Resumo: The objective of this study was to determine the economic cycle rotation of eucalyptus plantations in three productivity sites over hazardous conditions. The data used on this study, released by the company Fibria Celulose. Besides the timber production data, it was also given the company cash flow. It was from an evenaged stand and a monoclonal stand both of Eucalyptus urograndis. For the risk analysis, the study used Monte Carlo method, having as a result of the simulation the Net Present Value for Infinite Series, using as an input variable and/or source of uncertainty, the probability distributions of the land and wood prices, the costs of harvesting and transportation activities, the interest rate and also the timber production. The simulation consisted in carrying out 10,000 interactions, where it was obtained the necessary information for the development of the next analysis. As a conclusion the optimal rotation for cutting was 6, 8 and 11 years on the good sites (I), regular sites(II) and poor sites(III) respectively, being consistent with the biological laws of growth. Another conclusion is that even under the same management conditions, more productive sites generate greater economic returns and therefore lower risk in adverse economic scenarios.
URI: http://repositorio.ufla.br/jspui/handle/1/31893
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