Application of the Markov Chain in macroeconomic analysis of a managed forest in the Amazon.

• Autor(a) principal: ACUÑA, M. H. A.
• Data de Publicação: 2019
• Outros Autores: OLIVEIRA, L. C. de, OLIVEIRA, M. V. N. d', SOUZA, M. B., COSTA, C. A. F. da
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)
• Texto Completo: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1113288
• topic: Manejo florestal sustentável; Silvicultura sustentable; Forest dynamics; Dinámica forestal; Capital natural; Floresta ombrófila aberta; Modelos matemáticos; Cadena de Márkov; Floresta Estadual do Antimary (AC); Bujari (AC); Acre; Southwestern Amazon; Sudoeste da Amazônia; Floresta Tropical; Exploração Florestal; Análise Econômica; Modelo Matemático; Sustainable forestry; Natural capital; Economic analysis; Markov chain; Mathematical models

This study includes an economic analysis of the dynamics and prognosis of the forest structure of an area under sustainable forest management in the Amazon, in the primary production of tropical roundwood. It analyzes measurements taken between 2001 and 2011 and carries out forest forecasting for the period from 2001 to 2021 with the application of the Markov Matrix Chain. The variables measured by the probability matrix were transformed into equivalent annual rates and compared over the same period to the Brazilian macroeconomic indicators of gross domestic product (GDP) and the real interest rate of primary roundwood production (TJLP). The valuation of tree density utilized a series of average prices of world imports and exports of roundwood. Between 2001 and 2011, the parameters of the forest dynamics without valuation were similar to the TJLP (1.4% per year) and, when valued, the rates were close to the GDP of 3.5% per year. The forecast from 2001 to 2021 indicates that unrated economic groups behave in a similar way to the TJLP of 1% per annum and to the GDP of 2.2% per year, except the recovery category, which has a negative rate of 1.9% per year. The monitoring of tropical forests allows the achievement of economic indexes capable of assessing the anthropic and natural impacts in short periods of analysis and projecting them over time on natural capital.