Growth modeling of Cryptomeria japonica by partial trunk analysis

Authors

  • Vinícius Morais Coutinho Universidade Federal do Paraná
  • Ana Paula Dalla Corte Universidade Federal do Paraná
  • Carlos Roberto Sanquetta Universidade Federal do Paraná
  • Aurélio Lourenço Rodrigues Universidade Federal do Paraná
  • Mateus Niroh Inoue Sanquetta Universidade Federal do Paraná

DOI:

https://doi.org/10.4336/2017.pfb.37.90.1371

Keywords:

Probability analysis, Increment, Forest management

Abstract

This study aimed to evaluate the growth pattern of Cryptomeria japonica increment (L. F.) D. Don. and to describe the probability distribution in stands stablished at the municipality of Rio Negro, Paraná State. Twenty trees were sampled in a 34 years-old stand, with 3 m x 2 m spacing. Wood disks were taken from each tree at 1.3 m above the ground (DBH) to perform partial stem analysis. Diameter growth series without bark were used to generate the average cumulative growth curves for DBH (cm), mean annual increment (MAI) and current annual increment (CAI). From the increment data, the frequency distribution was evaluated by means of probability density functions (pdfs). The mean annual increment for DBH was 0.78 cm year-1 and the age of intersection of CAI and MAI curves was between the 7th and 8th years. It was found that near 43% of the species increments are concentrated bellow 0.5 cm. The results are useful to define appropriate management strategies for the species for sites similar to the studying regions, defining for example ages of silvicultural intervention, such as thinning.

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Published

2017-06-30

How to Cite

COUTINHO, Vinícius Morais; CORTE, Ana Paula Dalla; SANQUETTA, Carlos Roberto; RODRIGUES, Aurélio Lourenço; SANQUETTA, Mateus Niroh Inoue. Growth modeling of Cryptomeria japonica by partial trunk analysis. Pesquisa Florestal Brasileira, [S. l.], v. 37, n. 90, p. 93–98, 2017. DOI: 10.4336/2017.pfb.37.90.1371. Disponível em: https://pfb.cnpf.embrapa.br/pfb/index.php/pfb/article/view/1371. Acesso em: 18 may. 2024.

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