Allometric models for estimating the aboveground biomass of the mangrove Rhizophora mangle

Authors

  • Heide Vanessa Souza Santos Universidade Federal de Sergipe; Laboratorio de Erosão e Sedimentação
  • Francisco Sandro Rodrigues Hollanda Universidade Federal de Sergipe; Laboratorio de Erosão e Sedimentação
  • Tiago de Oliveira Santos Universidade Federal de Sergipe; Laboratorio de Erosão e Sedimentação
  • Karen Viviane Santana de Andrade Universidade Federal de Sergipe; Laboratorio de Erosão e Sedimentação
  • Mykael Bezerra Santos Santana Universidade Federal de Sergipe; Laboratorio de Erosão e Sedimentação
  • Gustavo Calderucio Duque Estrada Universidade do Estado do Rio de Janeiro; Faculdade de Oceanografia; Núcleo de Estudos em Manguezais
  • Mario Luiz Gomes Soares Universidade do Estado do Rio de Janeiro; Faculdade de Oceanografia; Núcleo de Estudos em Manguezais

DOI:

https://doi.org/10.1590/s1679-87592017127006501

Keywords:

Allometric equations, Aboveground biomass, Mangrove, Regression analysis, Rhizophora mangle

Abstract

The development of species-specific allometric models is critical to the improvement of aboveground biomass estimates, as well as to the estimation of carbon stock and sequestration in mangrove forests. This study developed allometric equations for estimating aboveground biomass of Rhizophora mangle in the mangroves of the estuary of the São Francisco River, in northeastern Brazil. Using a sample of 74 trees, simple linear regression analysis was used to test the dependence of biomass (total and per plant part) on size, considering both transformed (ln) and not-transformed data. Best equations were considered as those with the lowest standard error of estimation (SEE) and highest adjusted coefficient of determination (R2a). The ln-transformed equations showed better results, with R2a near 0.99 in most cases. The equations for reproductive parts presented low R2a values, probably attributed to the seasonal nature of this compartment. "Basal Area2 × Height" showed to be the best predictor, present in most of the best-fitted equations. The models presented here can be considered reliable predictors of the aboveground biomass of R. mangle in the NE-Brazilian mangroves as well as in any site were this widely distributed species present similar architecture to the trees used in the present study.

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Published

2017-03-01

Issue

Section

Original Article

How to Cite

Allometric models for estimating the aboveground biomass of the mangrove Rhizophora mangle. (2017). Brazilian Journal of Oceanography, 65(1), 44-53. https://doi.org/10.1590/s1679-87592017127006501