Please use this identifier to cite or link to this item: https://repositorio.inpa.gov.br/handle/1/18013
Title: Allometric models for estimating above- and below-ground biomass in Amazonian forests at São Gabriel da Cachoeira in the upper Rio Negro, Brazil
Authors: Lima, Adriano José Nogueira
Suwa, Rempei
Ribeiro, Gabriel Henrique Pires de Mello
Kajimoto, Takuya
Santos, Joaquim dos
Silva, Roseana Pereira da
Souza, Cacilda Adélia Sampaio de
Barros, Priscila Castro de
Noguchi, Hideyuki
Ishizuka, Moriyoshi
Higuchi, Niro
Keywords: A-coefficient
Allometric Models
Amazonian Forests
Best Fit
Best Model
Biomass Components
Biomass Estimation
Brazilian Amazon
Carbon Dynamics
Carbon Stocks
Census Data
Dry Mass
Meta Analysis
Power Functions
Primary Forest
Regional Scale
Regional Variation
Regression Model
Rio Negro
Single Variable
Stem Diameter
Study Sites
Total Biomass
Total Mass
Tree Height
Tree Size
Biomass
Climate Change
Estimation
Population Statistics
Regression Analysis
Forestry
Aboveground Biomass
Allometry
Belowground Biomass
Carbon Sink
Forest Ecosystem
Growth Modeling
Height Determination
Meta Analysis
Biological Populations
Biomass
Carbon
Climates
Estimation
Mathematical Models
Regression Analysis
Amazon River
Amazonas
Rio Negro [south America]
Issue Date: 2012
metadata.dc.publisher.journal: Forest Ecology and Management
metadata.dc.relation.ispartof: Volume 277, Pags. 163-172
Abstract: Precise estimation of biomass at a regional scale is required for evaluating forest carbon stocks throughout the Amazon. We examined six types of allometric models to identify the best estimator of biomass in primary forests (terra firme) in the northwestern sector of the Brazilian Amazon. We also tested six regression models for estimating tree height. We developed each allometric model using measurements of 101 trees excavated in a primary forest distributed along the upper Rio Negro. A simple power function with stem diameter at breast height D as a single variable was selected as the best model for estimating each biomass component, i.e. above-ground total mass AGW, below-ground total mass BGW, and whole individual mass. Among models developed to estimate tree height H from D, we selected a regression model with a coefficient corresponding to an asymptotic height as the best fit. The D-AGW relationship at our study site differed significantly from models developed previously for other regions of the Amazon. We explain this regional variation in part by regional differences in D-H relationships of sample trees. The D-BGW relationship at our site also differed significantly from that in the central Amazon. However, AGW-BGW relationships were consistent between the upper Rio Negro forest and other forests in the central Amazon, in that the BGW-AGW ratio was constant as 0.136 regardless of tree size. On the basis of D-based allometry and census data from 23 plots established in the upper Rio Negro region, we estimated a stand-level total biomass (dry mass) of 252.6Mgha -1. This estimate is at least 73% lower than the potential stand biomass for the region previously suggested by several meta-analyses. © 2012 Elsevier B.V.
metadata.dc.identifier.doi: 10.1016/j.foreco.2012.04.028
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