Allometric models for estimating above- and below-ground biomass in Amazonian forests at São Gabriel da Cachoeira in the upper Rio Negro, Brazil
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 t...
| Autor principal: | Lima, Adriano José Nogueira |
|---|---|
| Outros Autores: | 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 |
| Grau: | Artigo |
| Idioma: | English |
| Publicado em: |
Forest Ecology and Management
2020
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| Acesso em linha: |
https://repositorio.inpa.gov.br/handle/1/18013 |
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oai:repositorio:1-18013 |
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oai:repositorio:1-18013 Allometric models for estimating above- and below-ground biomass in Amazonian forests at São Gabriel da Cachoeira in the upper Rio Negro, Brazil 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 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 Brasil Carbon Climates Estimation Mathematical Models Regression Analysis Amazon River Amazonas Brasil Rio Negro [south America] 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. 2020-06-15T21:50:56Z 2020-06-15T21:50:56Z 2012 Artigo https://repositorio.inpa.gov.br/handle/1/18013 10.1016/j.foreco.2012.04.028 en Volume 277, Pags. 163-172 Restrito Forest Ecology and Management |
| institution |
Instituto Nacional de Pesquisas da Amazônia - Repositório Institucional |
| collection |
INPA-RI |
| language |
English |
| topic |
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 Brasil Carbon Climates Estimation Mathematical Models Regression Analysis Amazon River Amazonas Brasil Rio Negro [south America] |
| spellingShingle |
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 Brasil Carbon Climates Estimation Mathematical Models Regression Analysis Amazon River Amazonas Brasil Rio Negro [south America] Lima, Adriano José Nogueira Allometric models for estimating above- and below-ground biomass in Amazonian forests at São Gabriel da Cachoeira in the upper Rio Negro, Brazil |
| topic_facet |
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 Brasil Carbon Climates Estimation Mathematical Models Regression Analysis Amazon River Amazonas Brasil Rio Negro [south America] |
| description |
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. |
| format |
Artigo |
| author |
Lima, Adriano José Nogueira |
| author2 |
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 |
| author2Str |
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 |
| title |
Allometric models for estimating above- and below-ground biomass in Amazonian forests at São Gabriel da Cachoeira in the upper Rio Negro, Brazil |
| title_short |
Allometric models for estimating above- and below-ground biomass in Amazonian forests at São Gabriel da Cachoeira in the upper Rio Negro, Brazil |
| title_full |
Allometric models for estimating above- and below-ground biomass in Amazonian forests at São Gabriel da Cachoeira in the upper Rio Negro, Brazil |
| title_fullStr |
Allometric models for estimating above- and below-ground biomass in Amazonian forests at São Gabriel da Cachoeira in the upper Rio Negro, Brazil |
| title_full_unstemmed |
Allometric models for estimating above- and below-ground biomass in Amazonian forests at São Gabriel da Cachoeira in the upper Rio Negro, Brazil |
| title_sort |
allometric models for estimating above- and below-ground biomass in amazonian forests at são gabriel da cachoeira in the upper rio negro, brazil |
| publisher |
Forest Ecology and Management |
| publishDate |
2020 |
| url |
https://repositorio.inpa.gov.br/handle/1/18013 |
| _version_ |
1787143934224367616 |
| score |
11.755432 |