Please use this identifier to cite or link to this item: https://repositorio.inpa.gov.br/handle/1/18013
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dc.contributor.authorLima, Adriano José Nogueira-
dc.contributor.authorSuwa, Rempei-
dc.contributor.authorRibeiro, Gabriel Henrique Pires de Mello-
dc.contributor.authorKajimoto, Takuya-
dc.contributor.authorSantos, Joaquim dos-
dc.contributor.authorSilva, Roseana Pereira da-
dc.contributor.authorSouza, Cacilda Adélia Sampaio de-
dc.contributor.authorBarros, Priscila Castro de-
dc.contributor.authorNoguchi, Hideyuki-
dc.contributor.authorIshizuka, Moriyoshi-
dc.contributor.authorHiguchi, Niro-
dc.date.accessioned2020-06-15T21:50:56Z-
dc.date.available2020-06-15T21:50:56Z-
dc.date.issued2012-
dc.identifier.urihttps://repositorio.inpa.gov.br/handle/1/18013-
dc.description.abstractPrecise 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.en
dc.language.isoenpt_BR
dc.relation.ispartofVolume 277, Pags. 163-172pt_BR
dc.rightsRestrito*
dc.subjectA-coefficienten
dc.subjectAllometric Modelsen
dc.subjectAmazonian Forestsen
dc.subjectBest Fiten
dc.subjectBest Modelen
dc.subjectBiomass Componentsen
dc.subjectBiomass Estimationen
dc.subjectBrazilian Amazonen
dc.subjectCarbon Dynamicsen
dc.subjectCarbon Stocksen
dc.subjectCensus Dataen
dc.subjectDry Massen
dc.subjectMeta Analysisen
dc.subjectPower Functionsen
dc.subjectPrimary Foresten
dc.subjectRegional Scaleen
dc.subjectRegional Variationen
dc.subjectRegression Modelen
dc.subjectRio Negroen
dc.subjectSingle Variableen
dc.subjectStem Diameteren
dc.subjectStudy Sitesen
dc.subjectTotal Biomassen
dc.subjectTotal Massen
dc.subjectTree Heighten
dc.subjectTree Sizeen
dc.subjectBiomassen
dc.subjectClimate Changeen
dc.subjectEstimationen
dc.subjectPopulation Statisticsen
dc.subjectRegression Analysisen
dc.subjectForestryen
dc.subjectAboveground Biomassen
dc.subjectAllometryen
dc.subjectBelowground Biomassen
dc.subjectCarbon Sinken
dc.subjectForest Ecosystemen
dc.subjectGrowth Modelingen
dc.subjectHeight Determinationen
dc.subjectMeta Analysisen
dc.subjectBiological Populationsen
dc.subjectBiomassen
dc.subjectCarbonen
dc.subjectClimatesen
dc.subjectEstimationen
dc.subjectMathematical Modelsen
dc.subjectRegression Analysisen
dc.subjectAmazon Riveren
dc.subjectAmazonasen
dc.subjectRio Negro [south America]en
dc.titleAllometric models for estimating above- and below-ground biomass in Amazonian forests at São Gabriel da Cachoeira in the upper Rio Negro, Brazilen
dc.typeArtigopt_BR
dc.identifier.doi10.1016/j.foreco.2012.04.028-
dc.publisher.journalForest Ecology and Managementpt_BR
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