Diametric distribution of species in a tropical rain forest in southern of Rio de Janeiro State, Brazil

Detalhes bibliográficos
Autor(a) principal: Cysneiros, Vinicius Costa
Data de Publicação: 2017
Outros Autores: Amorim, Thiago de Azevedo, Mendonça Júnior, Joaquim de Oliveira, Gaui, Tatiana Dias, de Moraes, Juan Carlos Resende, Braz, Denise Monte, Machado, Sebastião do Amaral
Tipo de documento: Artigo
Idioma: por
Título da fonte: Pesquisa Florestal Brasileira (Online)
Texto Completo: https://pfb.cnpf.embrapa.br/pfb/index.php/pfb/article/view/1070
Resumo: The goal of this study was to evaluate the performance and select probability density functions to describe the diametric distributions of the forest community and the main three species in a tropical rain forest in southern of Rio de Janeiro State. We tested the functions: Normal, Normal Log, Beta, Gamma, Sb Johnson and Weibull. Adjustments were carried out using Solver tool (MSExcel®) which uses the reduced linear gradient algorithm, optimizing the functions parameters. Value D Kolmogorov–Smirnov and estimation of standard error (Syx%) were evaluate to select the best model. In general, Sb Johnson and Weibull functions presented better statistics adjustment and greater precision in the estimates. Even representing the reality of the distribution, the smaller class intervals did not provide better adjustments, more precise estimates being provided by the larger ranges and smaller classes.
id EMBRAPA-5_add6c0ab0af5f3b00d34fa5815771fd9
oai_identifier_str oai:pfb.cnpf.embrapa.br/pfb:article/1070
network_acronym_str EMBRAPA-5
network_name_str Pesquisa Florestal Brasileira (Online)
repository_id_str
spelling Diametric distribution of species in a tropical rain forest in southern of Rio de Janeiro State, BrazilDistribuição diamétrica de espécies da Floresta Ombrófila Densa no Sul do Estado do Rio de JaneiroFloresta AtlânticaFunções densidade de probabilidadeModelagemAtlantic ForestDensity probability functionsModelingThe goal of this study was to evaluate the performance and select probability density functions to describe the diametric distributions of the forest community and the main three species in a tropical rain forest in southern of Rio de Janeiro State. We tested the functions: Normal, Normal Log, Beta, Gamma, Sb Johnson and Weibull. Adjustments were carried out using Solver tool (MSExcel®) which uses the reduced linear gradient algorithm, optimizing the functions parameters. Value D Kolmogorov–Smirnov and estimation of standard error (Syx%) were evaluate to select the best model. In general, Sb Johnson and Weibull functions presented better statistics adjustment and greater precision in the estimates. Even representing the reality of the distribution, the smaller class intervals did not provide better adjustments, more precise estimates being provided by the larger ranges and smaller classes.O objetivo do presente estudo foi avaliar o desempenho e selecionar funções densidade de probabilidade que descrevam a distribuição diamétrica da comunidade florestal e das três principais espécies da Floresta Ombrófila Densa no sul do estado do Rio de Janeiro. Foram testadas as funções Normal, Log Normal, Beta, Gama, Sb de Johnson e Weibull. Os ajustes foram realizados com auxílio da ferramenta Solver (MSExcel®), que utiliza o algoritmo linear de gradiente reduzido para otimização dos parâmetros das funções. Para a seleção do melhor modelo foram avaliados o valor D de Kolmogorov – Smirnov e o erro padrão da estimativa (Syx %). De maneira geral, as funções Sb de Johnson e Weibull apresentaram as melhores estatísticas de ajuste e maior precisão nas estimativas. Mesmo representando melhor a realidade da distribuição, os menores intervalos de classe não forneceram os melhores ajustes, sendo as estimativas mais precisas propiciadas pelos maiores intervalos e menores números de classes.Embrapa Florestas2017-03-31info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://pfb.cnpf.embrapa.br/pfb/index.php/pfb/article/view/107010.4336/2017.pfb.37.89.1070Pesquisa Florestal Brasileira; v. 37 n. 89 (2017): jan./mar.; 1-10Pesquisa Florestal Brasileira; Vol. 37 No. 89 (2017): jan./mar.; 1-101983-26051809-3647reponame:Pesquisa Florestal Brasileira (Online)instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa)instacron:EMBRAPAporhttps://pfb.cnpf.embrapa.br/pfb/index.php/pfb/article/view/1070/562Copyright (c) 2017 Vinicius Costa Cysneiros, Thiago de Azevedo Amorim, Joaquim de Oliveira Mendonça Júnior, Tatiana Dias Gaui, Juan Carlos Resende de Moraes, Denise Monte Braz, Sebastião do Amaral Machadohttps://creativecommons.org/licenses/by-nc-nd/4.0info:eu-repo/semantics/openAccessCysneiros, Vinicius CostaAmorim, Thiago de AzevedoMendonça Júnior, Joaquim de OliveiraGaui, Tatiana Diasde Moraes, Juan Carlos ResendeBraz, Denise MonteMachado, Sebastião do Amaral2018-01-07T18:59:59Zoai:pfb.cnpf.embrapa.br/pfb:article/1070Revistahttps://pfb.cnpf.embrapa.br/pfb/index.php/pfb/PUBhttps://pfb.cnpf.embrapa.br/pfb/index.php/pfb/oaipfb@embrapa.br || revista.pfb@gmail.com || patricia.mattos@embrapa.br1983-26051809-3647opendoar:2018-01-07T18:59:59Pesquisa Florestal Brasileira (Online) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa)false
dc.title.none.fl_str_mv Diametric distribution of species in a tropical rain forest in southern of Rio de Janeiro State, Brazil
Distribuição diamétrica de espécies da Floresta Ombrófila Densa no Sul do Estado do Rio de Janeiro
title Diametric distribution of species in a tropical rain forest in southern of Rio de Janeiro State, Brazil
spellingShingle Diametric distribution of species in a tropical rain forest in southern of Rio de Janeiro State, Brazil
Cysneiros, Vinicius Costa
Floresta Atlântica
Funções densidade de probabilidade
Modelagem
Atlantic Forest
Density probability functions
Modeling
title_short Diametric distribution of species in a tropical rain forest in southern of Rio de Janeiro State, Brazil
title_full Diametric distribution of species in a tropical rain forest in southern of Rio de Janeiro State, Brazil
title_fullStr Diametric distribution of species in a tropical rain forest in southern of Rio de Janeiro State, Brazil
title_full_unstemmed Diametric distribution of species in a tropical rain forest in southern of Rio de Janeiro State, Brazil
title_sort Diametric distribution of species in a tropical rain forest in southern of Rio de Janeiro State, Brazil
author Cysneiros, Vinicius Costa
author_facet Cysneiros, Vinicius Costa
Amorim, Thiago de Azevedo
Mendonça Júnior, Joaquim de Oliveira
Gaui, Tatiana Dias
de Moraes, Juan Carlos Resende
Braz, Denise Monte
Machado, Sebastião do Amaral
author_role author
author2 Amorim, Thiago de Azevedo
Mendonça Júnior, Joaquim de Oliveira
Gaui, Tatiana Dias
de Moraes, Juan Carlos Resende
Braz, Denise Monte
Machado, Sebastião do Amaral
author2_role author
author
author
author
author
author
dc.contributor.author.fl_str_mv Cysneiros, Vinicius Costa
Amorim, Thiago de Azevedo
Mendonça Júnior, Joaquim de Oliveira
Gaui, Tatiana Dias
de Moraes, Juan Carlos Resende
Braz, Denise Monte
Machado, Sebastião do Amaral
dc.subject.por.fl_str_mv Floresta Atlântica
Funções densidade de probabilidade
Modelagem
Atlantic Forest
Density probability functions
Modeling
topic Floresta Atlântica
Funções densidade de probabilidade
Modelagem
Atlantic Forest
Density probability functions
Modeling
description The goal of this study was to evaluate the performance and select probability density functions to describe the diametric distributions of the forest community and the main three species in a tropical rain forest in southern of Rio de Janeiro State. We tested the functions: Normal, Normal Log, Beta, Gamma, Sb Johnson and Weibull. Adjustments were carried out using Solver tool (MSExcel®) which uses the reduced linear gradient algorithm, optimizing the functions parameters. Value D Kolmogorov–Smirnov and estimation of standard error (Syx%) were evaluate to select the best model. In general, Sb Johnson and Weibull functions presented better statistics adjustment and greater precision in the estimates. Even representing the reality of the distribution, the smaller class intervals did not provide better adjustments, more precise estimates being provided by the larger ranges and smaller classes.
publishDate 2017
dc.date.none.fl_str_mv 2017-03-31
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://pfb.cnpf.embrapa.br/pfb/index.php/pfb/article/view/1070
10.4336/2017.pfb.37.89.1070
url https://pfb.cnpf.embrapa.br/pfb/index.php/pfb/article/view/1070
identifier_str_mv 10.4336/2017.pfb.37.89.1070
dc.language.iso.fl_str_mv por
language por
dc.relation.none.fl_str_mv https://pfb.cnpf.embrapa.br/pfb/index.php/pfb/article/view/1070/562
dc.rights.driver.fl_str_mv https://creativecommons.org/licenses/by-nc-nd/4.0
info:eu-repo/semantics/openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-nd/4.0
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Embrapa Florestas
publisher.none.fl_str_mv Embrapa Florestas
dc.source.none.fl_str_mv Pesquisa Florestal Brasileira; v. 37 n. 89 (2017): jan./mar.; 1-10
Pesquisa Florestal Brasileira; Vol. 37 No. 89 (2017): jan./mar.; 1-10
1983-2605
1809-3647
reponame:Pesquisa Florestal Brasileira (Online)
instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa)
instacron:EMBRAPA
instname_str Empresa Brasileira de Pesquisa Agropecuária (Embrapa)
instacron_str EMBRAPA
institution EMBRAPA
reponame_str Pesquisa Florestal Brasileira (Online)
collection Pesquisa Florestal Brasileira (Online)
repository.name.fl_str_mv Pesquisa Florestal Brasileira (Online) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa)
repository.mail.fl_str_mv pfb@embrapa.br || revista.pfb@gmail.com || patricia.mattos@embrapa.br
_version_ 1783370935421632512

Registros relacionados