Spatial distribution of wood volume in Brazilian savannas
Autor(a) principal: | |
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Data de Publicação: | 2019 |
Outros Autores: | , , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Anais da Academia Brasileira de Ciências (Online) |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652019000700853 |
Resumo: | Abstract: Here we model and describe the wood volume of Cerrado Sensu Stricto, a highly heterogeneous vegetation type in the Savanna biome, in the state of Minas Gerais, Brazil, integrating forest inventory data with spatial-environmental variables, multivariate regression, and regression kriging. Our study contributes to a better understanding of the factors that affect the spatial distribution of the wood volume of this vegetation type as well as allowing better representation of the spatial heterogeneity of this biome. Wood volume estimates were obtained through regression models using different environmental variables as independent variables. Using the best fitted model, spatial analysis of the residuals was carried out by selecting a semivariogram model for generating an ordinary kriging map, which in turn was used with the fitted regression model in the regression kriging technique. Seasonality of both temperature and precipitation, along with the density of deforestation, explained the variations of wood volume throughout Minas Gerais. The spatial distribution of predicted wood volume of Cerrado Sensu Stricto in Minas Gerais revealed the high variability of this variable (15.32 to 98.38 m3 ha-1) and the decreasing gradient in the southeast-northwest direction. |
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Spatial distribution of wood volume in Brazilian savannascerrado sensu strictoforest inventorygeostatisticsregression krigingvolumetryAbstract: Here we model and describe the wood volume of Cerrado Sensu Stricto, a highly heterogeneous vegetation type in the Savanna biome, in the state of Minas Gerais, Brazil, integrating forest inventory data with spatial-environmental variables, multivariate regression, and regression kriging. Our study contributes to a better understanding of the factors that affect the spatial distribution of the wood volume of this vegetation type as well as allowing better representation of the spatial heterogeneity of this biome. Wood volume estimates were obtained through regression models using different environmental variables as independent variables. Using the best fitted model, spatial analysis of the residuals was carried out by selecting a semivariogram model for generating an ordinary kriging map, which in turn was used with the fitted regression model in the regression kriging technique. Seasonality of both temperature and precipitation, along with the density of deforestation, explained the variations of wood volume throughout Minas Gerais. The spatial distribution of predicted wood volume of Cerrado Sensu Stricto in Minas Gerais revealed the high variability of this variable (15.32 to 98.38 m3 ha-1) and the decreasing gradient in the southeast-northwest direction.Academia Brasileira de Ciências2019-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652019000700853Anais da Academia Brasileira de Ciências v.91 n.4 2019reponame:Anais da Academia Brasileira de Ciências (Online)instname:Academia Brasileira de Ciências (ABC)instacron:ABC10.1590/0001-3765201920180666info:eu-repo/semantics/openAccessSILVEIRA,EDUARDA M.O.REIS,ALINY A. DOSTERRA,MARCELA C.N.S.WITHEY,KIERAN D.MELLO,JOSÉ M. DEACERBI-JÚNIOR,FAUSTO W.FERRAZ FILHO,ANTONIO CARLOSMELLO,CARLOS R.eng2019-10-17T00:00:00Zoai:scielo:S0001-37652019000700853Revistahttp://www.scielo.br/aabchttps://old.scielo.br/oai/scielo-oai.php||aabc@abc.org.br1678-26900001-3765opendoar:2019-10-17T00:00Anais da Academia Brasileira de Ciências (Online) - Academia Brasileira de Ciências (ABC)false |
dc.title.none.fl_str_mv |
Spatial distribution of wood volume in Brazilian savannas |
title |
Spatial distribution of wood volume in Brazilian savannas |
spellingShingle |
Spatial distribution of wood volume in Brazilian savannas SILVEIRA,EDUARDA M.O. cerrado sensu stricto forest inventory geostatistics regression kriging volumetry |
title_short |
Spatial distribution of wood volume in Brazilian savannas |
title_full |
Spatial distribution of wood volume in Brazilian savannas |
title_fullStr |
Spatial distribution of wood volume in Brazilian savannas |
title_full_unstemmed |
Spatial distribution of wood volume in Brazilian savannas |
title_sort |
Spatial distribution of wood volume in Brazilian savannas |
author |
SILVEIRA,EDUARDA M.O. |
author_facet |
SILVEIRA,EDUARDA M.O. REIS,ALINY A. DOS TERRA,MARCELA C.N.S. WITHEY,KIERAN D. MELLO,JOSÉ M. DE ACERBI-JÚNIOR,FAUSTO W. FERRAZ FILHO,ANTONIO CARLOS MELLO,CARLOS R. |
author_role |
author |
author2 |
REIS,ALINY A. DOS TERRA,MARCELA C.N.S. WITHEY,KIERAN D. MELLO,JOSÉ M. DE ACERBI-JÚNIOR,FAUSTO W. FERRAZ FILHO,ANTONIO CARLOS MELLO,CARLOS R. |
author2_role |
author author author author author author author |
dc.contributor.author.fl_str_mv |
SILVEIRA,EDUARDA M.O. REIS,ALINY A. DOS TERRA,MARCELA C.N.S. WITHEY,KIERAN D. MELLO,JOSÉ M. DE ACERBI-JÚNIOR,FAUSTO W. FERRAZ FILHO,ANTONIO CARLOS MELLO,CARLOS R. |
dc.subject.por.fl_str_mv |
cerrado sensu stricto forest inventory geostatistics regression kriging volumetry |
topic |
cerrado sensu stricto forest inventory geostatistics regression kriging volumetry |
description |
Abstract: Here we model and describe the wood volume of Cerrado Sensu Stricto, a highly heterogeneous vegetation type in the Savanna biome, in the state of Minas Gerais, Brazil, integrating forest inventory data with spatial-environmental variables, multivariate regression, and regression kriging. Our study contributes to a better understanding of the factors that affect the spatial distribution of the wood volume of this vegetation type as well as allowing better representation of the spatial heterogeneity of this biome. Wood volume estimates were obtained through regression models using different environmental variables as independent variables. Using the best fitted model, spatial analysis of the residuals was carried out by selecting a semivariogram model for generating an ordinary kriging map, which in turn was used with the fitted regression model in the regression kriging technique. Seasonality of both temperature and precipitation, along with the density of deforestation, explained the variations of wood volume throughout Minas Gerais. The spatial distribution of predicted wood volume of Cerrado Sensu Stricto in Minas Gerais revealed the high variability of this variable (15.32 to 98.38 m3 ha-1) and the decreasing gradient in the southeast-northwest direction. |
publishDate |
2019 |
dc.date.none.fl_str_mv |
2019-01-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652019000700853 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652019000700853 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/0001-3765201920180666 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
text/html |
dc.publisher.none.fl_str_mv |
Academia Brasileira de Ciências |
publisher.none.fl_str_mv |
Academia Brasileira de Ciências |
dc.source.none.fl_str_mv |
Anais da Academia Brasileira de Ciências v.91 n.4 2019 reponame:Anais da Academia Brasileira de Ciências (Online) instname:Academia Brasileira de Ciências (ABC) instacron:ABC |
instname_str |
Academia Brasileira de Ciências (ABC) |
instacron_str |
ABC |
institution |
ABC |
reponame_str |
Anais da Academia Brasileira de Ciências (Online) |
collection |
Anais da Academia Brasileira de Ciências (Online) |
repository.name.fl_str_mv |
Anais da Academia Brasileira de Ciências (Online) - Academia Brasileira de Ciências (ABC) |
repository.mail.fl_str_mv |
||aabc@abc.org.br |
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1754302868145307648 |