Predictive modeling distribution of pioneer species in the state of Minas Gerais, Brazil

Detalhes bibliográficos
Autor(a) principal: Nunes Coelho, Guilherme Leite
Data de Publicação: 2016
Outros Autores: De Carvalho, Luis Marcelo Tavares, Gomide, Lucas Rezende
Tipo de documento: Artigo
Idioma: por
Título da fonte: Pesquisa Agropecuária Brasileira (Online)
Texto Completo: https://seer.sct.embrapa.br/index.php/pab/article/view/22276
Resumo: The objective of this work was to determine the potential distribution of 23 pioneer species in the state of Minas Gerais, Brazil, as well as to identify the environmental variables that influence their distributions. The Maxent algorithm was chosen to associate the occurrence of species with the following bioclimatic variables: diurnal temperature variation, isothermality, temperature seasonality, driest month precipitation, precipitation seasonality (coefficient of variation), and actual evapotranspiration. The normalized difference vegetation index (NDVI), flora conservation status, and the spatial heterogeneity of vegetation types were also evaluated, besides erodibility (susceptibility of soil to erosion), groundwater availability, soil texture, organic matter content, mineral occurrence (existing mineral species by lithological unit), pedological simplified map, slope and altitude. The species Anadenanthera colubrina was the most suitable for the Caatinga biome, followed by Casearia sylvestris and Plathymenia reticulate, indicated for the Atlantic Forest and the Cerrado biomes, respectively. The use of Maxent is recommended as a tool to guide conservation plans that require the indication of species, aiming to recover degraded or deforested vegetation areas.
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spelling Predictive modeling distribution of pioneer species in the state of Minas Gerais, BrazilModelagem preditiva de distribuição de espécies pioneiras no Estado de Minas GeraisMaxent; conservation plan; native plant; habitat predictionMaxent; plano de conservação; planta nativa; predição de habitatThe objective of this work was to determine the potential distribution of 23 pioneer species in the state of Minas Gerais, Brazil, as well as to identify the environmental variables that influence their distributions. The Maxent algorithm was chosen to associate the occurrence of species with the following bioclimatic variables: diurnal temperature variation, isothermality, temperature seasonality, driest month precipitation, precipitation seasonality (coefficient of variation), and actual evapotranspiration. The normalized difference vegetation index (NDVI), flora conservation status, and the spatial heterogeneity of vegetation types were also evaluated, besides erodibility (susceptibility of soil to erosion), groundwater availability, soil texture, organic matter content, mineral occurrence (existing mineral species by lithological unit), pedological simplified map, slope and altitude. The species Anadenanthera colubrina was the most suitable for the Caatinga biome, followed by Casearia sylvestris and Plathymenia reticulate, indicated for the Atlantic Forest and the Cerrado biomes, respectively. The use of Maxent is recommended as a tool to guide conservation plans that require the indication of species, aiming to recover degraded or deforested vegetation areas.O objetivo deste trabalho foi determinar a distribuição potencial de 23 espécies pioneiras no Estado de Minas Gerias, além de identificar as variáveis ambientais que influenciam as suas distribuições. O algoritmo Maxent foi escolhido para relacionar a ocorrência de espécies às seguintes variáveis bioclimáticas: variação diurna de temperatura, isotermalidade, sazonalidade da temperatura, precipitação do mês mais seco, sazonalidade da precipitação (coeficiente de variação) e evapotranspiração real. Também foram avaliados índice de vegetação por diferença normalizada (NDVI), grau de conservação da flora e heterogeneidade espacial de fitofisionomias, bem como erodibilidade (suscetibilidade do solo à erosão), disponibilidade de água subterrânea, textura do solo, teor de matéria orgânica, ocorrência mineral (espécies minerais existentes por unidade litológica), mapa pedológico simplificado, declividade e altitude. A espécie Anadenanthera colubrina foi a mais indicada para o bioma Caatinga, seguida de Casearia sylvestris e Plathymenia reticulata, indicadas para o bioma Mata Atlântica e Cerrado, respectivamente. Recomenda-se utilizar o Maxent como ferramenta para orientar os planos de conservação que necessitam de indicação de espécies, para recuperar áreas de vegetação degradadas ou desmatadas.Pesquisa Agropecuaria BrasileiraPesquisa Agropecuária BrasileiraCoordenação de Aperfeiçoamento de Pessoal de Nível Superior (Capes)Nunes Coelho, Guilherme LeiteDe Carvalho, Luis Marcelo TavaresGomide, Lucas Rezende2016-05-19info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://seer.sct.embrapa.br/index.php/pab/article/view/22276Pesquisa Agropecuaria Brasileira; v.51, n.3, mar. 2016; 207-214Pesquisa Agropecuária Brasileira; v.51, n.3, mar. 2016; 207-2141678-39210100-104xreponame:Pesquisa Agropecuária Brasileira (Online)instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa)instacron:EMBRAPAporhttps://seer.sct.embrapa.br/index.php/pab/article/view/22276/13275Direitos autorais 2016 Pesquisa Agropecuária Brasileirainfo:eu-repo/semantics/openAccess2016-05-19T18:03:31Zoai:ojs.seer.sct.embrapa.br:article/22276Revistahttp://seer.sct.embrapa.br/index.php/pabPRIhttps://old.scielo.br/oai/scielo-oai.phppab@sct.embrapa.br || sct.pab@embrapa.br1678-39210100-204Xopendoar:2016-05-19T18:03:31Pesquisa Agropecuária Brasileira (Online) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa)false
dc.title.none.fl_str_mv Predictive modeling distribution of pioneer species in the state of Minas Gerais, Brazil
Modelagem preditiva de distribuição de espécies pioneiras no Estado de Minas Gerais
title Predictive modeling distribution of pioneer species in the state of Minas Gerais, Brazil
spellingShingle Predictive modeling distribution of pioneer species in the state of Minas Gerais, Brazil
Nunes Coelho, Guilherme Leite
Maxent; conservation plan; native plant; habitat prediction
Maxent; plano de conservação; planta nativa; predição de habitat
title_short Predictive modeling distribution of pioneer species in the state of Minas Gerais, Brazil
title_full Predictive modeling distribution of pioneer species in the state of Minas Gerais, Brazil
title_fullStr Predictive modeling distribution of pioneer species in the state of Minas Gerais, Brazil
title_full_unstemmed Predictive modeling distribution of pioneer species in the state of Minas Gerais, Brazil
title_sort Predictive modeling distribution of pioneer species in the state of Minas Gerais, Brazil
author Nunes Coelho, Guilherme Leite
author_facet Nunes Coelho, Guilherme Leite
De Carvalho, Luis Marcelo Tavares
Gomide, Lucas Rezende
author_role author
author2 De Carvalho, Luis Marcelo Tavares
Gomide, Lucas Rezende
author2_role author
author
dc.contributor.none.fl_str_mv
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (Capes)
dc.contributor.author.fl_str_mv Nunes Coelho, Guilherme Leite
De Carvalho, Luis Marcelo Tavares
Gomide, Lucas Rezende
dc.subject.por.fl_str_mv Maxent; conservation plan; native plant; habitat prediction
Maxent; plano de conservação; planta nativa; predição de habitat
topic Maxent; conservation plan; native plant; habitat prediction
Maxent; plano de conservação; planta nativa; predição de habitat
description The objective of this work was to determine the potential distribution of 23 pioneer species in the state of Minas Gerais, Brazil, as well as to identify the environmental variables that influence their distributions. The Maxent algorithm was chosen to associate the occurrence of species with the following bioclimatic variables: diurnal temperature variation, isothermality, temperature seasonality, driest month precipitation, precipitation seasonality (coefficient of variation), and actual evapotranspiration. The normalized difference vegetation index (NDVI), flora conservation status, and the spatial heterogeneity of vegetation types were also evaluated, besides erodibility (susceptibility of soil to erosion), groundwater availability, soil texture, organic matter content, mineral occurrence (existing mineral species by lithological unit), pedological simplified map, slope and altitude. The species Anadenanthera colubrina was the most suitable for the Caatinga biome, followed by Casearia sylvestris and Plathymenia reticulate, indicated for the Atlantic Forest and the Cerrado biomes, respectively. The use of Maxent is recommended as a tool to guide conservation plans that require the indication of species, aiming to recover degraded or deforested vegetation areas.
publishDate 2016
dc.date.none.fl_str_mv 2016-05-19
dc.type.none.fl_str_mv
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
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format article
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dc.identifier.uri.fl_str_mv https://seer.sct.embrapa.br/index.php/pab/article/view/22276
url https://seer.sct.embrapa.br/index.php/pab/article/view/22276
dc.language.iso.fl_str_mv por
language por
dc.relation.none.fl_str_mv https://seer.sct.embrapa.br/index.php/pab/article/view/22276/13275
dc.rights.driver.fl_str_mv Direitos autorais 2016 Pesquisa Agropecuária Brasileira
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Direitos autorais 2016 Pesquisa Agropecuária Brasileira
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Pesquisa Agropecuaria Brasileira
Pesquisa Agropecuária Brasileira
publisher.none.fl_str_mv Pesquisa Agropecuaria Brasileira
Pesquisa Agropecuária Brasileira
dc.source.none.fl_str_mv Pesquisa Agropecuaria Brasileira; v.51, n.3, mar. 2016; 207-214
Pesquisa Agropecuária Brasileira; v.51, n.3, mar. 2016; 207-214
1678-3921
0100-104x
reponame:Pesquisa Agropecuária Brasileira (Online)
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reponame_str Pesquisa Agropecuária Brasileira (Online)
collection Pesquisa Agropecuária Brasileira (Online)
repository.name.fl_str_mv Pesquisa Agropecuária Brasileira (Online) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa)
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