Predictive modeling distribution of pioneer species in the state of Minas Gerais, Brazil
Autor(a) principal: | |
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Data de Publicação: | 2016 |
Outros Autores: | , |
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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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 info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
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) 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 Agropecuária Brasileira (Online) |
collection |
Pesquisa Agropecuária Brasileira (Online) |
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Pesquisa Agropecuária Brasileira (Online) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa) |
repository.mail.fl_str_mv |
pab@sct.embrapa.br || sct.pab@embrapa.br |
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1793416663577657344 |