Autoregressive modelling of species richness in the Brazilian Cerrado

Detalhes bibliográficos
Autor(a) principal: Vieira,CM.
Data de Publicação: 2008
Outros Autores: Blamires,D, Diniz-Filho,JAF., Bini,LM., Rangel,TFLVB.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Brazilian Journal of Biology
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1519-69842008000200003
Resumo: Spatial autocorrelation is the lack of independence between pairs of observations at given distances within a geographical space, a phenomenon commonly found in ecological data. Taking into account spatial autocorrelation when evaluating problems in geographical ecology, including gradients in species richness, is important to describe both the spatial structure in data and to correct the bias in Type I errors of standard statistical analyses. However, to effectively solve these problems it is necessary to establish the best way to incorporate the spatial structure to be used in the models. In this paper, we applied autoregressive models based on different types of connections and distances between 181 cells covering the Cerrado region of Central Brazil to study the spatial variation in mammal and bird species richness across the biome. Spatial structure was stronger for birds than for mammals, with R² values ranging from 0.77 to 0.94 for mammals and from 0.77 to 0.97 for birds, for models based on different definitions of spatial structures. According to the Akaike Information Criterion (AIC), the best autoregressive model was obtained by using the rook connection. In general, these results furnish guidelines for future modelling of species richness patterns in relation to environmental predictors and other variables expressing human occupation in the biome.
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spelling Autoregressive modelling of species richness in the Brazilian Cerradospatial autoregressionspecies richnessCerradobirdsmammalsSpatial autocorrelation is the lack of independence between pairs of observations at given distances within a geographical space, a phenomenon commonly found in ecological data. Taking into account spatial autocorrelation when evaluating problems in geographical ecology, including gradients in species richness, is important to describe both the spatial structure in data and to correct the bias in Type I errors of standard statistical analyses. However, to effectively solve these problems it is necessary to establish the best way to incorporate the spatial structure to be used in the models. In this paper, we applied autoregressive models based on different types of connections and distances between 181 cells covering the Cerrado region of Central Brazil to study the spatial variation in mammal and bird species richness across the biome. Spatial structure was stronger for birds than for mammals, with R² values ranging from 0.77 to 0.94 for mammals and from 0.77 to 0.97 for birds, for models based on different definitions of spatial structures. According to the Akaike Information Criterion (AIC), the best autoregressive model was obtained by using the rook connection. In general, these results furnish guidelines for future modelling of species richness patterns in relation to environmental predictors and other variables expressing human occupation in the biome.Instituto Internacional de Ecologia2008-05-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S1519-69842008000200003Brazilian Journal of Biology v.68 n.2 2008reponame:Brazilian Journal of Biologyinstname:Instituto Internacional de Ecologia (IIE)instacron:IIE10.1590/S1519-69842008000200003info:eu-repo/semantics/openAccessVieira,CM.Blamires,DDiniz-Filho,JAF.Bini,LM.Rangel,TFLVB.eng2008-07-21T00:00:00Zoai:scielo:S1519-69842008000200003Revistahttps://www.scielo.br/j/bjb/https://old.scielo.br/oai/scielo-oai.phpbjb@bjb.com.br||bjb@bjb.com.br1678-43751519-6984opendoar:2008-07-21T00:00Brazilian Journal of Biology - Instituto Internacional de Ecologia (IIE)false
dc.title.none.fl_str_mv Autoregressive modelling of species richness in the Brazilian Cerrado
title Autoregressive modelling of species richness in the Brazilian Cerrado
spellingShingle Autoregressive modelling of species richness in the Brazilian Cerrado
Vieira,CM.
spatial autoregression
species richness
Cerrado
birds
mammals
title_short Autoregressive modelling of species richness in the Brazilian Cerrado
title_full Autoregressive modelling of species richness in the Brazilian Cerrado
title_fullStr Autoregressive modelling of species richness in the Brazilian Cerrado
title_full_unstemmed Autoregressive modelling of species richness in the Brazilian Cerrado
title_sort Autoregressive modelling of species richness in the Brazilian Cerrado
author Vieira,CM.
author_facet Vieira,CM.
Blamires,D
Diniz-Filho,JAF.
Bini,LM.
Rangel,TFLVB.
author_role author
author2 Blamires,D
Diniz-Filho,JAF.
Bini,LM.
Rangel,TFLVB.
author2_role author
author
author
author
dc.contributor.author.fl_str_mv Vieira,CM.
Blamires,D
Diniz-Filho,JAF.
Bini,LM.
Rangel,TFLVB.
dc.subject.por.fl_str_mv spatial autoregression
species richness
Cerrado
birds
mammals
topic spatial autoregression
species richness
Cerrado
birds
mammals
description Spatial autocorrelation is the lack of independence between pairs of observations at given distances within a geographical space, a phenomenon commonly found in ecological data. Taking into account spatial autocorrelation when evaluating problems in geographical ecology, including gradients in species richness, is important to describe both the spatial structure in data and to correct the bias in Type I errors of standard statistical analyses. However, to effectively solve these problems it is necessary to establish the best way to incorporate the spatial structure to be used in the models. In this paper, we applied autoregressive models based on different types of connections and distances between 181 cells covering the Cerrado region of Central Brazil to study the spatial variation in mammal and bird species richness across the biome. Spatial structure was stronger for birds than for mammals, with R² values ranging from 0.77 to 0.94 for mammals and from 0.77 to 0.97 for birds, for models based on different definitions of spatial structures. According to the Akaike Information Criterion (AIC), the best autoregressive model was obtained by using the rook connection. In general, these results furnish guidelines for future modelling of species richness patterns in relation to environmental predictors and other variables expressing human occupation in the biome.
publishDate 2008
dc.date.none.fl_str_mv 2008-05-01
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=S1519-69842008000200003
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1519-69842008000200003
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/S1519-69842008000200003
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 Instituto Internacional de Ecologia
publisher.none.fl_str_mv Instituto Internacional de Ecologia
dc.source.none.fl_str_mv Brazilian Journal of Biology v.68 n.2 2008
reponame:Brazilian Journal of Biology
instname:Instituto Internacional de Ecologia (IIE)
instacron:IIE
instname_str Instituto Internacional de Ecologia (IIE)
instacron_str IIE
institution IIE
reponame_str Brazilian Journal of Biology
collection Brazilian Journal of Biology
repository.name.fl_str_mv Brazilian Journal of Biology - Instituto Internacional de Ecologia (IIE)
repository.mail.fl_str_mv bjb@bjb.com.br||bjb@bjb.com.br
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