Autoregressive modelling of species richness in the Brazilian Cerrado
Autor(a) principal: | |
---|---|
Data de Publicação: | 2008 |
Outros Autores: | , , , |
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. |
id |
IIE-1_e0d42d4a7d7cc6ee3f20f20b7a6b581d |
---|---|
oai_identifier_str |
oai:scielo:S1519-69842008000200003 |
network_acronym_str |
IIE-1 |
network_name_str |
Brazilian Journal of Biology |
repository_id_str |
|
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 |
_version_ |
1752129876814462976 |