Spatial regression techniques for inter‐population data: studying the relationships between morphological and environmental variation

Autores
Perez, S. I.; Diniz Filho, J. A. F.; Bernal, Valeria; Gonzalez, Paula Natalia
Año de publicación
2010
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Understanding the importance of environmental dimensions behind the morphological variation among populations has long been a central goal of evolutionary biology. The main objective of this study was to review the spatial regression techniques employed to test the association between morphological and environmental variables. In addition, we show empirically how spatial regression techniques can be used to test the association of cranialform variation among worldwide human populations with a set of ecological variables, taking into account the spatial autocorrelation in data. We suggest that spatial autocorrelation must be studied to explore the spatial structure underlying morphological variation and incorporated in regression models to provide more accurate statistical estimates of the relationships between morphological and ecological variables. Finally, we discuss the statistical properties of these techniques and the underlying reasons for using the spatial approach in population studies.
Fil: Perez, S. I.. Universidad Nacional de La Plata. Facultad de Ciencias Naturales y Museo. División Antropología; Argentina
Fil: Diniz Filho, J. A. F.. Universidade Federal de Goiás; Brasil
Fil: Bernal, Valeria. Universidad Nacional de La Plata. Facultad de Ciencias Naturales y Museo. División Antropología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata; Argentina
Fil: Gonzalez, Paula Natalia. Universidad Nacional de La Plata. Facultad de Ciencias Naturales y Museo. División Antropología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata; Argentina
Materia
AUTOCORRELATION
EVOLUTIONARY ANTHROPOLOGY
MORPHOMETRIC TECHNIQUES
SPATIAL STATISTICAL TECHNIQUES
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/243360
Acceder
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repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Spatial regression techniques for inter‐population data: studying the relationships between morphological and environmental variationPerez, S. I.Diniz Filho, J. A. F.Bernal, ValeriaGonzalez, Paula NataliaAUTOCORRELATIONEVOLUTIONARY ANTHROPOLOGYMORPHOMETRIC TECHNIQUESSPATIAL STATISTICAL TECHNIQUEShttps://purl.org/becyt/ford/1.6https://purl.org/becyt/ford/1Understanding the importance of environmental dimensions behind the morphological variation among populations has long been a central goal of evolutionary biology. The main objective of this study was to review the spatial regression techniques employed to test the association between morphological and environmental variables. In addition, we show empirically how spatial regression techniques can be used to test the association of cranialform variation among worldwide human populations with a set of ecological variables, taking into account the spatial autocorrelation in data. We suggest that spatial autocorrelation must be studied to explore the spatial structure underlying morphological variation and incorporated in regression models to provide more accurate statistical estimates of the relationships between morphological and ecological variables. Finally, we discuss the statistical properties of these techniques and the underlying reasons for using the spatial approach in population studies.Fil: Perez, S. I.. Universidad Nacional de La Plata. Facultad de Ciencias Naturales y Museo. División Antropología; ArgentinaFil: Diniz Filho, J. A. F.. Universidade Federal de Goiás; BrasilFil: Bernal, Valeria. Universidad Nacional de La Plata. Facultad de Ciencias Naturales y Museo. División Antropología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata; ArgentinaFil: Gonzalez, Paula Natalia. Universidad Nacional de La Plata. Facultad de Ciencias Naturales y Museo. División Antropología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata; ArgentinaWiley Blackwell Publishing, Inc2010-10info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/243360Perez, S. I.; Diniz Filho, J. A. F.; Bernal, Valeria; Gonzalez, Paula Natalia; Spatial regression techniques for inter‐population data: studying the relationships between morphological and environmental variation; Wiley Blackwell Publishing, Inc; Journal of Evolutionary Biology; 23; 2; 10-2010; 237-2481010-061XCONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://onlinelibrary.wiley.com/doi/10.1111/j.1420-9101.2009.01905.xinfo:eu-repo/semantics/altIdentifier/doi/10.1111/j.1420-9101.2009.01905.xinfo:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T09:33:44Zoai:ri.conicet.gov.ar:11336/243360instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 09:33:44.378CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Spatial regression techniques for inter‐population data: studying the relationships between morphological and environmental variation
title Spatial regression techniques for inter‐population data: studying the relationships between morphological and environmental variation
spellingShingle Spatial regression techniques for inter‐population data: studying the relationships between morphological and environmental variation
Perez, S. I.
AUTOCORRELATION
EVOLUTIONARY ANTHROPOLOGY
MORPHOMETRIC TECHNIQUES
SPATIAL STATISTICAL TECHNIQUES
title_short Spatial regression techniques for inter‐population data: studying the relationships between morphological and environmental variation
title_full Spatial regression techniques for inter‐population data: studying the relationships between morphological and environmental variation
title_fullStr Spatial regression techniques for inter‐population data: studying the relationships between morphological and environmental variation
title_full_unstemmed Spatial regression techniques for inter‐population data: studying the relationships between morphological and environmental variation
title_sort Spatial regression techniques for inter‐population data: studying the relationships between morphological and environmental variation
dc.creator.none.fl_str_mv Perez, S. I.
Diniz Filho, J. A. F.
Bernal, Valeria
Gonzalez, Paula Natalia
author Perez, S. I.
author_facet Perez, S. I.
Diniz Filho, J. A. F.
Bernal, Valeria
Gonzalez, Paula Natalia
author_role author
author2 Diniz Filho, J. A. F.
Bernal, Valeria
Gonzalez, Paula Natalia
author2_role author
author
author
dc.subject.none.fl_str_mv AUTOCORRELATION
EVOLUTIONARY ANTHROPOLOGY
MORPHOMETRIC TECHNIQUES
SPATIAL STATISTICAL TECHNIQUES
topic AUTOCORRELATION
EVOLUTIONARY ANTHROPOLOGY
MORPHOMETRIC TECHNIQUES
SPATIAL STATISTICAL TECHNIQUES
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.6
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Understanding the importance of environmental dimensions behind the morphological variation among populations has long been a central goal of evolutionary biology. The main objective of this study was to review the spatial regression techniques employed to test the association between morphological and environmental variables. In addition, we show empirically how spatial regression techniques can be used to test the association of cranialform variation among worldwide human populations with a set of ecological variables, taking into account the spatial autocorrelation in data. We suggest that spatial autocorrelation must be studied to explore the spatial structure underlying morphological variation and incorporated in regression models to provide more accurate statistical estimates of the relationships between morphological and ecological variables. Finally, we discuss the statistical properties of these techniques and the underlying reasons for using the spatial approach in population studies.
Fil: Perez, S. I.. Universidad Nacional de La Plata. Facultad de Ciencias Naturales y Museo. División Antropología; Argentina
Fil: Diniz Filho, J. A. F.. Universidade Federal de Goiás; Brasil
Fil: Bernal, Valeria. Universidad Nacional de La Plata. Facultad de Ciencias Naturales y Museo. División Antropología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata; Argentina
Fil: Gonzalez, Paula Natalia. Universidad Nacional de La Plata. Facultad de Ciencias Naturales y Museo. División Antropología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata; Argentina
description Understanding the importance of environmental dimensions behind the morphological variation among populations has long been a central goal of evolutionary biology. The main objective of this study was to review the spatial regression techniques employed to test the association between morphological and environmental variables. In addition, we show empirically how spatial regression techniques can be used to test the association of cranialform variation among worldwide human populations with a set of ecological variables, taking into account the spatial autocorrelation in data. We suggest that spatial autocorrelation must be studied to explore the spatial structure underlying morphological variation and incorporated in regression models to provide more accurate statistical estimates of the relationships between morphological and ecological variables. Finally, we discuss the statistical properties of these techniques and the underlying reasons for using the spatial approach in population studies.
publishDate 2010
dc.date.none.fl_str_mv 2010-10
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/243360
Perez, S. I.; Diniz Filho, J. A. F.; Bernal, Valeria; Gonzalez, Paula Natalia; Spatial regression techniques for inter‐population data: studying the relationships between morphological and environmental variation; Wiley Blackwell Publishing, Inc; Journal of Evolutionary Biology; 23; 2; 10-2010; 237-248
1010-061X
CONICET Digital
CONICET
url http://hdl.handle.net/11336/243360
identifier_str_mv Perez, S. I.; Diniz Filho, J. A. F.; Bernal, Valeria; Gonzalez, Paula Natalia; Spatial regression techniques for inter‐population data: studying the relationships between morphological and environmental variation; Wiley Blackwell Publishing, Inc; Journal of Evolutionary Biology; 23; 2; 10-2010; 237-248
1010-061X
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://onlinelibrary.wiley.com/doi/10.1111/j.1420-9101.2009.01905.x
info:eu-repo/semantics/altIdentifier/doi/10.1111/j.1420-9101.2009.01905.x
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Wiley Blackwell Publishing, Inc
publisher.none.fl_str_mv Wiley Blackwell Publishing, Inc
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.070432

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