Sympatry inference and network analysis in biogeography

Autores
Dos Santos, Daniel Andrés; Fernandez, Hugo Rafael; Cuezzo, Maria Gabriela; Dominguez, Eduardo
Año de publicación
2008
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
A new approach for biogeography to find patterns of sympatry, based on network analysis, is proposed. Biogeographic analysis focuses basically on sympatry patterns of species. Sympatry is a network (= relational) datum, but it has never been analyzed before using relational tools such as Network Analysis. Our approach to biogeographic analysis consists of two parts: first the sympatry inference and second the network analysis method (NAM). The sympatry inference method was designed to propose sympatry hypothesis, constructing a basal sympatry network based on punctual data, independent of a priori distributional area determination. In this way, two or more species are considered sympatric when there is interpenetration and relative proximity among their records of occurrence. In nature, groups of species presenting within-group sympatry and between-group allopatry constitute natural units (units of co-occurrence). These allopatric units are usually connected by intermediary species. The network analysis method (NAM) that we propose here is based on the identification and removal of intermediary species to segregate units of co-occurrence, using the betweenness measure and the clustering coefficient. The species ranges of the units of co-occurrence obtained are transferred to a map, being considered as candidates to areas of endemism. The new approach was implemented on three different real complex data sets (one of them a classic example previously used in biogeography) resulting in (1) independence of predefined spatial units; (2) definition of co-occurrence patterns from the sympatry network structure, not from species range similarities; (3) higher stability in results despite scale changes; (4) identification of candidates to areas of endemism supported by strictly endemic species; (5) identification of intermediary species with particular biological attributes. Copyright © Society of Systematic Biologists.
Fil: Dos Santos, Daniel Andrés. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto de Biodiversidad Neotropical. Universidad Nacional de Tucumán. Facultad de Ciencias Naturales e Instituto Miguel Lillo. Instituto de Biodiversidad Neotropical. Instituto de Biodiversidad Neotropical; Argentina
Fil: Fernandez, Hugo Rafael. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto de Biodiversidad Neotropical. Universidad Nacional de Tucumán. Facultad de Ciencias Naturales e Instituto Miguel Lillo. Instituto de Biodiversidad Neotropical. Instituto de Biodiversidad Neotropical; Argentina
Fil: Cuezzo, Maria Gabriela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto de Biodiversidad Neotropical. Universidad Nacional de Tucumán. Facultad de Ciencias Naturales e Instituto Miguel Lillo. Instituto de Biodiversidad Neotropical. Instituto de Biodiversidad Neotropical; Argentina
Fil: Dominguez, Eduardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto de Biodiversidad Neotropical. Universidad Nacional de Tucumán. Facultad de Ciencias Naturales e Instituto Miguel Lillo. Instituto de Biodiversidad Neotropical. Instituto de Biodiversidad Neotropical; Argentina
Materia
BETWEENNESS
CLUSTERING COEFFICIENT
DOT MAPS
HISTORICAL BIOGEOGRAPHY
INTERMEDIARY SPECIES
UNITS OF CO-OCCURRENCE
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:11336/141515
Acceder
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network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Sympatry inference and network analysis in biogeographyDos Santos, Daniel AndrésFernandez, Hugo RafaelCuezzo, Maria GabrielaDominguez, EduardoBETWEENNESSCLUSTERING COEFFICIENTDOT MAPSHISTORICAL BIOGEOGRAPHYINTERMEDIARY SPECIESUNITS OF CO-OCCURRENCEhttps://purl.org/becyt/ford/1.6https://purl.org/becyt/ford/1A new approach for biogeography to find patterns of sympatry, based on network analysis, is proposed. Biogeographic analysis focuses basically on sympatry patterns of species. Sympatry is a network (= relational) datum, but it has never been analyzed before using relational tools such as Network Analysis. Our approach to biogeographic analysis consists of two parts: first the sympatry inference and second the network analysis method (NAM). The sympatry inference method was designed to propose sympatry hypothesis, constructing a basal sympatry network based on punctual data, independent of a priori distributional area determination. In this way, two or more species are considered sympatric when there is interpenetration and relative proximity among their records of occurrence. In nature, groups of species presenting within-group sympatry and between-group allopatry constitute natural units (units of co-occurrence). These allopatric units are usually connected by intermediary species. The network analysis method (NAM) that we propose here is based on the identification and removal of intermediary species to segregate units of co-occurrence, using the betweenness measure and the clustering coefficient. The species ranges of the units of co-occurrence obtained are transferred to a map, being considered as candidates to areas of endemism. The new approach was implemented on three different real complex data sets (one of them a classic example previously used in biogeography) resulting in (1) independence of predefined spatial units; (2) definition of co-occurrence patterns from the sympatry network structure, not from species range similarities; (3) higher stability in results despite scale changes; (4) identification of candidates to areas of endemism supported by strictly endemic species; (5) identification of intermediary species with particular biological attributes. Copyright © Society of Systematic Biologists.Fil: Dos Santos, Daniel Andrés. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto de Biodiversidad Neotropical. Universidad Nacional de Tucumán. Facultad de Ciencias Naturales e Instituto Miguel Lillo. Instituto de Biodiversidad Neotropical. Instituto de Biodiversidad Neotropical; ArgentinaFil: Fernandez, Hugo Rafael. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto de Biodiversidad Neotropical. Universidad Nacional de Tucumán. Facultad de Ciencias Naturales e Instituto Miguel Lillo. Instituto de Biodiversidad Neotropical. Instituto de Biodiversidad Neotropical; ArgentinaFil: Cuezzo, Maria Gabriela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto de Biodiversidad Neotropical. Universidad Nacional de Tucumán. Facultad de Ciencias Naturales e Instituto Miguel Lillo. Instituto de Biodiversidad Neotropical. Instituto de Biodiversidad Neotropical; ArgentinaFil: Dominguez, Eduardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto de Biodiversidad Neotropical. Universidad Nacional de Tucumán. Facultad de Ciencias Naturales e Instituto Miguel Lillo. Instituto de Biodiversidad Neotropical. Instituto de Biodiversidad Neotropical; ArgentinaOxford University Press2008-06info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/141515Dos Santos, Daniel Andrés; Fernandez, Hugo Rafael; Cuezzo, Maria Gabriela; Dominguez, Eduardo; Sympatry inference and network analysis in biogeography; Oxford University Press; Systematic Biology; 57; 3; 6-2008; 432-4481063-5157CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1080/10635150802172192info:eu-repo/semantics/altIdentifier/url/https://academic.oup.com/sysbio/article/57/3/432/1664254info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-22T11:30:19Zoai:ri.conicet.gov.ar:11336/141515instacron: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:34982025-10-22 11:30:19.595CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Sympatry inference and network analysis in biogeography
title Sympatry inference and network analysis in biogeography
spellingShingle Sympatry inference and network analysis in biogeography
Dos Santos, Daniel Andrés
BETWEENNESS
CLUSTERING COEFFICIENT
DOT MAPS
HISTORICAL BIOGEOGRAPHY
INTERMEDIARY SPECIES
UNITS OF CO-OCCURRENCE
title_short Sympatry inference and network analysis in biogeography
title_full Sympatry inference and network analysis in biogeography
title_fullStr Sympatry inference and network analysis in biogeography
title_full_unstemmed Sympatry inference and network analysis in biogeography
title_sort Sympatry inference and network analysis in biogeography
dc.creator.none.fl_str_mv Dos Santos, Daniel Andrés
Fernandez, Hugo Rafael
Cuezzo, Maria Gabriela
Dominguez, Eduardo
author Dos Santos, Daniel Andrés
author_facet Dos Santos, Daniel Andrés
Fernandez, Hugo Rafael
Cuezzo, Maria Gabriela
Dominguez, Eduardo
author_role author
author2 Fernandez, Hugo Rafael
Cuezzo, Maria Gabriela
Dominguez, Eduardo
author2_role author
author
author
dc.subject.none.fl_str_mv BETWEENNESS
CLUSTERING COEFFICIENT
DOT MAPS
HISTORICAL BIOGEOGRAPHY
INTERMEDIARY SPECIES
UNITS OF CO-OCCURRENCE
topic BETWEENNESS
CLUSTERING COEFFICIENT
DOT MAPS
HISTORICAL BIOGEOGRAPHY
INTERMEDIARY SPECIES
UNITS OF CO-OCCURRENCE
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.6
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv A new approach for biogeography to find patterns of sympatry, based on network analysis, is proposed. Biogeographic analysis focuses basically on sympatry patterns of species. Sympatry is a network (= relational) datum, but it has never been analyzed before using relational tools such as Network Analysis. Our approach to biogeographic analysis consists of two parts: first the sympatry inference and second the network analysis method (NAM). The sympatry inference method was designed to propose sympatry hypothesis, constructing a basal sympatry network based on punctual data, independent of a priori distributional area determination. In this way, two or more species are considered sympatric when there is interpenetration and relative proximity among their records of occurrence. In nature, groups of species presenting within-group sympatry and between-group allopatry constitute natural units (units of co-occurrence). These allopatric units are usually connected by intermediary species. The network analysis method (NAM) that we propose here is based on the identification and removal of intermediary species to segregate units of co-occurrence, using the betweenness measure and the clustering coefficient. The species ranges of the units of co-occurrence obtained are transferred to a map, being considered as candidates to areas of endemism. The new approach was implemented on three different real complex data sets (one of them a classic example previously used in biogeography) resulting in (1) independence of predefined spatial units; (2) definition of co-occurrence patterns from the sympatry network structure, not from species range similarities; (3) higher stability in results despite scale changes; (4) identification of candidates to areas of endemism supported by strictly endemic species; (5) identification of intermediary species with particular biological attributes. Copyright © Society of Systematic Biologists.
Fil: Dos Santos, Daniel Andrés. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto de Biodiversidad Neotropical. Universidad Nacional de Tucumán. Facultad de Ciencias Naturales e Instituto Miguel Lillo. Instituto de Biodiversidad Neotropical. Instituto de Biodiversidad Neotropical; Argentina
Fil: Fernandez, Hugo Rafael. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto de Biodiversidad Neotropical. Universidad Nacional de Tucumán. Facultad de Ciencias Naturales e Instituto Miguel Lillo. Instituto de Biodiversidad Neotropical. Instituto de Biodiversidad Neotropical; Argentina
Fil: Cuezzo, Maria Gabriela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto de Biodiversidad Neotropical. Universidad Nacional de Tucumán. Facultad de Ciencias Naturales e Instituto Miguel Lillo. Instituto de Biodiversidad Neotropical. Instituto de Biodiversidad Neotropical; Argentina
Fil: Dominguez, Eduardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto de Biodiversidad Neotropical. Universidad Nacional de Tucumán. Facultad de Ciencias Naturales e Instituto Miguel Lillo. Instituto de Biodiversidad Neotropical. Instituto de Biodiversidad Neotropical; Argentina
description A new approach for biogeography to find patterns of sympatry, based on network analysis, is proposed. Biogeographic analysis focuses basically on sympatry patterns of species. Sympatry is a network (= relational) datum, but it has never been analyzed before using relational tools such as Network Analysis. Our approach to biogeographic analysis consists of two parts: first the sympatry inference and second the network analysis method (NAM). The sympatry inference method was designed to propose sympatry hypothesis, constructing a basal sympatry network based on punctual data, independent of a priori distributional area determination. In this way, two or more species are considered sympatric when there is interpenetration and relative proximity among their records of occurrence. In nature, groups of species presenting within-group sympatry and between-group allopatry constitute natural units (units of co-occurrence). These allopatric units are usually connected by intermediary species. The network analysis method (NAM) that we propose here is based on the identification and removal of intermediary species to segregate units of co-occurrence, using the betweenness measure and the clustering coefficient. The species ranges of the units of co-occurrence obtained are transferred to a map, being considered as candidates to areas of endemism. The new approach was implemented on three different real complex data sets (one of them a classic example previously used in biogeography) resulting in (1) independence of predefined spatial units; (2) definition of co-occurrence patterns from the sympatry network structure, not from species range similarities; (3) higher stability in results despite scale changes; (4) identification of candidates to areas of endemism supported by strictly endemic species; (5) identification of intermediary species with particular biological attributes. Copyright © Society of Systematic Biologists.
publishDate 2008
dc.date.none.fl_str_mv 2008-06
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/11336/141515
Dos Santos, Daniel Andrés; Fernandez, Hugo Rafael; Cuezzo, Maria Gabriela; Dominguez, Eduardo; Sympatry inference and network analysis in biogeography; Oxford University Press; Systematic Biology; 57; 3; 6-2008; 432-448
1063-5157
CONICET Digital
CONICET
url http://hdl.handle.net/11336/141515
identifier_str_mv Dos Santos, Daniel Andrés; Fernandez, Hugo Rafael; Cuezzo, Maria Gabriela; Dominguez, Eduardo; Sympatry inference and network analysis in biogeography; Oxford University Press; Systematic Biology; 57; 3; 6-2008; 432-448
1063-5157
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1080/10635150802172192
info:eu-repo/semantics/altIdentifier/url/https://academic.oup.com/sysbio/article/57/3/432/1664254
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
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Oxford University Press
publisher.none.fl_str_mv Oxford University Press
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 12.964596

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