Consensus in the search for areas of endemism

Autores
Aagesen, Lone; Szumik, Claudia Adriana; Goloboff, Pablo Augusto
Año de publicación
2013
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
For ambiguous data sets, methods to determine areas of endemism based on an optimality criterion may result in large numbers of candidate areas, and thus some kind of consensus technique is required to summarize those results. This paper presents a formal description of two possible algorithms or rules for area consensus, which merge candidate areas if they share a user-defined percentage of the species that define each candidate area. The two consensus rules summarize ambiguity in different ways. Applying the ?tight? rule will result in consensus areas defined by species present in nearly all cells, but in cases where there is significant conflict the result may be a high number of distinct consensus areas. The ?loose? consensus rule is more agglomerative and will result in fewer consensus areas, combining areas when overlapping distribution patterns exist. Depending on the aim and scale of the analysis, the two consensus rules can be used either to delimit areas of endemism with sharp boundaries or to identify diffuse and gradually replacing biogeographical patterns. These two different approaches are discussed and demonstrated using real data.
Fil: Aagesen, Lone. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Botánica Darwinion; Argentina
Fil: Szumik, Claudia Adriana. Universidad Nacional de Tucumán. Facultad de Ciencias Naturales e Instituto Miguel Lillo. Instituto Superior de Entomología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Tucumán; Argentina
Fil: Goloboff, Pablo Augusto. Universidad Nacional de Tucumán. Facultad de Ciencias Naturales e Instituto Miguel Lillo. Instituto Superior de Entomología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Tucumán; Argentina
Materia
Areas of Endemism
Biogeography
Conflicting Species Distributions
Consensus Algorithms
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:11336/7327
Acceder
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spelling Consensus in the search for areas of endemismAagesen, LoneSzumik, Claudia AdrianaGoloboff, Pablo AugustoAreas of EndemismBiogeographyConflicting Species DistributionsConsensus Algorithmshttps://purl.org/becyt/ford/1.6https://purl.org/becyt/ford/1For ambiguous data sets, methods to determine areas of endemism based on an optimality criterion may result in large numbers of candidate areas, and thus some kind of consensus technique is required to summarize those results. This paper presents a formal description of two possible algorithms or rules for area consensus, which merge candidate areas if they share a user-defined percentage of the species that define each candidate area. The two consensus rules summarize ambiguity in different ways. Applying the ?tight? rule will result in consensus areas defined by species present in nearly all cells, but in cases where there is significant conflict the result may be a high number of distinct consensus areas. The ?loose? consensus rule is more agglomerative and will result in fewer consensus areas, combining areas when overlapping distribution patterns exist. Depending on the aim and scale of the analysis, the two consensus rules can be used either to delimit areas of endemism with sharp boundaries or to identify diffuse and gradually replacing biogeographical patterns. These two different approaches are discussed and demonstrated using real data.Fil: Aagesen, Lone. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Botánica Darwinion; ArgentinaFil: Szumik, Claudia Adriana. Universidad Nacional de Tucumán. Facultad de Ciencias Naturales e Instituto Miguel Lillo. Instituto Superior de Entomología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Tucumán; ArgentinaFil: Goloboff, Pablo Augusto. Universidad Nacional de Tucumán. Facultad de Ciencias Naturales e Instituto Miguel Lillo. Instituto Superior de Entomología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Tucumán; ArgentinaWiley2013-11info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/7327Aagesen, Lone; Szumik, Claudia Adriana; Goloboff, Pablo Augusto; Consensus in the search for areas of endemism; Wiley; Journal Of Biogeography; 40; 11; 11-2013; 2011-20160305-0270enginfo:eu-repo/semantics/altIdentifier/doi/10.1111/jbi.12172/abstractinfo:eu-repo/semantics/altIdentifier/url/http://onlinelibrary.wiley.com/doi/10.1111/jbi.12172/abstractinfo:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T09:51:04Zoai:ri.conicet.gov.ar:11336/7327instacron: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:34982025-09-03 09:51:05.25CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Consensus in the search for areas of endemism
title Consensus in the search for areas of endemism
spellingShingle Consensus in the search for areas of endemism
Aagesen, Lone
Areas of Endemism
Biogeography
Conflicting Species Distributions
Consensus Algorithms
title_short Consensus in the search for areas of endemism
title_full Consensus in the search for areas of endemism
title_fullStr Consensus in the search for areas of endemism
title_full_unstemmed Consensus in the search for areas of endemism
title_sort Consensus in the search for areas of endemism
dc.creator.none.fl_str_mv Aagesen, Lone
Szumik, Claudia Adriana
Goloboff, Pablo Augusto
author Aagesen, Lone
author_facet Aagesen, Lone
Szumik, Claudia Adriana
Goloboff, Pablo Augusto
author_role author
author2 Szumik, Claudia Adriana
Goloboff, Pablo Augusto
author2_role author
author
dc.subject.none.fl_str_mv Areas of Endemism
Biogeography
Conflicting Species Distributions
Consensus Algorithms
topic Areas of Endemism
Biogeography
Conflicting Species Distributions
Consensus Algorithms
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.6
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv For ambiguous data sets, methods to determine areas of endemism based on an optimality criterion may result in large numbers of candidate areas, and thus some kind of consensus technique is required to summarize those results. This paper presents a formal description of two possible algorithms or rules for area consensus, which merge candidate areas if they share a user-defined percentage of the species that define each candidate area. The two consensus rules summarize ambiguity in different ways. Applying the ?tight? rule will result in consensus areas defined by species present in nearly all cells, but in cases where there is significant conflict the result may be a high number of distinct consensus areas. The ?loose? consensus rule is more agglomerative and will result in fewer consensus areas, combining areas when overlapping distribution patterns exist. Depending on the aim and scale of the analysis, the two consensus rules can be used either to delimit areas of endemism with sharp boundaries or to identify diffuse and gradually replacing biogeographical patterns. These two different approaches are discussed and demonstrated using real data.
Fil: Aagesen, Lone. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Botánica Darwinion; Argentina
Fil: Szumik, Claudia Adriana. Universidad Nacional de Tucumán. Facultad de Ciencias Naturales e Instituto Miguel Lillo. Instituto Superior de Entomología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Tucumán; Argentina
Fil: Goloboff, Pablo Augusto. Universidad Nacional de Tucumán. Facultad de Ciencias Naturales e Instituto Miguel Lillo. Instituto Superior de Entomología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Tucumán; Argentina
description For ambiguous data sets, methods to determine areas of endemism based on an optimality criterion may result in large numbers of candidate areas, and thus some kind of consensus technique is required to summarize those results. This paper presents a formal description of two possible algorithms or rules for area consensus, which merge candidate areas if they share a user-defined percentage of the species that define each candidate area. The two consensus rules summarize ambiguity in different ways. Applying the ?tight? rule will result in consensus areas defined by species present in nearly all cells, but in cases where there is significant conflict the result may be a high number of distinct consensus areas. The ?loose? consensus rule is more agglomerative and will result in fewer consensus areas, combining areas when overlapping distribution patterns exist. Depending on the aim and scale of the analysis, the two consensus rules can be used either to delimit areas of endemism with sharp boundaries or to identify diffuse and gradually replacing biogeographical patterns. These two different approaches are discussed and demonstrated using real data.
publishDate 2013
dc.date.none.fl_str_mv 2013-11
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/11336/7327
Aagesen, Lone; Szumik, Claudia Adriana; Goloboff, Pablo Augusto; Consensus in the search for areas of endemism; Wiley; Journal Of Biogeography; 40; 11; 11-2013; 2011-2016
0305-0270
url http://hdl.handle.net/11336/7327
identifier_str_mv Aagesen, Lone; Szumik, Claudia Adriana; Goloboff, Pablo Augusto; Consensus in the search for areas of endemism; Wiley; Journal Of Biogeography; 40; 11; 11-2013; 2011-2016
0305-0270
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1111/jbi.12172/abstract
info:eu-repo/semantics/altIdentifier/url/http://onlinelibrary.wiley.com/doi/10.1111/jbi.12172/abstract
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
dc.publisher.none.fl_str_mv Wiley
publisher.none.fl_str_mv Wiley
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 13.13397

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