Power laws in species’ biotic interaction networks can be inferred from co-occurrence data

Autores
Galiana, Nuria; Arnoldi, Jean François; Mestre, Frederico; Rozenfeld, Alejandro Fabian; Araújo, Miguel B.
Año de publicación
2023
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Inferring biotic interactions from species co-occurrence patterns has long intrigued ecologists. Yet recent research revealed that co-occurrences may not reliably represent pairwise biotic interactions. We propose that examining network-level co-occurrence patterns can provide valuable insights into community structure and assembly. Analysing ten bipartite networks of empirically sampled biotic interactions and associated species spatial distribution, we find that approximately 20% of co-occurrences correspond to actual interactions. Moreover, the degree distribution shifts from exponential in co-occurrence networks to power laws in networks of biotic interactions. This shift results from a strong interplay between species’ biotic (their interacting partners) and abiotic (their environmental requirements) niches, and is accurately predicted by considering co-occurrence frequencies. Our work offers a mechanistic understanding of the assembly of ecological communities and suggests simple ways to infer fundamental biotic interaction network characteristics from co-occurrence data.
Fil: Galiana, Nuria. National Museum of Natural Sciences; España
Fil: Arnoldi, Jean François. No especifíca;
Fil: Mestre, Frederico. University of Évora; Portugal
Fil: Rozenfeld, Alejandro Fabian. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Centro de Investigaciones en Física e Ingeniería del Centro de la Provincia de Buenos Aires. Sede Olavarría del Centro de Investigaciones en Física e Ingeniería del Centro de la Provincia de Buenos Aires | Universidad Nacional del Centro de la Pcia. de Bs.as. Centro de Investigaciones en Física e Ingeniería del Centro de la Provincia de Buenos Aires. Sede Olavarría del Centro de Investigaciones en Física e Ingeniería del Centro de la Provincia de Buenos Aires; Argentina
Fil: Araújo, Miguel B.. University of Évora; Portugal
Materia
COMPLEX SYSTEMS
NETWORKS
INTERACTIONS
CO-OCURRENCE
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/251748
Acceder
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spelling Power laws in species’ biotic interaction networks can be inferred from co-occurrence dataGaliana, NuriaArnoldi, Jean FrançoisMestre, FredericoRozenfeld, Alejandro FabianAraújo, Miguel B.COMPLEX SYSTEMSNETWORKSINTERACTIONSCO-OCURRENCEhttps://purl.org/becyt/ford/1.2https://purl.org/becyt/ford/1https://purl.org/becyt/ford/1.6https://purl.org/becyt/ford/1Inferring biotic interactions from species co-occurrence patterns has long intrigued ecologists. Yet recent research revealed that co-occurrences may not reliably represent pairwise biotic interactions. We propose that examining network-level co-occurrence patterns can provide valuable insights into community structure and assembly. Analysing ten bipartite networks of empirically sampled biotic interactions and associated species spatial distribution, we find that approximately 20% of co-occurrences correspond to actual interactions. Moreover, the degree distribution shifts from exponential in co-occurrence networks to power laws in networks of biotic interactions. This shift results from a strong interplay between species’ biotic (their interacting partners) and abiotic (their environmental requirements) niches, and is accurately predicted by considering co-occurrence frequencies. Our work offers a mechanistic understanding of the assembly of ecological communities and suggests simple ways to infer fundamental biotic interaction network characteristics from co-occurrence data.Fil: Galiana, Nuria. National Museum of Natural Sciences; EspañaFil: Arnoldi, Jean François. No especifíca;Fil: Mestre, Frederico. University of Évora; PortugalFil: Rozenfeld, Alejandro Fabian. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Centro de Investigaciones en Física e Ingeniería del Centro de la Provincia de Buenos Aires. Sede Olavarría del Centro de Investigaciones en Física e Ingeniería del Centro de la Provincia de Buenos Aires | Universidad Nacional del Centro de la Pcia. de Bs.as. Centro de Investigaciones en Física e Ingeniería del Centro de la Provincia de Buenos Aires. Sede Olavarría del Centro de Investigaciones en Física e Ingeniería del Centro de la Provincia de Buenos Aires; ArgentinaFil: Araújo, Miguel B.. University of Évora; PortugalNature2023-11info: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/11336/251748Galiana, Nuria; Arnoldi, Jean François; Mestre, Frederico; Rozenfeld, Alejandro Fabian; Araújo, Miguel B.; Power laws in species’ biotic interaction networks can be inferred from co-occurrence data; Nature; Nature Ecology & Evolution; 8; 2; 11-2023; 209-2172397-334XCONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1038/s41559-023-02254-yinfo:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T09:49:25Zoai:ri.conicet.gov.ar:11336/251748instacron: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 09:49:25.875CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Power laws in species’ biotic interaction networks can be inferred from co-occurrence data
title Power laws in species’ biotic interaction networks can be inferred from co-occurrence data
spellingShingle Power laws in species’ biotic interaction networks can be inferred from co-occurrence data
Galiana, Nuria
COMPLEX SYSTEMS
NETWORKS
INTERACTIONS
CO-OCURRENCE
title_short Power laws in species’ biotic interaction networks can be inferred from co-occurrence data
title_full Power laws in species’ biotic interaction networks can be inferred from co-occurrence data
title_fullStr Power laws in species’ biotic interaction networks can be inferred from co-occurrence data
title_full_unstemmed Power laws in species’ biotic interaction networks can be inferred from co-occurrence data
title_sort Power laws in species’ biotic interaction networks can be inferred from co-occurrence data
dc.creator.none.fl_str_mv Galiana, Nuria
Arnoldi, Jean François
Mestre, Frederico
Rozenfeld, Alejandro Fabian
Araújo, Miguel B.
author Galiana, Nuria
author_facet Galiana, Nuria
Arnoldi, Jean François
Mestre, Frederico
Rozenfeld, Alejandro Fabian
Araújo, Miguel B.
author_role author
author2 Arnoldi, Jean François
Mestre, Frederico
Rozenfeld, Alejandro Fabian
Araújo, Miguel B.
author2_role author
author
author
author
dc.subject.none.fl_str_mv COMPLEX SYSTEMS
NETWORKS
INTERACTIONS
CO-OCURRENCE
topic COMPLEX SYSTEMS
NETWORKS
INTERACTIONS
CO-OCURRENCE
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.2
https://purl.org/becyt/ford/1
https://purl.org/becyt/ford/1.6
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Inferring biotic interactions from species co-occurrence patterns has long intrigued ecologists. Yet recent research revealed that co-occurrences may not reliably represent pairwise biotic interactions. We propose that examining network-level co-occurrence patterns can provide valuable insights into community structure and assembly. Analysing ten bipartite networks of empirically sampled biotic interactions and associated species spatial distribution, we find that approximately 20% of co-occurrences correspond to actual interactions. Moreover, the degree distribution shifts from exponential in co-occurrence networks to power laws in networks of biotic interactions. This shift results from a strong interplay between species’ biotic (their interacting partners) and abiotic (their environmental requirements) niches, and is accurately predicted by considering co-occurrence frequencies. Our work offers a mechanistic understanding of the assembly of ecological communities and suggests simple ways to infer fundamental biotic interaction network characteristics from co-occurrence data.
Fil: Galiana, Nuria. National Museum of Natural Sciences; España
Fil: Arnoldi, Jean François. No especifíca;
Fil: Mestre, Frederico. University of Évora; Portugal
Fil: Rozenfeld, Alejandro Fabian. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Centro de Investigaciones en Física e Ingeniería del Centro de la Provincia de Buenos Aires. Sede Olavarría del Centro de Investigaciones en Física e Ingeniería del Centro de la Provincia de Buenos Aires | Universidad Nacional del Centro de la Pcia. de Bs.as. Centro de Investigaciones en Física e Ingeniería del Centro de la Provincia de Buenos Aires. Sede Olavarría del Centro de Investigaciones en Física e Ingeniería del Centro de la Provincia de Buenos Aires; Argentina
Fil: Araújo, Miguel B.. University of Évora; Portugal
description Inferring biotic interactions from species co-occurrence patterns has long intrigued ecologists. Yet recent research revealed that co-occurrences may not reliably represent pairwise biotic interactions. We propose that examining network-level co-occurrence patterns can provide valuable insights into community structure and assembly. Analysing ten bipartite networks of empirically sampled biotic interactions and associated species spatial distribution, we find that approximately 20% of co-occurrences correspond to actual interactions. Moreover, the degree distribution shifts from exponential in co-occurrence networks to power laws in networks of biotic interactions. This shift results from a strong interplay between species’ biotic (their interacting partners) and abiotic (their environmental requirements) niches, and is accurately predicted by considering co-occurrence frequencies. Our work offers a mechanistic understanding of the assembly of ecological communities and suggests simple ways to infer fundamental biotic interaction network characteristics from co-occurrence data.
publishDate 2023
dc.date.none.fl_str_mv 2023-11
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/11336/251748
Galiana, Nuria; Arnoldi, Jean François; Mestre, Frederico; Rozenfeld, Alejandro Fabian; Araújo, Miguel B.; Power laws in species’ biotic interaction networks can be inferred from co-occurrence data; Nature; Nature Ecology & Evolution; 8; 2; 11-2023; 209-217
2397-334X
CONICET Digital
CONICET
url http://hdl.handle.net/11336/251748
identifier_str_mv Galiana, Nuria; Arnoldi, Jean François; Mestre, Frederico; Rozenfeld, Alejandro Fabian; Araújo, Miguel B.; Power laws in species’ biotic interaction networks can be inferred from co-occurrence data; Nature; Nature Ecology & Evolution; 8; 2; 11-2023; 209-217
2397-334X
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1038/s41559-023-02254-y
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Nature
publisher.none.fl_str_mv Nature
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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