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dc.contributor.authorValencia Rodríguez, Daniel-
dc.contributor.authorJiménez Segura, Luz Fernanda-
dc.contributor.authorRogéliz Prada, Carlos Andrés-
dc.contributor.authorParra Vergara, Juan Luis-
dc.date.accessioned2022-09-20T14:27:11Z-
dc.date.available2022-09-20T14:27:11Z-
dc.date.issued2021-
dc.identifier.citationValencia-Rodrı´guez D, Jime´nez-Segura L, Roge´liz CA, Parra JL (2021) Ecological niche modeling as an effective tool to predict the distribution of freshwater organisms: The case of the Sabaleta Brycon henni (Eigenmann, 1913). PLoS ONE 16(3): e0247876. https://doi.org/10.1371/journal.pone.0247876spa
dc.identifier.issn1932-6203-
dc.identifier.urihttps://hdl.handle.net/10495/30714-
dc.description.abstractABSTRACT: Ecological niche models (ENMs) aim to recreate the relationships between species and the environments where they occur and allow us to identify unexplored areas in geography where these species might be present. These models have been successfully used in terrestrial organisms but their application in aquatic organisms is still scarce. Recent advances in the availability of species occurrences and environmental information particular to aquatic systems allow the evaluation of these models. This study aims to characterize the niche of the Sabaleta Brycon henni Eigenmann 1913, an endemic fish of the Colombian Andes, using ENMs to predict its geographical distribution across the Magdalena Basin. For this purpose, we used a set of environmental variables specific to freshwater systems in addition to the customary bioclimatic variables, and species’ occurrence data to model its potential distribution using the Maximum Entropy algorithm (MaxEnt). We evaluate the relative importance between these two sets of variables, the model’s performance, and its geographic overlap with the IUCN map. Both on-site (annual precipitation, minimum temperature of coldest month) and upstream variables (open waters, average minimum temperature of the coldest month and average precipitation seasonality) were included in the models with the highest predictive accuracy. With an area under the curve of 90%, 99% of the species occurrences and 68% of absences correctly predicted, our results support the good performance of ENMs to predict the potential distribution of the Sabaleta and the utility of this tool in conservation and decision-making at the national level.spa
dc.format.extent17spa
dc.format.mimetypeapplication/pdfspa
dc.language.isoengspa
dc.publisherPublic Library of Sciencespa
dc.type.hasversioninfo:eu-repo/semantics/publishedVersionspa
dc.rightsinfo:eu-repo/semantics/openAccessspa
dc.rights.urihttp://creativecommons.org/licenses/by/2.5/co/*
dc.titleEcological niche modeling as an effective tool to predict the distribution of freshwater organisms : The case of the Sabaleta Brycon henni (Eigenmann, 1913)spa
dc.typeinfo:eu-repo/semantics/articlespa
dc.publisher.groupEcología y Evolución de Vertebradosspa
dc.publisher.groupGrupo de Ictiologíaspa
dc.identifier.doi10.1371/journal.pone.0247876-
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85spa
dc.rights.accessrightshttp://purl.org/coar/access_right/c_abf2spa
oaire.citationtitlePLoS ONEspa
oaire.citationstartpage1spa
oaire.citationendpage17spa
oaire.citationvolume16spa
oaire.citationissue3spa
dc.rights.creativecommonshttps://creativecommons.org/licenses/by/4.0/spa
dc.publisher.placeSan Francisco, Estados Unidosspa
dc.type.coarhttp://purl.org/coar/resource_type/c_2df8fbb1spa
dc.type.redcolhttps://purl.org/redcol/resource_type/ARTspa
dc.type.localArtículo de investigaciónspa
dc.subject.decsEcosistema-
dc.subject.decsEcosystem-
dc.subject.lembAgua dulce-
dc.subject.lembFresh water-
dc.subject.lembPeces de agua dulce-
dc.subject.lembFreshwater fish-
dc.subject.lembRíos-
dc.subject.lembRivers-
dc.subject.lembCartografía-
dc.subject.lembCartography-
dc.subject.agrovocDistribución geográfica-
dc.subject.agrovocGeographical distribution-
dc.subject.agrovocurihttp://aims.fao.org/aos/agrovoc/c_5083-
dc.description.researchgroupidCOL0147267spa
dc.description.researchgroupidCOL0078704spa
dc.relation.ispartofjournalabbrevPLoS ONE.spa
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