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dc.contributor.authorRamos-Jiliberto, Rodrigo [Univ Mayor, Ctr Genom Ecol & Environm GEMA]es_CL
dc.contributor.authorValdovinos, Fernanda S.es_CL
dc.contributor.authorBerlow, Eric L.es_CL
dc.contributor.authorMoisset de Espanes, Pabloes_CL
dc.contributor.authorVázquez, Diego P.es_CL
dc.contributor.authorMartínez, Neo D.es_CL
dc.date.accessioned2020-04-08T14:11:55Z
dc.date.accessioned2020-04-13T18:12:36Z
dc.date.available2020-04-08T14:11:55Z
dc.date.available2020-04-13T18:12:36Z
dc.date.issued2018es_CL
dc.identifier.citationValdovinos, F. S., Berlow, E. L., De Espanés, P. M., Ramos-Jiliberto, R., Vázquez, D. P., & Martinez, N. D. (2018). Species traits and network structure predict the success and impacts of pollinator invasions. Nature communications, 9(1), 1-8.es_CL
dc.identifier.issn2041-1723es_CL
dc.identifier.urihttps://doi.org/10.1038/s41467-018-04593-yes_CL
dc.identifier.urihttp://repositorio.umayor.cl/xmlui/handle/sibum/6114
dc.identifier.urihttps://www.nature.com/articles/s41467-018-04593-y
dc.description.abstractSpecies invasions constitute a major and poorly understood threat to plant-pollinator systems. General theory predicting which factors drive species invasion success and subsequent effects on native ecosystems is particularly lacking. We address this problem using a consumer-resource model of adaptive behavior and population dynamics to evaluate the invasion success of alien pollinators into plant-pollinator networks and their impact on native species. We introduce pollinator species with different foraging traits into network models with different levels of species richness, connectance, and nestedness. Among 31 factors tested, including network and alien properties, we find that aliens with high foraging efficiency are the most successful invaders. Networks exhibiting high alien-native diet overlap, fraction of alien-visited plant species, most-generalist plant connectivity, and number of specialist pollinator species are the most impacted by invaders. Our results mimic several disparate observations conducted in the field and potentially elucidate the mechanisms responsible for their variability.es_CL
dc.description.sponsorshipUniversity of MichiganUniversity of Michigan System; US NSFNational Science Foundation (NSF) [ICER-131383, DEB-1241253]; US DOEUnited States Department of Energy (DOE) [DE-SC0016247]; FONDECYTComision Nacional de Investigacion Cientifica y Tecnologica (CONICYT)CONICYT FONDECYT [1120958]es_CL
dc.description.sponsorshipThis work was supported by the University of Michigan (to F.S.V.); the US NSF (ICER-131383 and DEB-1241253 (to N.D.M.), US DOE DE-SC0016247 (to NDM), and FONDECYT 1120958 (to P.M.d.E. and R.R. J.).es_CL
dc.language.isoenes_CL
dc.publisherNATURE PUBLISHING GROUPes_CL
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Chile
dc.sourceNat. Commun., MAY 2018. 9
dc.subjectMultidisciplinary Scienceses_CL
dc.titleSpecies traits and network structure predict the success and impacts of pollinator invasionses_CL
dc.typeArtículoes_CL
umayor.facultadCIENCIASes_CL
umayor.politicas.sherpa/romeoDOAJ Gold, Green Publishedes_CL
umayor.indexadoWOS:000433552200001es_CL
umayor.indexadoPMID: 29855466es_CL
dc.identifier.doiDOI: 10.1038/s41467-018-04593-yes_CL]
umayor.indicadores.wos-(cuartil)Q1es_CL
umayor.indicadores.scopus-(scimago-sjr)SCIMAGO/ INDICE H: 248 Hes_CL


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