Species traits and network structure predict the success and impacts of pollinator invasions
Author
dc.contributor.author
Valdovinos, Fernanda S.
Author
dc.contributor.author
Berlow, Eric L.
Author
dc.contributor.author
Moisset de Espanes, Pablo
Author
dc.contributor.author
Ramos-Jiliberto, Rodrigo
Author
dc.contributor.author
Vázquez, Diego P.
Author
dc.contributor.author
Martínez, Neo D.
Admission date
dc.date.accessioned
2018-09-25T18:59:30Z
Available date
dc.date.available
2018-09-25T18:59:30Z
Publication date
dc.date.issued
2018-05-31
Cita de ítem
dc.identifier.citation
Nature communications Volumen: 9 Número de artículo: 2153
es_ES
Identifier
dc.identifier.other
10.1038/s41467-018-04593-y
Identifier
dc.identifier.uri
https://repositorio.uchile.cl/handle/2250/151734
Abstract
dc.description.abstract
Species 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_ES
Patrocinador
dc.description.sponsorship
University of Michigan
US NSF
ICER-131383
DEB-1241253
US DOE
DE-SC0016247
FONDECYT
1120958