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dc.contributor.authorSimmons, Benno
dc.contributor.authorCirtwill, Alyssa R
dc.contributor.authorBaker, Nick J
dc.contributor.authorWauchope, Hannah
dc.contributor.authorDicks, Lynn
dc.contributor.authorStouffer, Daniel B
dc.contributor.authorSutherland, William
dc.date.accessioned2019-01-30T10:32:38Z
dc.date.available2019-01-30T10:32:38Z
dc.date.issued2019-01
dc.identifier.issn1600-0706
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/288548
dc.description.abstractIndirect interactions play an essential role in governing population, community and coevolutionary dynamics across a diverse range of ecological communities. Such communities are widely represented as bipartite networks: graphs depicting interactions between two groups of species, such as plants and pollinators or hosts and parasites. For over thirty years, studies have used indices, such as connectance and species degree, to characterise the structure of these networks and the roles of their constituent species. However, compressing a complex network into a single metric necessarily discards large amounts of information about indirect interactions. Given the large literature demonstrating the importance and ubiquity of indirect effects, many studies of network structure are likely missing a substantial piece of the ecological puzzle. Here we use the emerging concept of bipartite motifs to outline a new framework for bipartite networks that incorporates indirect interactions. While this framework is a significant departure from the current way of thinking about bipartite ecological networks, we show that this shift is supported by analyses of simulated and empirical data. We use simulations to show how consideration of indirect interactions can highlight differences missed by the current index paradigm that may be ecologically important. We extend this finding to empirical plant-pollinator communities, showing how two bee species, with similar direct interactions, differ in how specialised their competitors are. These examples underscore the need to not rely solely on network- and species-level indices for characterising the structure of bipartite ecological networks.
dc.publisherWiley-Blackwell
dc.subjectindirect interactions
dc.subjectecological networks
dc.subjectmutualistic networks
dc.subjectfood webs
dc.subjectparasitism
dc.subjectseed dispersal
dc.subjectpollination
dc.subjectherbivory
dc.subjectmotifs
dc.titleMotifs in bipartite ecological networks: uncovering indirect interactions
dc.typeArticle
prism.publicationNameOikos
dc.identifier.doi10.17863/CAM.35833
dcterms.dateAccepted2018-08-25
rioxxterms.versionofrecord10.1111/oik.05670
rioxxterms.versionVoR
rioxxterms.licenseref.urihttp://www.rioxx.net/licenses/all-rights-reserved
rioxxterms.licenseref.startdate2018-08-25
dc.contributor.orcidSimmons, Benno [0000-0002-2751-9430]
dc.contributor.orcidWauchope, Hannah [0000-0001-5370-4616]
dc.contributor.orcidDicks, Lynn [0000-0002-8304-4468]
dc.contributor.orcidSutherland, William [0000-0002-6498-0437]
dc.identifier.eissn1600-0706
dc.publisher.urlhttps://onlinelibrary.wiley.com/doi/full/10.1111/oik.05670
rioxxterms.typeJournal Article/Review
pubs.funder-project-idNERC (1653183)
pubs.funder-project-idNERC (1653183)
pubs.funder-project-idNERC (NE/N014472/2)
cam.issuedOnline2018-09-06
dc.identifier.urlhttps://onlinelibrary.wiley.com/doi/full/10.1111/oik.05670
rioxxterms.freetoread.startdate2019-09-06


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