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dc.contributor.authorCropp, Roger
dc.contributor.authorNorbury, John
dc.date.accessioned2019-06-25T23:41:55Z
dc.date.available2019-06-25T23:41:55Z
dc.date.issued2019
dc.identifier.issn0092-8240
dc.identifier.doi10.1007/s11538-018-0508-1
dc.identifier.urihttp://hdl.handle.net/10072/385727
dc.description.abstractPollination interactions are common, and their maintenance is critical for many food crops upon which human populations depend. Pollination is a mutualism interaction; together with predation and competition, mutualism makes up the triumvirate of fundamental interactions that control population dynamics. Here we examine pollination interactions (nectar reward for gamete transport service) using a simple heuristic model similar to the Lotka–Volterra models that have underpinned our understanding of predation and competition so effectively since the 1920s. We use a genetic algorithm to simulate the eco-evolutionary interactions of the plant and pollinator populations and examine the distributions of the parameter values and zero isoclines to infer the relative ubiquity of the various eco-evolutionary outcomes possible in the model. Our results suggest that trade-offs between costs and benefits for the pollinator may be a key component of obligate pollination systems in achieving adaptive success creating and stably occupying mutualist niches.
dc.description.peerreviewedYes
dc.languageEnglish
dc.language.isoeng
dc.publisherSpringer
dc.relation.ispartofjournalBulletin of Mathematical Biology
dc.subject.fieldofresearchMathematical Sciences
dc.subject.fieldofresearchBiological Sciences
dc.subject.fieldofresearchcode01
dc.subject.fieldofresearchcode06
dc.titleSimulating Eco-evolutionary Processes in an Obligate Pollination Model with a Genetic Algorithm
dc.typeJournal article
dc.type.descriptionC1 - Articles
dc.type.codeC - Journal Articles
dc.description.versionAccepted Manuscript (AM)
gro.description.notepublicThis publication has been entered into Griffith Research Online as an Advanced Online Version.
gro.rights.copyright© 2018 Springer. This is an electronic version of an article published in Bulletin of Mathematical Biology, AOV. Bulletin of Mathematical Biology is available online at: http://link.springer.com/ with the open URL of your article.
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gro.griffith.authorCropp, Roger A.


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