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dc.contributor.authorChokechaipaisarn, Chedhawat
dc.contributor.authorGardner, Andy
dc.date.accessioned2023-07-17T14:30:07Z
dc.date.available2023-07-17T14:30:07Z
dc.date.issued2023-07-11
dc.identifier290278921
dc.identifier7a367413-56d7-4d2d-8aa7-e1c460036af2
dc.identifier.citationChokechaipaisarn , C & Gardner , A 2023 , ' A simulation test of the prediction that density-dependent dispersal promotes female-biased sex allocation in viscous populations ' , microPublication Biology . https://doi.org/10.17912/micropub.biology.000821en
dc.identifier.issn2578-9430
dc.identifier.urihttps://hdl.handle.net/10023/27973
dc.descriptionFunding: This work was supported by the Queen Sirikit Scholarship and the European Research Council (grant no. 771387).en
dc.description.abstractA classic result of sex-allocation theory is that the sex ratio is predicted to be invariant with respect to the rate of dispersal. However, a recent mathematical analysis has suggested that if individuals are able to adjust their probability of dispersal according to the local density of their neighbourhood, then a lower rate of dispersal will be associated with greater female-bias. Here, we perform a computer simulation test of this prediction. Our simulation data provide strong qualitative support for the prediction, and a Monte Carlo randomization test of significance allows us to reject the null hypothesis of the invariance relationship.
dc.format.extent4
dc.format.extent619927
dc.language.isoeng
dc.relation.ispartofmicroPublication Biologyen
dc.subjectQH301 Biologyen
dc.subjectDASen
dc.subject.lccQH301en
dc.titleA simulation test of the prediction that density-dependent dispersal promotes female-biased sex allocation in viscous populationsen
dc.typeJournal articleen
dc.contributor.sponsorEuropean Research Councilen
dc.contributor.institutionUniversity of St Andrews. School of Biologyen
dc.contributor.institutionUniversity of St Andrews. Centre for Biological Diversityen
dc.contributor.institutionUniversity of St Andrews. Institute of Behavioural and Neural Sciencesen
dc.contributor.institutionUniversity of St Andrews. St Andrews Bioinformatics Uniten
dc.identifier.doi10.17912/micropub.biology.000821
dc.description.statusPeer revieweden
dc.identifier.grantnumber771387en


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