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dc.contributor.authorNightingale, Glenna Faith
dc.contributor.authorIllian, Janine Baerbel
dc.contributor.authorKing, Ruth
dc.date.accessioned2015-10-01T23:12:55Z
dc.date.available2015-10-01T23:12:55Z
dc.date.issued2015-09
dc.identifier.citationNightingale , G F , Illian , J B & King , R 2015 , ' Pairwise interaction point processes for modelling bivariate spatial point patterns in the presence of interaction uncertainty ' , Journal of Environmental Statistics , vol. 7 , no. 3 .en
dc.identifier.issn1945-1296
dc.identifier.otherPURE: 220442010
dc.identifier.otherPURE UUID: c23fed04-3416-4c1d-8f66-b222e6808458
dc.identifier.urihttps://hdl.handle.net/10023/7583
dc.description.abstractCurrent ecological research seeks to understand the mechanisms that sustain biodiversity and allow a large number of species to coexist. Coexistence concerns inter-individual interactions. Consequently, there is an interest in identifying and quantifying interactions within and between species as reflected in the spatial pattern formed by the individuals. This study analyses the spatial pattern formed by the locations of plants in a community with high biodiversity from Western Australia. We fit a pairwise interaction Gibbs marked point process to the data using a Bayesian approach and quantify the inhibitory interactions within and between the two species. We quantitatively discriminate between competing models corresponding to different inter-specific and intraspecific interactions via posterior model probabilities. The analysis provides evidence that the intraspecific interactions for the two species of the genus Banksia are generally similar to those between the two species providing some evidence for mechanisms that sustain biodiversity.
dc.language.isoeng
dc.relation.ispartofJournal of Environmental Statisticsen
dc.rightsCopyright 2015 the Authors. This work is licensed under the following licenses: Paper: Creative Commons Attribution 3.0 Unported License (http://creativecommons.org/licenses/by/3.0/). Code: Commons GNU General Public License License (http://creativecommons.org/licenses/GPL/2.0/).en
dc.subjectGibbs point processesen
dc.subjectMultivariate spatial point patternsen
dc.subjectReversible jump Markov chain Monte Carloen
dc.subjectHA Statisticsen
dc.subject3rd-DASen
dc.subject.lccHAen
dc.titlePairwise interaction point processes for modelling bivariate spatial point patterns in the presence of interaction uncertaintyen
dc.typeJournal articleen
dc.description.versionPublisher PDFen
dc.contributor.institutionUniversity of St Andrews. Geography & Sustainable Developmenten
dc.contributor.institutionUniversity of St Andrews. School of Mathematics and Statisticsen
dc.contributor.institutionUniversity of St Andrews. Scottish Oceans Instituteen
dc.contributor.institutionUniversity of St Andrews. Centre for Research into Ecological & Environmental Modellingen
dc.description.statusPeer revieweden
dc.identifier.urlhttp://www.jenvstat.org/v07/i03en


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