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Pairwise interaction point processes for modelling bivariate spatial point patterns in the presence of interaction uncertainty

Research output: Contribution to journalArticle


Current 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.


Original languageEnglish
JournalJournal of Environmental Statistics
Issue number3
StatePublished - Sep 2015

    Research areas

  • Gibbs point processes, Multivariate spatial point patterns, Reversible jump Markov chain Monte Carlo

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