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Hierarchical spatial point process analysis for a plant community with high biodiversity
Authors:Janine B. Illian  Jesper Møller  Rasmus P. Waagepetersen
Affiliation:(1) CREEM, School of Mathematics and Statistics, University of St Andrews, Buchanan Gardens, St Andrews, Fife, KY16 9LZ, Scotland, UK;(2) Department of Mathematical Sciences, Aalborg University, Fredrik Bajers Vej 7G, 9220 Aalborg, Denmark
Abstract:A complex multivariate spatial point pattern of a plant community with high biodiversity is modelled using a hierarchical multivariate point process model. In the model, interactions between plants with different post-fire regeneration strategies are of key interest. We consider initially a maximum likelihood approach to inference where problems arise due to unknown interaction radii for the plants. We next demonstrate that a Bayesian approach provides a flexible framework for incorporating prior information concerning the interaction radii. From an ecological perspective, we are able both to confirm existing knowledge on species’ interactions and to generate new biological questions and hypotheses on species’ interactions.
Contact Information Rasmus P. WaagepetersenEmail:
Keywords:Bayesian inference  Ecological plant communities  Maximum likelihood  Multivariate spatial point process  Spatial interaction
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