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

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Date
09/2015
Author
Nightingale, Glenna Faith
Illian, Janine Baerbel
King, Ruth
Keywords
Gibbs point processes
Multivariate spatial point patterns
Reversible jump Markov chain Monte Carlo
HA Statistics
3rd-DAS
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Abstract
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.
Citation
Nightingale , 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 .
Publication
Journal of Environmental Statistics
Status
Peer reviewed
ISSN
1945-1296
Type
Journal article
Rights
Copyright 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/).
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  • University of St Andrews Research
URL
http://www.jenvstat.org/v07/i03
URI
http://hdl.handle.net/10023/7583

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