The Saturated Pairwise Interaction Gibbs Point Process as a Joint Species Distribution Model. Issue 5 (19th September 2022)

• Record Type: Journal Article
• Authors: Flint, Ian; Golding, Nick; Vesk, Peter; Wang, Yan; Xia, Aihua
• Is Part Of: Journal of the Royal Statistical Society. Volume 71:Issue 5(2022)
• Page Start: 1721
• Page End: 1752
• Publication Date: 2022-09-19
• Subjects: Barro Colorado Island -- Gibbs processes -- joint species distribution models -- pairwise interactions -- spatial point processes; Statistics -- Periodicals; 519.5
• DOI: 10.1111/rssc.12596
• Languages: English
• ISSNs: 0035-9254

Abstract

Abstract: In an effort to effectively model observed patterns in the spatial configuration of individuals of multiple species in nature, we introduce the saturated pairwise interaction Gibbs point process. Its main strength lies in its ability to model both attraction and repulsion within and between species, over different scales. As such, it is particularly well-suited to the study of associations in complex ecosystems. Based on the existing literature, we provide an easy to implement fitting procedure as well as a technique to make inference for the model parameters. We also prove that under certain hypotheses the point process is locally stable, which allows us to use the well-known 'coupling from the past' algorithm to draw samples from the model. Different numerical experiments show the robustness of the model. We study three different ecological data sets, demonstrating in each one that our model helps disentangle competing ecological effects on species' distribution.