Tree‐based inference of species interaction networks from abundance data. Issue 5 (15th March 2020)

• Record Type: Journal Article
• Authors: Momal, Raphaëlle; Robin, Stéphane; Ambroise, Christophe
• Editors: Warton, David
• Is Part Of: Methods in ecology and evolution. Volume 11:Issue 5(2020)
• Page Start: 621
• Page End: 632
• Publication Date: 2020-03-15
• Subjects: abundance data -- covariates adjustment -- EM algorithm -- graphical models -- matrix tree theorem -- Poisson log‐normal model -- species interaction network; Ecology -- Periodicals; Evolution -- Periodicals; 577
• DOI: 10.1111/2041-210X.13380
• Languages: English
• ISSNs: 2041-210X

Abstract

Abstract: The behaviour of ecological systems mainly relies on the interactions between the species it involves. We consider the problem of inferring the species interaction network from abundance data. To be relevant, any network inference methodology needs to handle count data and to account for possible environmental effects. It also needs to distinguish between direct interactions and indirect associations and graphical models provide a convenient framework for this purpose. A simulation study shows that the proposed methodology compares well with state‐of‐the‐art approaches, even when the underlying graph strongly differs from a tree. The analysis of two datasets highlights the influence of covariates on the inferred network. Accounting for covariates is critical to avoid spurious edges. The proposed approach could be extended to perform network comparison or to look for missing species.