DOI: 10.1101/470161Nov 19, 2018Paper

Untangling direct species associations from mediator species effects with graphical models

BioRxiv : the Preprint Server for Biology
Gordana PopovicAngela T Moles

Abstract

Ecologists often investigate co-occurrence patterns in multi-species data in order to gain insight into the ecological causes of observed co-occurrences. Apart from direct associations between two species, two species may co-occur because they both respond in similar ways to environmental variables, or due to the presence of other (mediator) species. A wide variety of methods are now available for modelling how environmental filtering drives species distributions. In contrast, methods for studying other causes of co-occurence are much more limited. 'Graphical' methods, which can be used to study how mediator species impact co-occurrence patterns, have recently been proposed for use in ecology. However, available methods are limited to presence/absence data and methods assuming multivariate normality, which is problematic when analysing abundances. We propose Gaussian copula graphical models (GCGMs) for studying the effect of mediator species on co-occurence patterns. GCGMs are a flexible type of graphical model which naturally accommodates all data types -- binary (presence/absence), counts, as well as ordinal data and biomass, in a unified framework. Simulations for count data demonstrate that GCGMs are better able to distingu...Continue Reading

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Environment
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