Can Ecological Interactions be Inferred from Spatial Data? - Stephens, Christopher Rhodes; Gonzalez-Salazar, Constantino; Villalobos, Maricarmen; Marquet, Pablo (Biodiversity Informatics, 2020)
The characterisation and quantication of ecological interactions, and the constructionof species distributions and their associated ecological niches, is of fundamentaltheoretical and practical importance. In this paper we give an overview of a Bayesianinference framework, developed over the last 10 years, which, using spatial data, offersa general formalism within which ecological interactions may be characterised andquantied. Interactions are identied through deviations of the spatial distributionof co-occurrences of spatial variables relative to a benchmark for the non-interactingsystem, and based on a statistical ensemble of spatial cells. The formalism allows forthe integration of both biotic and abiotic factors of arbitrary resolution. We concentrateon the conceptual and mathematical underpinnings of the formalism, showinghow, using the Naive Bayes approximation, it can be used to not only compare andcontrast the relative contribution from each variable, but also to construct speciesdistributions and niches based on arbitrary variable type. We show how the formalismcan be used to quantify confounding and therefore help disentangle the complexcausal chains that are present in ecosystems. We also show species distributions andtheir associated niches can be used to infer standard "micro" ecological interactions,such as predation and parasitism. We present several representative use cases thatvalidate our framework, both in terms of being consistent with present knowledge ofa set of known interactions, as well as making and validating predictions about new,previously unknown interactions in the case of zoonoses.