Can Ecological Interactions be Inferred from Spatial Data?

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Christopher Rhodes Stephens
Constantino Gonzalez-Salazar
Maricarmen Villalobos
Pablo Marquet

Abstract

The characterisation and quantication of ecological interactions, and the construction


of species distributions and their associated ecological niches, is of fundamental


theoretical and practical importance. In this paper we give an overview of a Bayesian


inference framework, developed over the last 10 years, which, using spatial data, offers


a general formalism within which ecological interactions may be characterised and


quantied. Interactions are identied through deviations of the spatial distribution


of co-occurrences of spatial variables relative to a benchmark for the non-interacting


system, and based on a statistical ensemble of spatial cells. The formalism allows for


the integration of both biotic and abiotic factors of arbitrary resolution. We concentrate


on the conceptual and mathematical underpinnings of the formalism, showing


how, using the Naive Bayes approximation, it can be used to not only compare and


contrast the relative contribution from each variable, but also to construct species


distributions and niches based on arbitrary variable type. We show how the formalism


can be used to quantify confounding and therefore help disentangle the complex


causal chains that are present in ecosystems. We also show species distributions and


their associated niches can be used to infer standard "micro" ecological interactions,


such as predation and parasitism. We present several representative use cases that


validate our framework, both in terms of being consistent with present knowledge of


a set of known interactions, as well as making and validating predictions about new,


previously unknown interactions in the case of zoonoses.

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