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A theory for species co-occurrence in interaction networks
Authors:Email author" target="_blank">Kévin?CazellesEmail author  Miguel?B?Araújo  Nicolas?Mouquet  Dominique?Gravel
Institution:1.Institut des Sciences de l’Evolution, CNRS UMR 5554,Université de Montpellier,Montpellier Cedex 5,France;2.Département de Biologie, Chimie et Géographie,Université du Québec à Rimouski,Québec,Canada;3.Imperial College London,Ascot,UK;4.Department of Biogeography Global Change,National Museum of Natural Sciences, CSIC,Madrid,Spain;5.Center for Macroecology, Evolution and Climate,University of Copenhagen,Copenhagen,Denmark
Abstract:The study of species co-occurrences has been central in community ecology since the foundation of the discipline. Co-occurrence data are, nevertheless, a neglected source of information to model species distributions and biogeographers are still debating about the impact of biotic interactions on species distributions across geographical scales. We argue that a theory of species co-occurrence in ecological networks is needed to better inform interpretation of co-occurrence data, to formulate hypotheses for different community assembly mechanisms, and to extend the analysis of species distributions currently focused on the relationship between occurrences and abiotic factors. The main objective of this paper is to provide the first building blocks of a general theory for species co-occurrences. We formalize the problem with definitions of the different probabilities that are studied in the context of co-occurrence analyses. We analyze three species interactions modules and conduct multi-species simulations in order to document five principles influencing the associations between species within an ecological network: (i) direct interactions impact pairwise co-occurrence, (ii) indirect interactions impact pairwise co-occurrence, (iii) pairwise co-occurrence rarely are symmetric, (iv) the strength of an association decreases with the length of the shortest path between two species, and (v) the strength of an association decreases with the number of interactions a species is experiencing. Our analyses reveal the difficulty of the interpretation of species interactions from co-occurrence data. We discuss whether the inference of the structure of interaction networks is feasible from co-occurrence data. We also argue that species distributions models could benefit from incorporating conditional probabilities of interactions within the models as an attempt to take into account the contribution of biotic interactions to shaping individual distributions of species.
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