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The dissimilarity of species interaction networks

Authors

  • Timothée Poisot,

    Corresponding author
    1. Département de biologie, Chimie et Géographie, Université du Québec à Rimouski, Rimouski, QC, Canada
    2. Québec Centre for Biodiversity Sciences, Montréal, QC, Canada
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  • Elsa Canard,

    1. Institut des Sciences de l'Évolution, UMR CNRS-UM2 5554, Université Montpellier 2, Montpellier CEDEX 05, France
    2. Centre de coopération internationale en recherche agronomique pour le développement – PRAM, Martinique, France
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  • David Mouillot,

    1. Écologie des Systèmes Marins Côtiers, UMR 5119, Université Montpellier 2, Montpellier, France
    2. ARC Centre of Excellence for Coral Reef Studies, James Cook University, Townsville, Australia
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  • Nicolas Mouquet,

    1. Institut des Sciences de l'Évolution, UMR CNRS-UM2 5554, Université Montpellier 2, Montpellier CEDEX 05, France
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  • Dominique Gravel

    1. Département de biologie, Chimie et Géographie, Université du Québec à Rimouski, Rimouski, QC, Canada
    2. Québec Centre for Biodiversity Sciences, Montréal, QC, Canada
    3. Institut des Sciences de l'Évolution, UMR CNRS-UM2 5554, Université Montpellier 2, Montpellier CEDEX 05, France
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Abstract

In a context of global changes, and amidst the perpetual modification of community structure undergone by most natural ecosystems, it is more important than ever to understand how species interactions vary through space and time. The integration of biogeography and network theory will yield important results and further our understanding of species interactions. It has, however, been hampered so far by the difficulty to quantify variation among interaction networks. Here, we propose a general framework to study the dissimilarity of species interaction networks over time, space or environments, allowing both the use of quantitative and qualitative data. We decompose network dissimilarity into interactions and species turnover components, so that it is immediately comparable to common measures of β-diversity. We emphasise that scaling up β-diversity of community composition to the β-diversity of interactions requires only a small methodological step, which we foresee will help empiricists adopt this method. We illustrate the framework with a large dataset of hosts and parasites interactions and highlight other possible usages. We discuss a research agenda towards a biogeographical theory of species interactions.

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