Incorporating dominant species as proxies for biotic interactions strengthens plant community models

Authors

  • Peter C. le Roux,

    Corresponding author
    1. Department of Geosciences and Geography, University of Helsinki, Helsinki, Finland
    2. Department of Plant Science, University of Pretoria, Pretoria, South Africa
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    • Authors contributed equally to the manuscript.
  • Loïc Pellissier,

    1. Department of Bioscience, Arctic Research Centre, Aarhus University, Roskilde, Denmark
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    • Authors contributed equally to the manuscript.
  • Mary S. Wisz,

    1. Department of Bioscience, Arctic Research Centre, Aarhus University, Roskilde, Denmark
    2. Greenland Climate Research Centre, Greenland Institute of Natural Resources, Nuuk, Greenland
    3. Department of Ecology & Environment, DHI Water & Environment, Hørsholm, Denmark
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  • Miska Luoto

    1. Department of Geosciences and Geography, University of Helsinki, Helsinki, Finland
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Summary

  1. Biotic interactions exert considerable influence on the distribution of individual species and should, thus, strongly impact communities. Implementing biotic interactions in spatial models of community assembly is therefore essential for accurately modelling assemblage properties. However, this remains a challenge due to the difficulty of detecting the role of species interactions and because accurate paired community and environment data sets are required to disentangle biotic influences from abiotic effects.
  2. Here, we incorporate data from three dominant species into community-level models as a proxy for the frequency and intensity of their interactions with other species and predict emergent assemblage properties for the co-occurring subdominant species. By analysing plant community and field-quantified environmental data from specially designed and spatially replicated monitoring grids, we provide a robust in vivo test of community models.
  3. Considering this well-defined and easily quantified surrogate for biotic interactions consistently improved realism in all aspects of community models (community composition, species richness and functional structure), irrespective of modelling methodology.
  4. Dominant species reduced community richness locally and favoured species with similar leaf dry matter content. This effect was most pronounced under conditions of high plant biomass and cover, where stronger competitive impacts are expected. Analysis of leaf dry matter content suggests that this effect may occur through efficient resource sequestration.
  5. Synthesis. We demonstrate the strong role of dominant species in shaping multiple plant community attributes, and thus the need to explicitly include interspecific interactions to achieve robust predictions of assemblage properties. Incorporating information on biotic interactions strengthens our capacity not only to predict the richness and composition of communities, but also how their structure and function will be modified in the face of global change.

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