Traits and phylogenetic history contribute to network structure across Canadian plant-pollinator communities


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Authors: Chamberlain, SA; Cartar, RV; Worley, AC; Semmler, SJ; Gielens, G; Elwell, S; Evans, ME; Vamosi, JC; Elle, E
Year: 2014
Journal: Oecologia 176: 545-556   Article Link (DOI)  PubMed
Title: Traits and phylogenetic history contribute to network structure across Canadian plant-pollinator communities
Abstract: Interaction webs, or networks, define how the members of two or more trophic levels interact. However, the traits that mediate network structure have not been widely investigated. Generally, the mechanism that determines plant-pollinator partnerships is thought to involve the matching of a suite of species traits (such as abundance, phenology, morphology) between trophic levels. These traits are often unknown or hard to measure, but may reflect phylogenetic history. We asked whether morphological traits or phylogenetic history were more important in mediating network structure in mutualistic plant-pollinator interaction networks from Western Canada. At the plant species level, sexual system, growth form, and flower symmetry were the most important traits. For example species with radially symmetrical flowers had more connections within their modules (a subset of species that interact more among one another than outside of the module) than species with bilaterally symmetrical flowers. At the pollinator species level, social species had more connections within and among modules. In addition, larger pollinators tended to be more specialized. As traits mediate interactions and have a phylogenetic signal, we found that phylogenetically close species tend to interact with a similar set of species. At the network level, patterns were weak, but we found increasing functional trait and phylogenetic diversity of plants associated with increased weighted nestedness. These results provide evidence that both specific traits and phylogenetic history can contribute to the nature of mutualistic interactions within networks, but they explain less variation between networks.
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