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Data from: Accelerating homogenization of the global plant–frugivore meta-network


Fricke, Evan; Svenning, Jens-Christian (2020), Data from: Accelerating homogenization of the global plant–frugivore meta-network, Dryad, Dataset,


Introductions of species by humans are causing the homogenization of species composition across biogeographic barriers. The ecological and evolutionary consequences of introduced species derive from their effects on networks of species interactions, but we lack a quantitative understanding of the impacts of introduced species on ecological networks and their biogeographic patterns globally. Here we address this data gap by analysing mutualistic seed-dispersal interactions from 410 local networks, encompassing 24,455 unique pairwise interactions between 1,631 animal and 3,208 plant species. We show that species introductions reduce biogeographic compartmentalization of the global meta-network, in which nodes are species and links are interactions observed within any local network. This homogenizing effect extends across spatial scales, decreasing beta diversity among local networks and modularity within networks. The prevalence of introduced interactions is directly related to human environmental modification and is accelerating, having increased sevenfold over the past 75 years. These dynamics alter the coevolutionary environments that mutualists experience, and we find that introduced species disproportionately interact with other introduced species. These processes are likely to amplify biotic homogenization in future ecosystems and may reduce the resilience of ecosystems by allowing perturbations to propagate more quickly and exposing disparate ecosystems to similar drivers. Our results highlight the importance of managing the increasing homogenization of ecological complexity. 

Usage Notes

Open the .Rproj file and run 'network homogenization analysis.R' within the analysis folder to reproduce analyses and figures.


National Science Foundation, Award: DBI-1639145

VILLUM FONDEN, Award: 16549