title: Resistant microbial cooccurrence patterns inferred by network topology.
abstract: Although complex cooccurrence patterns have been described for microbes in natural communities, these patterns have scarcely been interpreted in the context of ecosystem functioning and stability. Here we constructed networks from species cooccurrences between pairs of microorganisms which were extracted from five individual aquatic time series, including a dystrophic and a eutrophic lake as well as an open ocean site. The resulting networks exhibited higher clustering coefficients, shorter path lengths, and higher average node degrees and levels of betweenness than those of random networks. Moreover, simulations demonstrated that taxa with a large number of cooccurrences and placement at convergence positions in the network, so-called "hubs" and "bottlenecks," confer resistance against random removal of "taxa." Accordingly, we refer to cooccurrences at convergence positions as system-relevant interdependencies, as they, like hubs and bottlenecks, determine network topology. These topology features of the cooccurrence networks point toward microbial community dynamics being resistant over time and thus could provide indicators for the state of ecosystem stability.
authors.affiliation: Department of Ecology and Genetics, Limnology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden University of Jyväskylä, Department of Biological and Environmental Science, Jyväskylä, Finland.
authors.forename: Sari
authors.initials: S
authors.lastname: Peura
authors.affiliation: Department of Ecology and Genetics, Limnology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden.
authors.forename: Stefan
authors.initials: S
authors.lastname: Bertilsson
authors.affiliation: University of Jyväskylä, Department of Biological and Environmental Science, Jyväskylä, Finland.
authors.forename: Roger I
authors.initials: RI
authors.lastname: Jones
authors.affiliation: Department of Ecology and Genetics, Limnology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden alexander.eiler@ebc.uu.se.
authors.forename: Alexander
authors.initials: A
authors.lastname: Eiler
mesh_terms: D016000:Cluster Analysis; D017753:Ecosystem; D059013:Microbial Consortia; D056265:Microbial Interactions; D008969:Molecular Sequence Data; D017422:Sequence Analysis, DNA; D014871:Water Microbiology