Molecular Ecological Networks In Response to Elevated Carbon Dioxide.

Understanding the interactions among different species and their responses to environmental changes is a central goal in ecology. Although the network interactions and their responses to environmental changes have been intensively studied in macroecology, very little is known in microbial ecology because defining the network structure in a microbial community is of a grand challenge. Here, a novel random matrix theory (RMT)-based conceptual framework is developed for identifying both phylogenetic and functional molecular ecological networks (pMENs, fMENs) using metagenomics sequencing data of 16S rRNA genes and GeoChip data from soil microbial communities in a long-term grassland FACE (Free Air CO₂ Enrichment) experiment. Our results demonstrated that RMT-based network approach is powerful in delineating molecular ecological networks in microbial communities. Also, the structure of the identified networks under ambient and elevated CO₂ was substantially different in terms of overall network topology, network composition, node overlap, module preservation, module-based higher order organization (meta-modules), topological roles of individual nodes, and network hubs. These results suggested that elevated CO₂ dramatically altered the network interactions among different phylogenetic and functional groups/populations. In addition, the changes in network structure were significantly correlated with soil carbon and nitrogen content, indicating the potential importance of network interactions in ecosystem functioning. Elucidating network interactions in microbial communities and their responses to environmental changes is fundamentally important for research in microbial ecology, systems microbiology, and global change.