With the increase in ecological data production, the need for robust automated functional community analysis approaches rises, creating an information-analysis gap. An accumulating body of evidence now supports the reliability of metabolic analysis, such as metabolic networks, as a tool for processing genomic information into describing the `lifestyle` of microbial species and the network of interaction they form within such communities. The integration of multiple singles species networks into a communal metabolic network representation allows for the investigation of the functional division between its participants, showing the metabolic hierarchy in the sampled environment. This work aims at looking beyond the species list and dynamically finding the functional significance and impact of each member on its community. Here we demonstrate the use of such metabolic network approaches in the functional division analysis of communities in the rhizosphere and bulk soil environments based on metagenomic data that was collected for cucumber and wheat crops. Applying ecological definitions for the description of niche complexity, metabolic reactions were classified as diverse – that is carried by a variety of species, or dominant – that is associated with a specific taxonomic group. Iterative removal of metabolic functions associated with specific taxonomic groups indicated that primary metabolism functions are carried by a diverse set of microbial species where the metabolism of secondary metabolites is associated with specific taxonomic groups. For example, the Rhizobiales taxonomic group has shown an effect on Xylene degradation, Burkholderials on the metabolism of terpenoids and Xantomonadales on cysteine metabolism. Species combinations lead to the synergistic emergence of new functions, missing in the single-species networks. The degree of complementation varies between different species combinations.
