title: Seeing the forest for the genes: using metagenomics to infer the aggregated traits of microbial communities.
abstract: Most environments harbor large numbers of microbial taxa with ecologies that remain poorly described and characterizing the functional capabilities of whole communities remains a key challenge in microbial ecology. Shotgun metagenomic analyses are increasingly recognized as a powerful tool to understand community-level attributes. However, much of this data is under-utilized due, in part, to a lack of conceptual strategies for linking the metagenomic data to the most relevant community-level characteristics. Microbial ecologists could benefit by borrowing the concept of community-aggregated traits (CATs) from plant ecologists to glean more insight from the ever-increasing amount of metagenomic data being generated. CATs can be used to quantify the mean and variance of functional traits found in a given community. A CAT-based strategy will often yield far more useful information for predicting the functional attributes of diverse microbial communities and changes in those attributes than the more commonly used analytical strategies. A more careful consideration of what CATs to measure and how they can be quantified from metagenomic data, will help build a more integrated understanding of complex microbial communities.
authors.affiliation: Cooperative Institute for Research in Environmental Sciences, University of Colorado Boulder, CO, USA ; Department of Ecology and Evolutionary Biology, University of Colorado Boulder, CO, USA.
authors.forename: Noah
authors.initials: N
authors.lastname: Fierer
authors.affiliation: Cooperative Institute for Research in Environmental Sciences, University of Colorado Boulder, CO, USA.
authors.forename: Albert
authors.initials: A
authors.lastname: Barberán
authors.affiliation: Environmental Research Institute, School of Science, University of Waikato Hamilton, New Zealand.
authors.forename: Daniel C
authors.initials: DC
authors.lastname: Laughlin
keywords: community-aggregated traits; metagenomics; microbial diversity; microbial ecology; traits