A holistic understanding of how biotic and abiotic factors govern rhizosphere-microbial community assembly has been a long-standing goal in microbial ecology. Despite the cataloguing of factors that influence community assembly, the ability to predict how communities will assemble in contrasting environments or predict the effect of external drivers is lacking.
Understanding processes that govern the assembly of communities is a major goal of the competitor/stress-tolerator/ruderal (CSR) theory. The CSR theory proposes that organisms face a three-way resource trade-off between investment in traits that facilitate: competition for resources (Competitive traits); survival in underproductive environments (Stress-tolerant traits); and survival in disturbed environments (Ruderal traits). Classification of an organism, or a community, as a C-, S- or R-type facilitates comparisons of community function and the environmental constraints shaping different communities. CSR theory was originally devised for plant-community ecology but opportunities are now open to apply this to microbial communities.
The aim of this study was to investigate whether Grime’s CSR classification scheme, could be applied to soil microbial communities with differing abiotic and biotic drivers. Microcosm experiments were used to separate the impact of cadmium (Cd) and the presence of a Cd-accumulating plant, Carpobrotus rossii, on the assembly of soil-bacterial communities. Illumina 16S rRNA profiles and predictive-metagenomic-profiling software (PICRUSt) were used to determine community-aggregated traits (CATs) and ascribe CSR classifications to microbial communities.
We identified functional CATs enriched in rhizosphere and bulk soils that belonged to coherent CSR groups with competition-related traits enriched in the rhizosphere and stress-tolerant/ruderal traits enriched in bulk soils. Additionally, whilst the presence of the plant rhizosphere significantly reduced community richness, the addition of Cd altered abundances of operational taxonomic units within the community, increasing Sphingomonadale and Sphingobacterale abundance.
The results suggest that predictive-metagenomic profiling and CATs can be used to ascribe CSR classifications to microbial communities. Further work towards developing a simplified framework for microbial CSR classification would facilitate interpretation and comparison of microbial communities from a diverse range of disparate environments.