Microorganisms are vital in mediating the earth’s biogeochemical cycles; yet, despite our rapidly increasing ability to explore complex environmental microbial communities, the relationship between microbial community structure and ecosystem processes remains poorly understood. Here, we address a fundamental and unanswered question in microbial ecology: ‘When do we need to understand microbial community structure to accurately predict function?’ We present a statistical analysis investigating the value of environmental data and microbial community structure independently and in combination for explaining rates of carbon and nitrogen cycling processes within 82 global datasets. Environmental variables were the strongest predictors of process rates but left 44% of variation unexplained on average, suggesting the potential for microbial data to increase model accuracy. Although only 29% of our datasets were significantly improved by adding information on microbial community structure, we observed improvement in models of processes mediated by narrow phylogenetic guilds via functional gene data, and conversely, improvement in models of facultative microbial processes via community diversity metrics. Our results also suggest that microbial diversity can strengthen predictions of respiration rates beyond microbial biomass parameters, as 53% of models were improved by incorporating both sets of predictors compared to 35% by microbial biomass alone. Our analysis represents the first comprehensive analysis of research examining links between microbial community structure and ecosystem function. Taken together, our results indicate that a greater understanding of microbial communities informed by ecological principles may enhance our ability to predict ecosystem process rates relative to assessments based on environmental variables and microbial physiology.

Phylogeny reflects genetic and phenotypic traits in Bacteria and Archaea. The phylogenetic conservatism of microbial traits has prompted the application of phylogeny-based algorithms to predict unknown trait values of extant taxa based on the traits of their evolutionary relatives to estimate, for instance, rRNA gene copy numbers, gene contents or tolerance to abiotic conditions. Unlike the 'macrobial' world, microbial ecologists face scenarios potentially compromising the accuracy of trait reconstruction methods, as, for example, extremely large phylogenies and limited information on the traits of interest. We review 990 bacterial and archaeal traits from the literature and support that phylogenetic trait conservatism is widespread through the tree of life, while revealing that it is generally weak for ecologically relevant phenotypic traits and high for genetically complex traits. We then perform a simulation exercise to assess the accuracy of phylogeny-based trait predictions in common scenarios faced by microbial ecologists. Our simulations show that ca. 60% of the variation in phylogeny-based trait predictions depends on the magnitude of the trait conservatism, the number of species in the tree, the proportion of species with unknown trait values and the mean distance in the tree to the nearest neighbour with a known trait value. Results are similar for both binary and continuous traits. We discuss these results under the light of the reviewed traits and provide recommendations for the use of phylogeny-based trait predictions for microbial ecologists.

Under global change, how biological diversity and ecosystem services are maintained in time is a fundamental question. Ecologists have long argued about multiple mechanisms by which local biodiversity might control the temporal stability of ecosystem properties. Accumulating theories and empirical evidence suggest that, together with different population and community parameters, these mechanisms largely operate through differences in functional traits among organisms. We review potential trait-stability mechanisms together with underlying tests and associated metrics. We identify various trait-based components, each accounting for different stability mechanisms, that contribute to buffering, or propagating, the effect of environmental fluctuations on ecosystem functioning. This comprehensive picture, obtained by combining different puzzle pieces of trait-stability effects, will guide future empirical and modeling investigations. Biotic mechanisms of stability: a jigsaw puzzleAs biodiversity is declining at an unprecedented rate, a particularly urgent scientific challenge is to understand and predict the consequences of biodiversity loss on multiple ecosystem functions [1][2][3]. Temporal stability of the functioning of ecosystems is critical to both intrinsic and human purposes (Box 1, Figure 1). Temporal stability can be defined as the ability of a system to maintain, through time, multiple ecosystem properties (see Glossary) in relation to reference conditions. Key elements of stability (Box 1 and Figure 1) are, for example, inter-annual constancy in ecosystem properties, but also resistance and recovery from environmental change and perturbation. Stability is maintained by populations, communities, and ecosystems that can buffer the effects of environmental variation, thus retaining ecosystem functions such as productivity, carbon sequestration, pollination, etc. The idea that greater biodiversity stabilizes natural communities and ecosystems (i.e., diversity begets stability [4,5]) has led to a longrunning debate on the relationship between species diversity and stability [6,7].