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Linking microbial community composition with the corresponding ecosystem functions remains challenging. Because microbial communities can differ in their functional responses, this knowledge gap limits ecosystem assessment, design and management. To develop models that explicitly incorporate microbial populations and guide efforts to characterize their functional differences, we propose a novel approach derived from reliability engineering. This reliability modeling approach is illustrated here using a microbial ecology dataset from denitrifying bioreactors. Reliability modeling is well-suited for analyzing the stability of complex networks composed of many microbial populations. It could also be applied to evaluate the redundancy within a particular biochemical pathway in a microbial community. Reliability modeling allows characterization of the system's resilience and identification of failure-prone functional groups or biochemical steps, which can then be targeted for monitoring or enhancement. The reliability engineering approach provides a new perspective for unraveling the interactions between microbial community diversity, functional redundancy and ecosystem services, as well as practical tools for the design and management of engineered ecosystems.

The concentrations of atmospheric carbon dioxide (CO2) and tropospheric ozone (O3) have been rising due to human activities. However, little is known about how such increases influence soil microbial communities. We hypothesized that elevated CO2 (eCO2) and elevated O3 (eO3) would significantly affect the functional composition, structure and metabolic potential of soil microbial communities, and that various functional groups would respond to such atmospheric changes differentially. To test these hypotheses, we analyzed 96 soil samples from a soybean free-air CO2 enrichment (SoyFACE) experimental site using a comprehensive functional gene microarray (GeoChip 3.0). The results showed the overall functional composition and structure of soil microbial communities shifted under eCO2, eO3 or eCO2+eO3. Key functional genes involved in carbon fixation and degradation, nitrogen fixation, denitrification and methane metabolism were stimulated under eCO2, whereas those involved in N fixation, denitrification and N mineralization were suppressed under eO3, resulting in the fact that the abundance of some eO3-supressed genes was promoted to ambient, or eCO2-induced levels by the interaction of eCO2+eO3. Such effects appeared distinct for each treatment and significantly correlated with soil properties and soybean yield. Overall, our analysis suggests possible mechanisms of microbial responses to global atmospheric change factors through the stimulation of C and N cycling by eCO2, the inhibition of N functional processes by eO3 and the interaction by eCO2 and eO3. This study provides new insights into our understanding of microbial functional processes in response to global atmospheric change in soybean agro-ecosystems.

Estimates of the number of species of bacteria per gram of soil vary between 2000 and 8.3 million (Gans et al., 2005; Schloss and Handelsman, 2006). The highest estimate suggests that the number may be so large as to be impractical to test by amplification and sequencing of the highly conserved 16S rRNA gene from soil DNA (Gans et al., 2005). Here we present the use of high throughput DNA pyrosequencing and statistical inference to assess bacterial diversity in four soils across a large transect of the western hemisphere. The number of bacterial 16S rRNA sequences obtained from each site varied from 26,140 to 53,533. The most abundant bacterial groups in all four soils were the Bacteroidetes, Betaproteobacteria and Alphaproteobacteria. Using three estimators of diversity, the maximum number of unique sequences (operational taxonomic units roughly corresponding to the species level) never exceeded 52,000 in these soils at the lowest level of dissimilarity. Furthermore, the bacterial diversity of the forest soil was phylum rich compared to the agricultural soils, which are species rich but phylum poor. The forest site also showed far less diversity of the Archaea with only 0.009% of all sequences from that site being from this group as opposed to 4%-12% of the sequences from the three agricultural sites. This work is the most comprehensive examination to date of bacterial diversity in soil and suggests that agricultural management of soil may significantly influence the diversity of bacteria and archaea.

Population dynamics are influenced by drivers acting from outside and from within an ecosystem. Extrinsic forces operating over broad spatial scales can impart synchronous behavior to separate populations, while internal, system-specific drivers often lead to idiosyncratic behavior. Here, we demonstrate synchrony in community-level dynamics among phytoplankton and bacteria in six north temperate humic lakes. The influence of regional meteorological factors explained much of the temporal variability in the phytoplankton community, and resulted in synchronous patterns of community change among lakes. Bacterial dynamics, in contrast, were driven by system-specific interactions with phytoplankton. Despite the importance of intrinsic factors for determining bacterial community composition and dynamics, we demonstrated that biological interactions transmitted the signal of the regional extrinsic drivers to the bacterial communities, ultimately resulting in synchronous community phenologies for bacterioplankton communities as well. This demonstrates how linkages between the components of a complex biological system can work to simplify the dynamics of the system and implies that it may be possible to predict the behavior of microbial communities responsible for important biogeochemical services in the landscape.