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.

The microbial assemblages of Lake Cisó and Lake Vilar (Banyoles, northeast Spain) were analyzed in space and time by microscopy and by performing PCR-denaturing gradient gel electrophoresis (DGGE) and sequence analysis of 16S rRNA gene fragments. Samples obtained from different water depths and at two different times of the year (in the winter during holomixis and in the early spring during a phytoplankton bloom) were analyzed. Although the lakes have the same climatic conditions and the same water source, the limnological parameters were different, as were most of the morphologically distinguishable photosynthetic bacteria enumerated by microscopy. The phylogenetic affiliations of the predominant DGGE bands were inferred by performing a comparative 16S rRNA sequence analysis. Sequences obtained from Lake Cisó samples were related to gram-positive bacteria and to members of the division Proteobacteria. Sequences obtained from Lake Vilar samples were related to members of the Cytophaga-Flavobacterium-Bacteroides phylum and to cyanobacteria. Thus, we found that like the previously reported differences between morphologically distinct inhabitants of the two lakes, there were also differences among the community members whose morphologies did not differ conspicuously. The changes in the species composition from winter to spring were also marked. The two lakes both contained sequences belonging to phototrophic green sulfur bacteria, which is consistent with microscopic observations, but these sequences were different from the sequences of cultured strains previously isolated from the lakes. Euryarchaeal sequences (i.e., methanogen-and thermoplasmarelated sequences) also were present in both lakes. These euryarchaeal group sequences dominated the archaeal sequences in Lake Cisó but not in Lake Vilar. In Lake Vilar, a new planktonic population related to the crenarchaeota produced the dominant archaeal band. The phylogenetic analysis indicated that new bacterial and archaeal lineages were present and that the microbial diversity of these assemblages was greater than previously known. We evaluated the correspondence between the abundances of several morphotypes and DGGE bands by comparing microscopy and sequencing results. Our data provide evidence that the sequences obtained from the DGGE fingerprints correspond to the microorganisms that are actually present at higher concentrations in the natural system. Identification and quantification of organisms, which provide the key parameters in diversity studies, are routinely performed operations in macroecology but are still difficult tasks in microbial ecology (5, 38). Measurements of bacterial metabolic processes yield valuable ecological information but, most of the time, give no clue as to which species are involved (15). As a result, our knowledge of the taxonomic compositions of microbial communities and of the factors which control the abundance and distribution of microbial populations is extremely limited.Over the last 10 years several molecular techniques have be...

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