Bacteria in soil are responsible for converting labile root exudates into microbial biomass that is more stable. This transformation is important for stabilizing soil organic carbon (SOC) and maintaining soil fertility. Bacterial partitioning of SOC into biosynthesis of new biomass or mineralization to carbon dioxide is defined as bacterial growth efficiency (BGE). BGE is also an integral component of models that simulate carbon dynamics in soil. However, variation in BGE in terrestrial ecosystems is not well understood, nor are environmental factors that influence it. In fact, BGE is often assumed to be constant. This dissertation explores BGE in four terrestrial biomes at the Kellogg Biological Station Long Term Ecological Research site and assesses factors that may influence BGE. BGE is calculated from bacterial production (BP) and respiration (BR) using the formula BGE = BP/(BP+BR). In terrestrial ecosystems, these parameters are often measured using a single radiolabeled substrate, which masks any influence of BGE specific to resources available in the soil. We developed a method that permits BGE measurements to reflect the nutrient status of the soil. BP was measured as 3H-leucine incorporation rate into protein and BR as oxygen consumption rate, both without exogenously added substrates. Using this method, variation of BGE was assessed for soils collected from deciduous forest and three different croplands. We showed that BGE was not constant, but varied from 0.23 to 0.63. Bacterial communities in soils from soybean monoculture cropland tended to have a higher BGE than those in deciduous forests or rotational cropland soils. BGE in cropland soils exhibited a large seasonal variation not observed in forest soils.BGE can also be influenced by the composition of bacterial communities, as different bacterial species have different energy and growth requirements. However, it is challenging to link a general function such as carbon transformation to the structure of the bacterial community because of high functional redundancy. Using 16S rRNA gene surveys of rotation cropland and forest soils, it is proposed that the efficiency of bacterial communities can be predicted. In addition to identification of the types of bacteria in the soil sample, 16S rRNA gene surveys also provide a glimpse of the lifestyle of the bacteria. The identity of the bacteria provides an estimate of the number of 16S rRNA genes in the genome, which can then indicate the ecological strategy of the bacteria. Based on the ecological strategy, the growth efficiency can be predicted. The rotation cropland and forest soils have different community composition but the overall 16S rRNA gene copy number is the same, consistent with the observation that these two communities have similar growth efficiencies. Inclusion of measured values of BGE into DAYCENT, a model simulating nutrient cycling in soils, revealed the sensitivity of the model to changes in BGE. When simulating carbon dynamics in a mock ecosystem, decreasing the default BGE value of 0.45 to the average BGE in forest soils, 0.35, reduced the active carbon fraction by 22%. This led to a 5% reduction in the predicted total soil carbon at equilibrium. Therefore, site-specific BGE is important for improving the predictive capacity of SOC models, especially when investigating the effects of changes in climate, soil edaphic properties and land management practices on labile SOC transformations.
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