Carbon use efficiency (CUE) is the proportion of carbon consumed by a microbe that is converted to biomass, versus the proportion that is respired as CO2. CUE is an important measurement of the activity of soil microbial communities and a determinant of soil carbon storage. CUE varies significantly across ecosystems, environmental parameters, and taxonomic groups. Though the variation is well documented, the causation is less understood. In order to accurately model ecosystem C fluxes, CUE needs to be more precisely estimated. Using a soil chronosequence and fertility gradient (the “Ecological Staircase” at Jug Handle State Natural Reserve in Mendocino County, California) this dissertation aims to understand the edaphic and biologic controls on CUE. Chapter 1 uses data collected over two years from the Ecological Staircase to identify which edaphic factors are the best estimators of soil microbial CUE. The Ecological Staircase exhibits a wide range of values for many important soil characteristics including pH, nutrient availability and quality, water content, texture, and organic matter content. However, because the chronosequence spans a short distance (~2.5 miles) other confounding factors are kept constant such as vegetation type, climate, parent material, and topography. CUE varies significantly across the chronosequence, peaking at the mid-age site where the environment is limiting but not too stressful. Soil pH, organic matter content, and substrate quality are found to be the most important factors in estimating CUE. Together these factors account for 76% of the variation in CUE across the chronosequence. Chapter 2 focuses on the effects of microbial community composition and functional characteristics on CUE. This chapter utilizes metagenomic sequencing data on samples collected across the chronosequence over the same two-year period as the first chapter. The microbial community composition shifts significantly across the sites and slow-growing taxa like Acidobacteria and fungi are more associated with a higher CUE. Fast-growing taxa like Proteobacteria and Firmicutes are more associated with low CUE. Other important genetic factors include genome size, rRNA operon copy number, genetic diversity, and abundances of genes related to carbon cycling, maintenance metabolism, motility, and membrane transporters. Combined with the results from chapter 1, a conceptual model of ecological strategies across the chronosequence was developed to explain how edaphic, taxonomic, and functional characteristics influence microbial community C cycling. Chapter 3 investigates the mechanism of how soil pH affects CUE. Results from Chapter 1 show that the relationship between CUE and soil pH is non-linear, switching from being positively correlated when pH is below 4.7 to a negative correlation above that threshold. There are multiple reasons that this relationship could exist including changes in microbial community composition, direct stress on microbes when soil becomes too acidic, or other indirect effects on microbial community functions. In order to better understand this mechanism, soil pH was altered in samples from three of the five sites at the Ecological Staircase so that there were samples at low, medium, and high ends of the range of pH at these sites. After a month-long incubation at the new pH values, CUE was measured for each and DNA was extracted from the soils for 16S amplicon sequencing to determine if there were changes in the microbial community composition based on pH changes. Overall the relationship between CUE and pH was quadratic as seen from the observational data in Chapter 1. I determined that pH affects microbial community activity both directly through effects on cellular function as well as indirectly through the role of pH on microbial community composition. Which mechanism was dominant depended upon the initial community; those in the young, fertile sites were more resistant to the effects of pH whereas the infertile sites had much larger shifts in community composition. Together these three chapters provide a comprehensive overview of how edaphic factors, as well as microbial community composition and function, affect microbial carbon use efficiency. These findings are valuable for accurately estimating CUE in C cycling models. This thesis also provides information for determining which types of soils promote soil C accumulation. In addition to improving the understanding of how to incorporate CUE into ecosystem models, it demonstrates how ecological strategies of microbial communities vary across a range of soil fertility.