The article by Stegen et al. (2013) addresses the challenge of quantifying the processes that govern community assembly and identifying abiotic factors that influence these processes. The authors develop an analytical framework to advance ecological understanding in two primary ways: quantitatively estimating the influences of Drift, Selection, and Dispersal, and using ecological patterns to characterize measured and unmeasured abiotic variables that impose Selection or result in low levels of Dispersal. They apply this framework to subsurface microbial communities in two geologically distinct formations of the unconfined aquifer underlying the Hanford Site in Washington State. Key findings include: 1. **Quantitative Estimation of Processes**: - Drift alone consistently governs about 25% of spatial turnover in community composition. - In deeper, finer-grained sediments, Selection is strong (governing about 60% of turnover), imposed by an unmeasured but spatially structured environmental variable. - In shallower, coarser-grained sediments, Selection is weaker (governing about 30% of turnover), imposed by vertically and horizontally structured hydrological factors. - Low levels of Dispersal (mainly due to spatial isolation) govern nearly 30% of turnover. - Highly permeable sediments are associated with high levels of Dispersal, homogenizing community composition and governing over 20% of turnover. 2. **Characterization of Abiotic Factors**: - The framework distinguishes between unmeasured and measured environmental variables that impose Selection and those that impose Dispersal Limitation. - Unmeasured environmental variables impose Selection in both formations, while measured variables impose Selection in the Hanford formation. - Dispersal Limitation is imposed by spatially structured hydrological factors in the full system and by vertical separation and horizontal distance from the Columbia River in the Hanford formation. The authors conclude that their framework provides inferences that cannot be achieved using preexisting approaches and suggests broad application to facilitate a unified understanding of microbial communities.The article by Stegen et al. (2013) addresses the challenge of quantifying the processes that govern community assembly and identifying abiotic factors that influence these processes. The authors develop an analytical framework to advance ecological understanding in two primary ways: quantitatively estimating the influences of Drift, Selection, and Dispersal, and using ecological patterns to characterize measured and unmeasured abiotic variables that impose Selection or result in low levels of Dispersal. They apply this framework to subsurface microbial communities in two geologically distinct formations of the unconfined aquifer underlying the Hanford Site in Washington State. Key findings include: 1. **Quantitative Estimation of Processes**: - Drift alone consistently governs about 25% of spatial turnover in community composition. - In deeper, finer-grained sediments, Selection is strong (governing about 60% of turnover), imposed by an unmeasured but spatially structured environmental variable. - In shallower, coarser-grained sediments, Selection is weaker (governing about 30% of turnover), imposed by vertically and horizontally structured hydrological factors. - Low levels of Dispersal (mainly due to spatial isolation) govern nearly 30% of turnover. - Highly permeable sediments are associated with high levels of Dispersal, homogenizing community composition and governing over 20% of turnover. 2. **Characterization of Abiotic Factors**: - The framework distinguishes between unmeasured and measured environmental variables that impose Selection and those that impose Dispersal Limitation. - Unmeasured environmental variables impose Selection in both formations, while measured variables impose Selection in the Hanford formation. - Dispersal Limitation is imposed by spatially structured hydrological factors in the full system and by vertical separation and horizontal distance from the Columbia River in the Hanford formation. The authors conclude that their framework provides inferences that cannot be achieved using preexisting approaches and suggests broad application to facilitate a unified understanding of microbial communities.