Permafrost soil characteristics and microbial community structure across a boreal forest watershed vary over short spatial scales and dictate community responses to thaw.

Understanding drivers of permafrost microbial community structure and function is critical for understanding permafrost microbiology and predicting ecosystem responses to thaw; however, studies describing ecological controls on these communities are lacking. We hypothesize that permafrost communities are uniquely shaped by constraints imposed by prolonged freezing, and decoupled from the selective factors that influence non-permafrost soil communities, but that pre-thaw environmental and community characteristics will be strong determinants of community structure and function post-thaw. We characterized patterns of environmental variation and microbial community composition in sixty permafrost samples spanning landscape gradients in a boreal forest watershed, and monitored community responses to thaw. Consistent with our hypothesis, we found that, proportionally, the strongest process influencing permafrost community composition was dispersal limitation (0.36), exceeding the influence of homogenous selection (0.21) and variable selection (0.16), and that deterministic selection arose primarily from energetic constraints of the permafrost environment. Our data supported a structural equation model in which organic carbon thermodynamics and organic acid content, influenced redox conditions and total selection. Post-thaw community composition was found to be driven primarily by pre-thaw community composition, indicating a strong influence of historical conditions. Together, these results suggest that community responses to thaw may be highly varied over short distances and that changes in community structure and function are likely to be drastic, as changes to system hydrology mobilize organisms and nutrients, thereby relieving the primary constraints on the system. These findings are being integrated with metabolomic and metatranscriptomic analyses to improve understanding of how pre-thaw conditions can be used to predict microbial activity post-thaw.