Wetlands are significant components of the global carbon (C) cycle, acting as the largest biogenic source of methane and highly active in carbon dioxide respiration. Dynamic water level fluctuations control the spatiotemporal occurrence of terrestrial-aquatic interfaces (TAIs) in wetlands, which may process C differently from their end-members. TAIs represent a critical and understudied component of wetland C budgets, across which microbial structure and function are seldom characterized. We sought to 1) seasonally assess how microbial community structure and their C-cycling functions vary across the TAI and across wetlands that vary in the frequency and duration of inundation (i.e., hydrologic regime); and 2) evaluate the relative importance of community structure to C-cycling functional diversity. Since November 2024 we periodically collect 30cm deep sediment cores from four topographic zones along a TAI (wetland basin to upland) of 12 wetlands that vary in hydrologic regime. Homogenized cores were aliquoted for genomic analysis (16S rRNA gene amplicons, metagenomes, metatranscriptomes) and sediment chemistry. Along a TAI, we predict that C-cycling functions and community structure are unique to topographic zones, driven by redox conditions. Further, we expect C-cycling functions to respond non-linearly along TAIs, such that the intermediate zone reflects a hotspot interface for C-processing relative to the basin and upland. Within wetlands, we predict hydrologic stability to result in less diverse and more selected communities within a given zone, and diversity to increase with increased hydrologic variability. Across wetlands, we expect that the more dissimilar the hydrologic regime, the more dissimilar community structure will be when comparing the same topographic zone. Finally, we expect that wetland TAIs will be functionally redundant, such that community structure does not regulate functional diversity and structure. This research highlights how dynamic aquatic interfaces impact wetland C-cycling and improves the modeling accuracy of wetland C budgets.