Subterranean estuaries (STEs) play an important role in linking nutrient cycling between marine and terrestrial systems. As being the primary drivers of nutrient cycling, the composition of microbial communities and their adaptation toward both, terrestrial and marine conditions are of special interest. While bacterial communities of STEs have received increasing scientific attention, archaeal and meiofaunal diversity was mostly neglected. Previous studies at the investigated sampling site, the STE of a mesotidal beach at the German North Sea island of Spiekeroog, focused on spatial and seasonal patterns of geochemical and bacterial diversity. By additionally investigating the archaeal and meiofaunal diversity and distribution, we now aimed to fill this gap of knowledge to understand the microbial response to submarine groundwater discharge (SGD). The topography of Spiekeroog beach and associated geochemical gradients in porewater displayed a distinct cross-shore zonation, with seawater infiltration on the upper beach at the high water line (HWL), and saline and brackish porewater exfiltration (SGD) at the ridge-runnel structure and the low water line (LWL) on the lower beach. This led to a higher evenness of prokaryotic communities in lower beach areas impacted by SGD compared to unimpacted areas. Archaea contributed 1–4% to the 16S rRNA gene sequence dataset. Those were dominated by Nitrosopumilaceae, corresponding well to higher concentrations of NH4+ in the discharge area of the STE. The unimpacted sites had elevated abundances of Wosearchaeia, which were also detected previously in impacted areas of an STE at Mobile Bay (Gulf of Mexico). While a large proportion of prokaryotes were present in the entire intertidal area, meiofaunal community compositions were site specific and dominated by nematodes. Nematode communities of the high-water line differed distinctively from the other sites. Overall, our data indicates that the three domains of life display distinctly different adaptations when facing the same conditions within the STE. Therefore, distribution patterns of any domain can only be understood if all of them, together with basic environmental information are investigated in an integrated context.
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