Vertical zonation within estuarine ecosystems can strongly influence microbial diversity and function by regulating competition, predation, and environmental stability. The degree to which microbial communities exhibit horizontal patterns through an estuary has received comparatively less attention. Here, we take a multi-omics ecosurveillance approach to study environmental gradients created by the transition between dominant vegetation types along a near pristine tropical river system (Wenlock River, Far North Queensland, Australia). The study sites included intertidal mudflats fringed by saltmarsh, mangrove or mixed soft substrata habitats. Collected sediments were analyzed for eukaryotes and prokaryotes using small sub-unit (SSU) rRNA gene amplicons to profile the relative taxonomic composition. Central carbon metabolism metabolites and other associated organic polar metabolites were analyzed using established metabolomics-based approaches, coupled with total heavy metals analysis. Eukaryotic taxonomic information was found to be more informative of habitat type. Bacterial taxonomy and community composition also showed habitat-specificity, with phyla Proteobacteria and Cyanobacteria strongly linked to mangroves and saltmarshes, respectively. In contrast, metabolite profiling was critical for understanding the biochemical pathways and expressed functional outputs in these systems that were tied to predicted microbial gene function (16S rRNA). A high degree of metabolic redundancy was observed in the bacterial communities, with the metabolomics data suggesting varying degrees of metabolic criticality based on habitat type. The predicted functions of the bacterial taxa combined with annotated metabolites accounted for the conservative perspective of microbial community redundancy against the putative metabolic pathway impacts in the metabolomics data. Coupling these data demonstrates that habitat-mediated estuarine gradients drive patterns of community diversity and metabolic function and highlights the real redundancy potential of habitat microbiomes. This information is useful as a point of comparison for these sensitive ecosystems and provides a framework for identifying potentially vulnerable or at-risk systems before they are significantly degraded.

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