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Hydrologic changes modify microbial community structure and ecosystem functions, especially in wetland systems. Here, we present 24 metagenomes from a coastal freshwater wetland experiment in which we manipulated hydrologic conditions and plant presence. These wetland soil metagenomes will deepen our understanding of how hydrology and vegetation influence microbial functional diversity.

Private groundwater wells can be unmonitored sources of contaminated water that can harm human health. Developing models that predict exposure could allow residents to take action to reduce risk. Machine learning models have been successful in predicting nitrate contamination using geospatial information such as proximity to nitrate sources, but previous models have not considered meteorological factors that change temporally. In this study, we test random forest (regression and classification) and linear regression models to predict nitrate contamination using rainfall, temperature, and readily available soil parameters. We trained and tested models for (1) all of North Carolina, (2) each geographic region in North Carolina, (3) a three‐county region with a high density of animal agriculture, and (4) a three‐county region with a low density of animal agriculture. All regression models had poor predictive performance (R2 < 0.09). The random forest classification model for the coastal plain showed fair agreement (Cohen's κ = 0.23) when trying to predict whether contamination occurred. All other classification models had slight or poor predictive performance. Our results show that temporal changes in rainfall and temperature, or in combination with soil data, are not enough to predict nitrate contamination in most areas of North Carolina. The low level of contamination (<25%) measured during the study could have contributed to the poor performance of the models. [ABSTRACT FROM AUTHOR]

Although the gut and the brain vastly differ in physiological function, they have been interlinked in a variety of different neurological and behavioral disorders. The bacteria that comprise the gut microbiome communicate and influence the function of various physiological processes within the body, including nervous system function. However, the effects of social experience in the context of dominance and social stress on gut microbiome remain poorly understood. Here, we examined whether social experience impacts the host zebrafish (Danio rerio) gut microbiome. We studied how social dominance during the first 2 weeks of social interactions changed the composition of zebrafish gut microbiome by comparing gut bacterial composition, diversity, and relative abundance between socially dominant, submissive, social isolates and control group–housed communal fish. Using amplicon sequencing of the 16S rRNA gene, we report that social dominance significantly affects host gut bacterial community composition but not bacterial diversity. At the genus level, Aeromonas and unclassified Enterobacteriaceae relative abundance decreased in dominant individuals while commensal bacteria (e.g. , Exiguobacterium and Cetobacterium) increased in relative abundance. Conversely, the relative abundance of Psychrobacter and Acinetobacter was increased in subordinates, isolates, and communal fish compared to dominant fish. The shift in commensal and pathogenic bacteria highlights the impact of social experience and the accompanying stress on gut microbiome, with potentially similar effects in other social organisms. [ABSTRACT FROM AUTHOR]

Salinization and eutrophication are nearly ubiquitous in watersheds with human activity. Despite the known impacts of the freshwater salinization syndrome (FSS) to organisms, we demonstrate a pronounced knowledge gap on how FSS alters wetland biogeochemistry. Most experiments assessing FSS and biogeochemistry pertain to coastal saltwater intrusion. The few inland wetland studies mostly add salt as sodium chloride. Sodium chloride alone does not reflect the ionic composition of inland salinization, which derives from heterogeneous sources, producing spatially and temporally variable ionic mixtures. We develop mechanistic hypotheses for how elevated ionic strength and changing ionic composition alter urban wetland sediment biogeochemistry, with the prediction that FSS diminishes nutrient removal capacity via a suite of related direct and indirect processes. We propose that future efforts specifically investigate inland urban wetlands, a category of wetland heavily relied on for its biogeochemical processing ability that is likely to be among the most impacted by salinization. [ABSTRACT FROM AUTHOR]

A comparative study was conducted to understand the relationship between soil and vegetation factors and microbial community structure and function in restored and reference wetlands within a mitigation bank. Microbial functions was found to be influenced by composition of bacterial communities and soil fertility and the denitrifying populations could potential use for the development of predictive models for restoration of biogeochemical transformations and improve the success of wetland restoration efforts.