Salinization, a widespread threat to the structure and ecological functioning of inland and coastal wetlands, is currently occurring at an unprecedented rate and geographic scale. The causes of salinization are diverse and include alterations to freshwater flows, land‐clearance, irrigation, disposal of wastewater effluent, sea level rise, storm surges, and applications of de‐icing salts. Climate change and anthropogenic modifications to the hydrologic cycle are expected to further increase the extent and severity of wetland salinization. Salinization alters the fundamental physicochemical nature of the soil‐water environment, increasing ionic concentrations and altering chemical equilibria and mineral solubility. Increased concentrations of solutes, especially sulfate, alter the biogeochemical cycling of major elements including carbon, nitrogen, phosphorus, sulfur, iron, and silica. The effects of salinization on wetland biogeochemistry typically include decreased inorganic nitrogen removal (with implications for water quality and climate regulation), decreased carbon storage (with implications for climate regulation and wetland accretion), and increased generation of toxic sulfides (with implications for nutrient cycling and the health/functioning of wetland biota). Indeed, increased salt and sulfide concentrations induce physiological stress in wetland biota and ultimately can result in large shifts in wetland communities and their associated ecosystem functions. The productivity and composition of freshwater species assemblages will be highly altered, and there is a high potential for the disruption of existing interspecific interactions. Although there is a wealth of information on how salinization impacts individual ecosystem components, relatively few studies have addressed the complex and often non‐linear feedbacks that determine ecosystem‐scale responses or considered how wetland salinization will affect landscape‐level processes. Although the salinization of wetlands may be unavoidable in many cases, these systems may also prove to be a fertile testing ground for broader ecological theories including (but not limited to): investigations into alternative stable states and tipping points, trophic cascades, disturbance‐recovery processes, and the role of historical events and landscape context in driving community response to disturbance.

To better understand the distribution of soil microbial communities at multiple spatial scales, a survey was conducted to examine the spatial organization of community structure in a wheat field in eastern Virginia (USA). Nearly 200 soil samples were collected at a variety of separation distances ranging from 2.5 cm to 11 m. Whole-community DNA was extracted from each sample, and community structure was compared using amplified fragment length polymorphism (AFLP) DNA fingerprinting. Relative similarity was calculated between each pair of samples and compared using geostatistical variogram analysis to study autocorrelation as a function of separation distance. Spatial autocorrelation was found at scales ranging from 30 cm to more than 6 m, depending on the sampling extent considered. In some locations, up to four different correlation length scales were detected. The presence of nested scales of variability suggests that the environmental factors regulating the development of the communities in this soil may operate at different scales. Kriging was used to generate maps of the spatial organization of communities across the plot, and the results demonstrated that bacterial distributions can be highly structured, even within a habitat that appears relatively homogeneous at the plot and field scale. Different subsets of the microbial community were distributed differently across the plot, and this is thought to be due to the variable response of individual populations to spatial heterogeneity associated with soil properties.

Environmental perturbations in wetlands affect the integrated plant-microbial-soil system, causing biogeochemical responses that can manifest at local to global scales. The objective of this study was to determine how saltwater intrusion affects carbon mineralization and greenhouse gas production in coastal wetlands. Working with tidal freshwater marsh soils that had experienced ~ 3.5 yr of in situ saltwater additions, we quantified changes in soil properties, measured extracellular enzyme activity associated with organic matter breakdown, and determined potential rates of anaerobic carbon dioxide (CO2) and methane (CH4) production. Soils from the field plots treated with brackish water had lower carbon content and higher C : N ratios than soils from freshwater plots, indicating that saltwater intrusion reduced carbon availability and increased organic matter recalcitrance. This was reflected in reduced activities of enzymes associated with the hydrolysis of cellulose and the oxidation of lignin, leading to reduced rates of soil CO2 and CH4 production. The effects of long-term saltwater additions contrasted with the effects of short-term exposure to brackish water during three-day laboratory incubations, which increased rates of CO2 production but lowered rates of CH4 production. Collectively, our data suggest that the long-term effect of saltwater intrusion on soil CO2 production is indirect, mediated through the effects of elevated salinity on the quantity and quality of autochthonous organic matter inputs to the soil. In contrast, salinity, organic matter content, and enzyme activities directly influence CH4 production. Our analyses demonstrate that saltwater intrusion into tidal freshwater marshes affects the entire process of carbon mineralization, from the availability of organic carbon through its terminal metabolism to CO2 and/or CH4, and illustrate that long-term shifts in biogeochemical functioning are not necessarily consistent with short-term disturbance-type responses.

Environmental metagenomic analysis is typically accomplished by assigning taxonomy and/or function from whole genome sequencing or 16S amplicon sequences. Both of these approaches are limited, however, by read length, among other technical and biological factors. A nanopore-based sequencing platform, MinION™, produces reads that are ≥1 × 10⁴ bp in length, potentially providing for more precise assignment, thereby alleviating some of the limitations inherent in determining metagenome composition from short reads. We tested the ability of sequence data produced by MinION (R7.3 flow cells) to correctly assign taxonomy in single bacterial species runs and in three types of low-complexity synthetic communities: a mixture of DNA using equal mass from four species, a community with one relatively rare (1%) and three abundant (33% each) components, and a mixture of genomic DNA from 20 bacterial strains of staggered representation. Taxonomic composition of the low-complexity communities was assessed by analyzing the MinION sequence data with three different bioinformatic approaches: Kraken, MG-RAST, and One Codex. Results: Long read sequences generated from libraries prepared from single strains using the version 5 kit and chemistry, run on the original MinION device, yielded as few as 224 to as many as 3497 bidirectional high-quality (2D) reads with an average overall study length of 6000 bp. For the single-strain analyses, assignment of reads to the correct genus by different methods ranged from 53.1% to 99.5%, assignment to the correct species ranged from 23.9% to 99.5%, and the majority of misassigned reads were to closely related organisms. A synthetic metagenome sequenced with the same setup yielded 714 high quality 2D reads of approximately 5500 bp that were up to 98% correctly assigned to the species level. Synthetic metagenome MinION libraries generated using version 6 kit and chemistry yielded from 899 to 3497 2D reads with lengths averaging 5700 bp with up to 98% assignment accuracy at the species level. The observed community proportions for “equal” and “rare” synthetic libraries were close to the known proportions, deviating from 0.1% to 10% across all tests. For a 20-species mock community with staggered contributions, a sequencing run detected all but 3 species (each included at 99% of reads were assigned to the correct family. Conclusions: At the current level of output and sequence quality (just under 4 × 10³ 2D reads for a synthetic metagenome), MinION sequencing followed by Kraken or One Codex analysis has the potential to provide rapid and accurate metagenomic analysis where the consortium is comprised of a limited number of taxa. Important considerations noted in this study included: high sensitivity of the MinION platform to the quality of input DNA, high variability of sequencing results across libraries and flow cells, and relatively small numbers of 2D reads per analysis limit. Together, these limited detection of very rare components of the microbial consortia, and would likely limit the utility of MinION for the sequencing of high-complexity metagenomic communities where thousands of taxa are expected. Furthermore, the limitations of the currently available data analysis tools suggest there is considerable room for improvement in the analytical approaches for the characterization of microbial communities using long reads. Nevertheless, the fact that the accurate taxonomic assignment of high-quality reads generated by MinION is approaching 99.5% and, in most cases, the inferred community structure mirrors the known proportions of a synthetic mixture warrants further exploration of practical application to environmental metagenomics as the platform continues to develop and improve. With further improvement in sequence throughput and error rate reduction, this platform shows great promise for precise real-time analysis of the composition and structure of more complex microbial communities.

A series of microcosm experiments was performed using serial dilutions of a sewage microbial community to inoculate a set of batch cultures in sterile sewage. After inoculation, the dilution-defined communities were allowed to regrow for several days and a number of community attributes were measured in the regrown assemblages. Based upon a set of numerical simulations, community structure was expected to differ along the dilution gradient; the greatest differences in structure were anticipated between the undiluted–low-dilution communities and the communities regrown from the very dilute (more than 10 ⁻⁴ ) inocula. Furthermore, some differences were expected among the lower-dilution treatments (e.g., between undiluted and 10 ⁻¹ ) depending upon the evenness of the original community. In general, each of the procedures used to examine the experimental community structures separated the communities into at least two, often three, distinct groups. The groupings were consistent with the simulated dilution of a mixture of organisms with a very uneven distribution. Significant differences in community structure were detected with genetic (amplified fragment length polymorphism and terminal restriction fragment length polymorphism), physiological (community level physiological profiling), and culture-based (colony morphology on R2A agar) measurements. Along with differences in community structure, differences in community size (acridine orange direct counting), composition (ratio of sewage medium counts to R2A counts, monitoring of each colony morphology across the treatments), and metabolic redundancy (i.e., generalist versus specialist) were also observed, suggesting that the differences in structure and diversity of communities maintained in the same environment can be manifested as differences in community organization and function.