PubMed · 14014591
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K F BOWDEN. 1963. The mixing processes in a tidal estuary.. https://pubmed.ncbi.nlm.nih.gov/14014591/
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Estuarine ecosystems face increasing heavy metal pollution from rapid urbanization and industrialization, yet the microbial adaptive strategies to multiple metal stressors across different habitats remain poorly understood. This study investigated the diversity and composition of bacterial and fungal communities across free-living (FL), particle-attached (PA), and sediment (SE) fractions from three estuaries with varying heavy metal contamination, and further investigated functional adaptations of bacterial communities. High-throughput amplicon sequencing revealed habitat-specific communities, with SE hosting the highest alpha diversity and enrichment of metal-resistant genera such as Woeseia and Sva1033. Environmental filtering, particularly by Zn, was the dominant driver shaping bacterial assemblages across all habitats, whereas fungal communities displayed greater stochastic assembly patterns. Analysis of 44 high-quality bacterial metagenome-assembled genomes (MAGs) revealed diverse metal resistance genes (cusA, znuB, and zntA), along with enriched metabolic pathways for carbon, nitrogen, and sulfur cycling. Notably, both active efflux/oxidative stress defense and indirect immobilization mechanisms were observed across all habitats, but their relative importance differed: FL and PA communities exhibited a greater reliance on active metal efflux (czcAB) and oxidative stress defense (trxAB) to maintain intracellular homeostasis, whereas SE communities displayed a stronger genomic potential for sulfate reduction (dsrAB) that may contribute to metal immobilization through sulfide precipitation. This metabolic partitioning highlights the complementary roles of different habitats in mediating metal toxicity and biogeochemical cycling, providing new insights into microbial resilience in polluted estuaries and underscoring the urgency of addressing heavy-metal contamination in these critical ecosystems.
Meandering is a fundamental geomorphic feature of rivers that plays a critical role in regulating pollutant attenuation. To elucidate its impact on antibiotic resistance genes (ARGs) distribution in estuarine intertidal sediments, samples were collected from both the landward side (freshwater-dominated) and the seaward side (tide-dominated) of a meander bend during ebb and flood tides. The total relative abundance of ARGs was approximately 2.7 times higher on the landward side, peaking during the ebb tide. Microbial composition analysis showed that genera Acinetobacter and Pseudomonas were dominant at the landward sites, while halophilic genera such as Marinobacter and Exiguobacterium were abundant at the seaward sites. Further analysis of metagenome-assembled genomes (MAGs) demonstrated that the dominant landward genus Acinetobacter acted as a key host of ARGs, with two of four MAGs encoding more than ten ARGs. Notably, the total relative abundance of mobile genetic elements was high but consistent between sides and tidal cycles (p > 0.05). Given this high dissemination risk, we further forecasted the ARGs transfer scenarios to oceanic settings based on a set of offshore MAGs (n = 3626). Three ARGs, i.e., acrA, vanSL, and AAC(2')-Ia, were inferred to have transfer potential, supported by neighboring MGEs detected in marine microorganisms. Analysis of the genomes of predicted recipients in the SRA database confirmed the predicted mobilizations. Together, this study highlights that the meandering planform may serve as a significant barrier, attenuating the discharge of ARGs from terrestrial sources into the marine environment.
Dissolved oxygen (DO) concentrations in estuarine bottom waters are a manifestation of multiple, interacting physical and biogeochemical processes, yet identifying their independent contributions remains challenging. Here, we analyze monthly water quality monitoring data from eight stations across Long Island Sound from 1994 to 2022 using a causal discovery framework (PCMCI+) and transformation of forcing variables. Our goal is to identify and isolate variables that causally influence bottom DO and improve predictive models by minimizing overfitting and multicollinearity. PCMCI+ reveals surface-layer temperature as the most important and consistent negative driver of bottom DO, followed by stratification. Wind events exhibit only brief relief by advection and mixing, while river discharge shows no direct causal link to DO, making it less influential than previously thought. Biogeochemical variables, including chlorophyll-a (Chl-a), nitrate and nitrite, and particulate carbon, influence DO through both contemporaneous and time-lagged pathways, often with signs that shift depending on the process. The derived models were evaluated by comparing skill scores, mean squared error, and Akaike Information Criterion. Both model types perform well, with coefficient of determination values exceeding 0.90 at multiple stations using only 3-5 predictors. Our analysis reveals that the best causal predictors are surface-layer temperature, stratification, Chl-a, and particle carbon. This approach provides a scalable framework for improving prediction models and understanding the mechanistic links that control the seasonal variability of DO in estuarine systems.