Antibiotic resistance trends among Vibrio vulnificus and Vibrio parahaemolyticus isolated from the Chesapeake Bay, Maryland: a longitudinal study.

Antibiotics are often used to treat severe Vibrio infections, with third-generation cephalosporins and tetracyclines combined or fluoroquinolones alone being recommended by the US Centers for Disease Control and Prevention. Increases in antibiotic resistance of both environmental and clinical vibrios are of concern; however, limited longitudinal data have been generated among environmental isolates to inform how resistance patterns may be changing over time. Hence, we evaluated long-term trends in antibiotic resistance of vibrios isolated from Chesapeake Bay waters (Maryland) across two 3-year sampling periods (2009-2012 and 2019-2022). Vibrio parahaemolyticus (n = 134) and Vibrio vulnificus (n = 94) toxR-confirmed isolates were randomly selected from both sampling periods and tested for antimicrobial susceptibility against eight antibiotics using the Kirby-Bauer disk diffusion method. A high percentage (94%-96%) of V. parahaemolyticus isolates from both sampling periods were resistant to ampicillin and only 2%-6% of these isolates expressed intermediate resistance or resistance to third-generation cephalosporins, amikacin, tetracycline, and trimethoprim-sulfamethoxazole. Even lower percentages of resistant V. vulnificus isolates were observed and those were mostly recovered from 2009 to 2012, however, the presence of multiple virulence factors was observed. The frequency of multi-drug resistance was relatively low (6%-8%) but included resistance against antibiotics used to treat severe vibriosis in adults and children. All isolates were susceptible to ciprofloxacin, a fluoroquinolone, indicating its sustained efficacy as a first-line agent in the treatment of severe vibriosis. Overall, our data indicate that antibiotic resistance patterns among V. parahaemolyticus and V. vulnificus recovered from the lower Chesapeake Bay have remained relatively stable since 2009.IMPORTANCEVibrio spp. have historically been susceptible to most clinically relevant antibiotics; however, resistance and intermediate-resistance have been increasingly recorded in both environmental and clinical isolates. Our data showed that while the percentage of multi-drug resistance and resistance to antibiotics was relatively low and stable across time, some Vibrio isolates displayed resistance and intermediate resistance to antibiotics typically used to treat severe vibriosis (e.g., third-generation cephalosporins, tetracyclines, sulfamethoxazole-trimethoprim, and aminoglycosides). Also, given the high case fatality rates observed with Vibrio vulnificus infections, the presence of multiple virulence factors in the tested isolates is concerning. Nevertheless, the continued susceptibility of all tested isolates against ciprofloxacin, a fluoroquinolone, is indicative of its use as an effective first-line treatment of severe Vibrio spp. infections stemming from exposure to Chesapeake Bay waters or contaminated seafood ingestion.

Community coalescence under variable hydrochemical conditions of the Chesapeake Bay shaped bacterial diversity and functional traits.

Community coalescence related to bacterial mixing events regulates community characteristics and affects the health of estuary ecosystems. At present, bacterial coalescence and its driving factors are still unclear. The present study used a dataset from the Chesapeake Bay (2017) to address how bacterial community coalescence in response to variable hydrochemistry in estuarine ecosystems. We determined that variable hydrochemistry promoted the deterioration of water quality. Temperature, orthophosphate, dissolved oxygen, chlorophyll a, Secchi disk depth, and dissolved organic phosphorus were the key environmental factors driving community coalescence. Bacteria with high tolerance to environmental change were the primary taxa accumulated in community coalescence, and the significance of deterministic processes to communities was revealed. Community coalescence was significantly correlated with the pathways of metabolism and organismal systems, and promoted the co-occurrence of antibiotic resistance and virulence factor genes. Briefly, community coalescence under variable hydrochemical conditions shaped bacterial diversity and functional traits, to optimise strategies for energy acquisition and lay the foundation for alleviating environmental pressures. However, potential pathogenic bacteria in community coalescence may be harmful to human health and environmental safety. The present study provides a scientific reference for ecological management of estuaries.

Evaluating the performance of Bayesian geostatistical prediction with physical barriers in the Chesapeake Bay.

The Chesapeake Bay is one of the most widely studied bodies of water in the United States and around the world. Routine monitoring of water quality indicators (e.g., salinity) relies on fixed sampling stations throughout the Bay. Utilizing this rich monitoring data, various methods produce surface predictions of water quality indicators to further characterize the health of the Bay as well as to support wildlife and human health research studies. Bayesian approaches for geostatistical modelling are becoming increasingly popular and can be preferred over frequentist approaches because full and exact inference can be computed, along with more accurate characterization of uncertainty. Traditional geostatistical prediction methods assume a Euclidean distance between two points when characterizing spatial dependence as a function of distance. However, Euclidean approaches may not be appropriate in estuarine environments when water-land boundaries are crossed during the modelling process. In this study, we compare stationary and barrier INLA geostatistical models with a classic kriging geostatistical model to predict salinity in the Chesapeake Bay during 4 months in 2019. Cross-validation is conducted for each approach to evaluate model performance based on prediction accuracy and precision. The results provide evidence that the two Bayesian-based models outperformed ordinary kriging, especially when examining prediction accuracy (most notably in the tributaries). We also suggest that the non-Euclidean model accounts for the appropriate water-based distances between sampling locations and is likely better at characterizing the uncertainty. However, more complex bodies of water may better showcase the capabilities and efficacy of the physical barrier INLA model.

Assessing the potential long-term effects of sea-level rise on salt marsh's coastal protective capacity under different climate pathway scenarios.

Salt marshes act as natural barriers that reduce wave energy during storm events and help protect coastal communities located in low-lying areas. This ecosystem can be an important asset for climate adaptation due to its particular capability of vertically accrete to adjust to long-term changes in water levels. Therefore, understanding marsh protection benefits thresholds in the face of sea-level rise (SLR) is important for planning future climate adaptation. In this context, the main goal of this manuscript is to examine how the storm protection benefits provided by salt marshes might evolve under SLR projections with different probability levels and emission pathways. In this study, a modeling framework that employs marsh migration predictions from the Sea Level Affecting Marshes Model (SLAMM) as parameterization into a hydrodynamic and wave model (ADCIRC + SWAN) was utilized to explicitly represent wave attenuation by vegetation under storm surge conditions. SLAMM predictions indicate that the SLR scenario, a combination of probability level and emission pathways, plays a substantial role in determining future marsh migration or marsh area loss. For example, results based on the 50% probability, stabilized emissions scenario show an increase of 45% in the marsh area on Maryland's Lower Eastern Shore by 2100, whereas Dorchester County alone could experience a 75% reduction in total salt marsh areas by 2100 under the 1% probability, growing emissions scenario. ADCIRC + SWAN results using SLAMM land cover and elevation outputs indicate that distinct temporal thresholds emerge where marsh extent sharply decreases and wave heights increase, especially after 2050, and exacerbates further after 2080. These findings can be utilized for guiding environmental policies and to aid informed decisions and actions in response to SLR-driven environmental changes.

Margalefidinium polykrikoides dinoflagellate blooms increase mortality of Acartia tonsa copepods.

Previous research on phytoplankton blooms has often focused on the initiation of blooms, while studies on the mechanisms underlying bloom decline and termination have been more limited. This study aimed to explore the extent of which Acartia tonsa (copepod) grazing does or does not contribute to Margalefidinium polykrikoides (dinoflagellate) bloom decline. M. polykrikoides is a prominent harmful algal bloom (HAB) species that forms dense blooms in coastal and estuarine systems around the world with known ichthyotoxic effects. Sampling occurred in the lower York River Estuary, Virginia, USA in 2021 and 2022 during two M. polykrikoides blooms. Prey removal experiments were conducted using organisms collected from the field to estimate A. tonsa ingestion rates on M. polykrikoides. While A. tonsa was capable of ingesting M. polykrikoides at low abundance, when M. polykrikoides abundance exceeded 2000 cells mL-1, A. tonsa experienced nearly 100% mortality in the 24-hour prey removal experiments. This suggests that A. tonsa likely cannot exert any top-down control on M. polykrikoides blooms, rather, at high concentrations, M. polykrikoides may act as its own grazing deterrent. Extensive M. polykrikoides blooms could therefore continue to persist due to a reduction in grazing pressure, rather than an increase. This would suggest that the decline of M. polykrikoides blooms is likely caused by another factor. As the frequency, duration, and magnitude of HABs are expected to increase in the future, these findings provide key insights to the trophic interactions that may be influencing the duration of M. polykrikoides blooms.

The Occurrence of Karenia species in mid-Atlantic coastal waters: Data from the Delmarva Peninsula, USA.

A bloom of Karenia papilionacea that occurred along the Delaware coast in late summer of 2007 was the first Karenia bloom reported on the Delmarva Peninsula (Delaware, Maryland, and Virginia, USA). Limited spatial and temporal monitoring conducted by state agencies and citizen science groups since 2007 have documented that several Karenia species are an annual component of the coastal phytoplankton community along the Delmarva Peninsula, often present at background to low concentrations (100 to 10,000 cells L-1). Blooms of Karenia (> 105 cells L-1) occurred in 2010, 2016, 2018, and 2019 in different areas along the Delmarva Peninsula coast. In late summer and early autumn of 2017, the lower Chesapeake Bay experienced a K. papilionacea bloom, the first recorded in Bay waters. Blooms typically occurred summer into autumn but were not monospecific; rather, they were dominated by either K. mikimotoi or K. papilionacea, with K. selliformis, K. brevis-like cells, and an undescribed Karenia species also present. Cell concentrations during these mid-Atlantic Karenia spp. blooms equalled concentrations reported for other Karenia blooms. However, the negative impacts to environmental and human health often associated with Karenia red tides were not observed. The data compiled here report on the presence of multiple Karenia species in coastal waters of the Delmarva Peninsula detected through routine monitoring and opportunistic sampling conducted between 2007 and 2022, as well as findings from research cruises undertaken in 2018 and 2019. These data should be used as a baseline for future phytoplankton community analyses supporting coastal HAB monitoring programs.

Planktonic eukaryotes in the Chesapeake Bay: contrasting responses of abundant and rare taxa to estuarine gradients.

Phytoplankton are important drivers of aquatic ecosystem function and environmental health. Their community compositions and distributions are directly impacted by environmental processes and human activities, including in the largest estuary in North America, the Chesapeake Bay. It is crucial to uncover how planktonic eukaryotes play fundamental roles as primary producers and trophic links and sustain estuarine ecosystems. In this study, we investigated the detailed community structure and spatiotemporal variations of planktonic eukaryotes in the Chesapeake Bay across space and time for three consecutive years. A clear seasonal and spatial shift of total, abundant, and rare planktonic eukaryotes was evident, and the pattern recurred interannually. Multiple harmful algal species have been identified in the Bay with varied distribution patterns, such as Karlodinium, Heterosigma akashiwo, Protoperidinium sp., etc. Compared to abundant taxa, rare subcommunities were more sensitive to environmental disturbance in terms of richness, diversity, and distribution. The combined effects of temporal variation (13.3%), nutrient availability (10.0%), and spatial gradients (8.8%) structured the distribution of eukaryotic microbial communities in the Bay. Similar spatiotemporal patterns between planktonic prokaryotes and eukaryotes suggest common mechanisms of adjustment, replacement, and species interaction for planktonic microbiomes under strong estuarine gradients. To our best knowledge, this work represents the first systematic study on planktonic eukaryotes in the Bay. A comprehensive view of the distribution of planktonic microbiomes and their interactions with environmental processes is critical in understanding the underlying microbial mechanisms involved in maintaining the stability, function, and environmental health of estuarine ecosystems. IMPORTANCE: Deep sequencing analysis of planktonic eukaryotes in the Chesapeake Bay reveals high community diversity with many newly recognized phytoplankton taxa. The Chesapeake Bay planktonic eukaryotes show distinct seasonal and spatial variability, with recurring annual patterns of total, abundant, and rare groups. Rare taxa mainly contribute to eukaryotic diversity compared to abundant groups, and they are more sensitive to spatiotemporal variations and environmental filtering. Temporal variations, nutrient availability, and spatial gradients significantly affect the distribution of eukaryotic microbial communities. Similar spatiotemporal patterns in prokaryotes and eukaryotes suggest common mechanisms of adjustment, substitution, and species interactions in planktonic microbiomes under strong estuarine gradients. Interannually recurring patterns demonstrate that diverse eukaryotic taxa have well adapted to the estuarine environment with a long residence time. Further investigations of how human activities impact estuarine planktonic eukaryotes are critical in understanding their essential ecosystem roles and in maintaining environmental safety and public health.