Eutrophication and Deoxygenation Drive High Methane Emissions from a Brackish Coastal System.

Coastal environments are a major source of marine methane in the atmosphere. Eutrophication and deoxygenation have the potential to amplify the coastal methane emissions. Here, we investigate methane dynamics in the eutrophic Stockholm Archipelago. We cover a range of sites with contrasting water column redox conditions and rates of organic matter degradation, with the latter reflected by the depth of the sulfate-methane transition zone (SMTZ) in the sediment. We find the highest benthic release of methane (2.2-8.6 mmol m-2 d-1) at sites where the SMTZ is located close to the sediment-water interface (2-10 cm). A large proportion of methane is removed in the water column via aerobic or anaerobic microbial pathways. At many locations, water column methane is highly depleted in 13C, pointing toward substantial bubble dissolution. Calculated and measured rates of methane release to the atmosphere range from 0.03 to 0.4 mmol m-2 d-1 and from 0.1 to 1.7 mmol m-2 d-1, respectively, with the highest fluxes at locations with a shallow SMTZ and anoxic and sulfidic bottom waters. Taken together, our results show that sites suffering most from both eutrophication and deoxygenation are hotspots of coastal marine methane emissions.

Haplosporidium nelsoni and Perkinsus marinus occurrence in waters of Great Bay Estuary, New Hampshire.

In Great Bay Estuary, New Hampshire, USA, Haplosporidium nelsoni and Perkinsus marinus are 2 active pathogens of the eastern oyster Crassostrea virginica (Gmelin), that cause MSX (multinucleated sphere with unknown affinity 'X') and dermo mortalities, respectively. Whereas studies have quantified infection intensities in oyster populations and determined whether these parasites exist in certain planktonic organisms, no studies thus far have examined both infectious agents simultaneously in water associated with areas that do and do not have oyster populations. As in other estuaries, both organisms are present in estuarine waters throughout the Bay, especially during June through November, when oysters are most active. Waters associated with oyster habitats had higher, more variable DNA concentrations from these pathogenic organisms than waters at a non-oyster site. This finding allows for enhanced understanding of disease-causing organisms in New England estuaries, where oyster restoration is a priority.

Integrating experiments with modeling to understand key bacterial taxa dynamics after episodic mixing of a stratified water column.

Hydraulic mixing of stratified reservoirs homogenizes physicochemical gradients and microbial communities. This has potential repercussions for microbial metabolism and water quality, not least in dams and hydraulically controlled waters. A better understanding of how key taxa respond to mixing of such stratified water bodies is needed to understand and predict the impact of hydraulic operations on microbial communities and nutrient dynamics in reservoirs. We studied taxa transitions between cyanobacteria and sulfur-transforming bacteria following mixing of stratified water columns in bioreactors and complemented the experimental approach with a biogeochemical model. Model predictions were consistent with experimental observations, suggesting that stable stratification of DO is restored within 24 h after episodic and complete mixing, at least in the absence of other more continuous disturbances. Subsequently, the concentration of S2- gradually return to pre-mixing states, with higher concentration at the surface and lower in the bottom waters, while the opposite pattern was seen for SO42-. The total abundance of sulfate-reducing bacteria and phototrophic sulfur bacteria increased markedly after 24h of mixing. The model further predicted that the rapid re-oxygenation of the entire water column by aeration will effectively suppress the water stratification and the growth of sulfur-transforming bacteria. Based on these results, we suggest that a reduction of thermocline depth by optimal flow regulation in reservoirs may also depress sulfur transforming bacteria and thereby constrain sulfur transformation processes and pollutant accumulation. The simulation of microbial nutrient transformation processes in vertically stratified waters can provide new insights about effective environmental management measures for reservoirs.

Biofilm formation and cell plasticity drive diazotrophy in an anoxygenic phototrophic bacterium.

IMPORTANCE: The contribution of non-cyanobacterial diazotrophs (NCDs) to total N2 fixation in the marine water column is unknown, but their importance is likely constrained by the limited availability of dissolved organic matter and low O2 conditions. Light could support N2 fixation and growth by NCDs, yet no examples from bacterioplankton exist. In this study, we show that the phototrophic NCD, Rhodopseudomonas sp. BAL398, which is a member of the diazotrophic community in the surface waters of the Baltic Sea, can utilize light. Our study highlights the significance of biofilm formation for utilizing light and fixing N2 under oxic conditions and the role of cell plasticity in regulating these processes. Our findings have implications for the general understanding of the ecology and importance of NCDs in marine waters.

Phaeogromids of the mesopelagic marine plankton: Temporal variability of concentrations and observations of feeding structures of four species from the mesopelagic in the Mediterranean Sea.

Challengerids, phaeogromids rhizarian protists, are emblematic protists of the deep sea but are also enigmatic as they occur in very low concentrations. In previous studies, we reported on temporal changes in abundance at a near-shore mesopelagic site, but only as part of sampling of the entire microplankton assemblage, not well-suited for examining phaeogromids. Consequently, we turned to using a closing plankton net to provide material from large volumes of seawater, thus allowing for more robust estimates of concentrations and material for observations of living cells, to our knowledge the first made. Here, we report our results on the four most commonly occurring species: Challengeranium diadon, Challengereron willemoesii, Challengeria xiphodon, and Euphysetta lucani. In contrast to our previous report, we found that changes in concentrations were not related to water column stratification, and the four species roughly co-varied with time. Observations of live cells revealed that all four species deploy tentacle-like pseudopods and also very large unstructured webs of fine pseudopods. The similarities in feeding webs suggest similar prey are exploited, and the similar temporal changes in abundances suggest a common factor or factors (unknown at this time) govern their concentrations. Films of live cells are provided in Supplementary Files.

Riverine Discharge Fuels the Production of Methylmercury in a Large Temperate Estuary.

Estuaries are an important food source for the world's growing population, yet human health is at risk from elevated exposure to methylmercury (MeHg) via the consumption of estuarine fish. Moreover, the sources and cycling of MeHg in temperate estuarine ecosystems are poorly understood. Here, we investigated the seasonal and tidal patterns of mercury (Hg) forms in Long Island Sound (LIS), in a location where North Atlantic Ocean waters mix with the Connecticut River. We found that seasonal variations in Hg and MeHg in LIS followed the extent of riverine Hg delivery, while tides further exacerbated the remobilization of earlier deposited riverine Hg. The net production of MeHg near the river plume was significant compared to that in other locations and enhanced during high tide, possibly resulting from the enhanced microbial activity and organic carbon remineralization in the river plume. Statistical models, driven by our novel data, further support the hypothesis that the river-delivered organic matter and inorganic Hg drive net MeHg production in the estuarine water column. Our study sheds light on the significance of water column biogeochemical processes in temperate tidal estuaries in regulating MeHg levels and inspires new questions in our quest to understand MeHg sources and dynamics in coastal oceans.

Low-Density Plastic Debris Dispersion beneath the Mediterranean Sea Surface.

Plastic is a widespread marine pollutant, with most studies focusing on the distribution of floating plastic debris at the sea surface. Recent evidence, however, indicates a significant presence of such low density plastic in the water column and at the seafloor, but information on its origin and dispersion is lacking. Here, we studied the pathways and fate of sinking plastic debris in the Mediterranean Sea, one of the most polluted world seas. We used a recent Lagrangian plastic-tracking model, forced with realistic parameters, including a maximum estimated sinking speed of 7.8 m/d. Our simulations showed that the locations where particles left the surface differed significantly from those where they reached the seafloor, with lateral transport distances between 119 and 282 km. Furthermore, 60% of particles deposited on the bottom coastal strip (20 km wide) were released from vessels, 20% from the facing country, and 20% from other countries. Theoretical considerations furthermore suggested that biological activities potentially responsible for the sinking of low density plastic occur throughout the water column. Our findings indicate that the responsibility for seafloor plastic pollution is shared among Mediterranean countries, with potential impact on pelagic and benthic biota.

Frequency-Domain Reverse-Time Migration with Analytic Green's Function for the Seismic Imaging of Shallow Water Column Structures in the Arctic Ocean.

Seismic oceanography can provide a two- or three-dimensional view of the water column thermocline structure at a vertical and horizontal resolution from the multi-channel seismic dataset. Several seismic imaging methods and techniques for seismic oceanography have been presented in previous research. In this study, we suggest a new formulation of the frequency-domain reverse-time migration method for seismic oceanography based on the analytic Green's function. For imaging thermocline structures in the water column from the seismic data, our proposed seismic reverse-time migration method uses the analytic Green's function for numerically calculating the forward- and backward-modeled wavefield rather than the wave propagation modeling in the conventional algorithm. The frequency-domain reverse-time migration with analytic Green's function does not require significant computational memory, resources, or a multifrontal direct solver to calculate the migration seismic images as like conventional reverse-time migration. The analytic Green's function in our reverse-time method makes it possible to provide a high-resolution seismic water column image with a meter-scale grid size, consisting of full-band frequency components for a modest cost and in a low-memory environment for computation. Our method was applied to multi-channel seismic data acquired in the Arctic Ocean and successfully constructed water column seismic images containing the oceanographic reflections caused by thermocline structures of the water mass. From the numerical test, we note that the oceanographic reflections of the migrated seismic images reflected the distribution of Arctic waters in a shallow depth and showed good correspondence with the anomalies of measured temperatures and calculated reflection coefficients from each XCDT profile. Our proposed method has been verified for field data application and accuracy of imaging performance.

Vertical distribution of microplastics in a river water column using an innovative sampling method.

Due to limitations of sampling methods, subsurface water is usually a less well-investigated compartment of the water column when scientists assess microplastic contamination. In this study, microplastic (MP) contamination was assessed in a freshwater river both in surface and subsurface using an innovative sampling method. Microplastic contamination in the lower part of the water column, i.e., near-bottom water and in sediments, was also studied. Three sampling campaigns were carried out during different weather conditions: stormy, rainy, and dry in order to observe their influence on the microplastics vertical distribution. No significant difference was observed between the abundance and types of MPs in surface and subsurface water. The proportion of polymer with theoretical density < 1 (polypropylene d = 0.9, polyethylene d = 0.91-0.95) and polystyrene (d = 0.1-1.06) in the surface and subsurface samples was 73.5%, and this proportion drops to 40.8% for the samples located in the near-bottom water and the sediments. Our results indicate that the MP concentration of the different compartments analyzed can be significantly influenced by rainfall during and prior to the sampling day. This study highlights that in shallow rivers, surface water sampling is representative of the water column MP contamination, but that sampling without taking environmental conditions into account may lead to erroneous estimation of MPs concentration and flux entering the marine environment.

Large quantities of small microplastics permeate the surface ocean to abyssal depths in the South Atlantic Gyre.

Hundreds of studies have surveyed plastic debris in surface ocean gyre and convergence zones, however, comprehensive microplastics (MPs, ≤5 mm) assessments beneath these surface accumulation areas are lacking. Using in situ high-volume filtration, Manta net and MultiNet sampling, combined with micro-Fourier-transform-infrared imaging, we discovered a high abundance (up to 244.3 pieces per cubic meter [n m-3 ]) of small microplastics (SMPs, characteristically <100 µm) from the surface to near-sea floor waters of the remote South Atlantic Subtropical Gyre. Large horizontal and vertical variations in the abundances of SMP were observed, displaying inverse vertical trends in some cases. SMP abundances in pump samples were more than two orders of magnitude higher than large microplastics (LMPs, >300 µm) concurrently collected in MultiNet samples. Higher-density polymers (e.g., alkyd resins and polyamide) comprised >65% of the total pump sample count, highlighting a discrepancy between polymer compositions from previous ocean surface-based surveys, typically dominated by buoyant polymers such as polyethylene and polypropylene. Contrary to previous reports stating LMP preferentially accumulated at density gradients, SMP with presumably slower sinking rates are much less influenced by density gradients, thus resulting in a more even vertical distribution in the water column, and potentially longer residence times. Overall, our findings suggest that SMP is a critical and largely underexplored constituent of the oceanic plastic inventory. Additionally, our data support that weak current systems contribute to the formation of SMP hotspots at depth, implying a higher encounter rate for subsurface particle feeders. Our study unveils the prevalence of plastics in the entire water column, highlighting the urgency for more quantification of the deep-ocean MP, particularly the smaller size fraction, to better understand ecosystem exposure and to predict MP fate and impacts.

Accumulation of organochlorine pesticide (OCP) residues in surface water and sediment from the Iznik Lake in Turkey.

This study was carried out to evaluate organochlorinated pesticide (OCPs) concentrations in the water column and sediments of Iznik Lake. Water samples and sediment were collected in different regions (six sampling sites) of the lake between January and December 2019 and tested for OCPs by gas chromatography-mass spectrometry (GC-MS). The results revealed that OCP residues throughout the sites varied depending on the anthropogenic activities of the region. OCPs detected in surface waters ranged from 0.01 to 60.80 µg/L and sediments from 0.06 to 14.21 ng/g dw. Endrin ketone, endrin aldehyde, endosulfan II, endrin, heptachlor epoxy, beta-BHC, gamma-BHC, ppDDD, and ppDDT concentrations exceeded the maximum residue limits indicated by the World Health Organization (WHO) for surface waters. Of the 18 analyzed OCP components, 17 were detected in sediment samples, and it was noted that they reached the highest concentration in summer. The presence of relatively high OCP levels according to WHO regulations in the waters of Iznik Lake, around which agricultural activities have been increasing rapidly in recent years, is a serious concern, and therefore, appropriate actions should be taken into consideration by the regulatory authorities.

Semi-Automated Data Processing and Semi-Supervised Machine Learning for the Detection and Classification of Water-Column Fish Schools and Gas Seeps with a Multibeam Echosounder.

Multibeam echosounders are widely used for 3D bathymetric mapping, and increasingly for water column studies. However, they rapidly collect huge volumes of data, which poses a challenge for water column data processing that is often still manual and time-consuming, or affected by low efficiency and high false detection rates if automated. This research describes a comprehensive and reproducible workflow that improves efficiency and reliability of target detection and classification, by calculating metrics for target cross-sections using a commercial software before feeding into a feature-based semi-supervised machine learning framework. The method is tested with data collected from an uncalibrated multibeam echosounder around an offshore gas platform in the Adriatic Sea. It resulted in more-efficient target detection, and, although uncertainties regarding user labelled training data need to be underlined, an accuracy of 98% in target classification was reached by using a final pre-trained stacking ensemble model.

An Experimental Study on Condition Diagnosis for Thrust Bearings in Oscillating Water Column Type Wave Power Systems.

In order to utilize wave energy, various wave power systems are being actively researched and developed and interest in them is increasing. To maximize the operational efficiency, it is very important to monitor and maintain the fault of components of the system. In recent years, interest in the management cost, high reliability and facility utilization of such systems has increased. In this regard, fault diagnosis technology including fault factor analysis and fault reproduction is drawing attention as an important main technology. Therefore, in this study, to reproduce and monitor the faults of a wave power system, firstly, the failure mode of the system was analyzed using FMEA analysis. Secondly, according to the derived failure mode and effect, the thrust bearing was selected as a target for fault reproduction and a test equipment bench was constructed. Finally, with the vibration data obtained by conducting the tests, the vibration spectrum was analyzed to extract the features of the data for each operating status; the data was classified by applying the three machine learning algorithms: naïve Bayes (NB), k-nearest neighbor (k-NN), and multi-layer perceptron (MLP). The criteria for determining the fault were derived. It is estimated that a more efficient fault diagnosis is possible by using the standard and fault monitoring method of this study.

Pesticide Mixtures in the Water-Column Versus Bottom-Sediments of Prairie Rivers.

River water-column and bottom-sediments samples were screened for 160 pesticide compounds to compare the types of pesticides present in the water-column versus bottom-sediments, and between segments of rivers flowing through intensively-managed versus semi-natural habitats. Of the 35 pesticide compounds detected, current-use pesticides accounted for 96% (water) and 76% (bottom sediments). Pesticide mixtures were present in 72% (water) and 51% (sediment) of the total samples. Only the river flowing through the most intensively managed habitat showed a wide range of pesticides in sediments, and many of these pesticides were also present in the water-column of that river. Current-use fungicides were detected in both the water-column and bottom-sediments but not in samples taken from rivers flowing predominantly through semi-natural habitats. The study period (May to August) corresponds to the peak time of regional pesticide applications and hence the time period that is most likely to show elevated concentrations of current-use pesticides in the water-column. The environmental concentrations of pesticide mixtures detected in the water-column were used to calculate Pesticide Toxicity Index (PTI) values as it applies to non-vascular or vascular plants, invertebrates, and fish. The PTI values were largest for non-vascular and vascular plants, reflecting that the pesticide mixtures in water-column were dominated by herbicides.

ANN-Based Airflow Control for an Oscillating Water Column Using Surface Elevation Measurements.

Oscillating water column (OWC) plants face power generation limitations due to the stalling phenomenon. This behavior can be avoided by an airflow control strategy that can anticipate the incoming peak waves and reduce its airflow velocity within the turbine duct. In this sense, this work aims to use the power of artificial neural networks (ANN) to recognize the different incoming waves in order to distinguish the strong waves that provoke the stalling behavior and generate a suitable airflow speed reference for the airflow control scheme. The ANN is, therefore, trained using real surface elevation measurements of the waves. The ANN-based airflow control will control an air valve in the capture chamber to adjust the airflow speed as required. A comparative study has been carried out to compare the ANN-based airflow control to the uncontrolled OWC system in different sea conditions. Also, another study has been carried out using real measured wave input data and generated power of the NEREIDA wave power plant. Results show the effectiveness of the proposed ANN airflow control against the uncontrolled case ensuring power generation improvement.

Numerical investigation of parametric resonance due to hydrodynamic coupling in a realistic wave energy converter.

Representative models of the nonlinear behavior of floating platforms are essential for their successful design, especially in the emerging field of wave energy conversion where nonlinear dynamics can have substantially detrimental effects on the converter efficiency. The spar buoy, commonly used for deep-water drilling, oil and natural gas extraction and storage, as well as offshore wind and wave energy generation, is known to be prone to experience parametric resonance. In the vast majority of cases, parametric resonance is studied by means of simplified analytical models, considering only two degrees of freedom (DoFs) of archetypical geometries, while neglecting collateral complexity of ancillary systems. On the contrary, this paper implements a representative 7-DoF nonlinear hydrodynamic model of the full complexity of a realistic spar buoy wave energy converter, which is used to verify the likelihood of parametric instability, quantify the severity of the parametrically excited response and evaluate its consequences on power conversion efficiency. It is found that the numerical model agrees with expected conditions for parametric instability from simplified analytical models. The model is then used as a design tool to determine the best ballast configuration, limiting detrimental effects of parametric resonance while maximizing power conversion efficiency.

Effect of intermittent aeration mode on nitrogen concentration in the water column and sediment pore water of aquaculture ponds.

Nitrogen in pond sediments is a major water quality concern and can impact the productivity of aquaculture. Dissolved oxygen is an important factor for improving water quality and boosting fish growth in aquaculture ponds, and plays an important role in the conversion of ammonium-nitrogen (NH4+-N) to nitrite-nitrogen (NO2--N) and eventually nitrate-nitrogen (NO3--N). A central goal of the study was to identify the best aeration method and strategy for improving water quality in aquaculture ponds. We conducted an experiment with six tanks, each with a different aeration mode to simulate the behavior of aquaculture ponds. The results show that a 36 hr aeration interval (Tc = 36 hr: 36 hr) and no aeration resulted in high concentrations of NH4+-N in the water column. Using a 12 hr interval time (Tc = 12 hr: 12 hr) resulted in higher NO2--N and NO3--N concentrations than any other aeration mode. Results from an 8 hr interval time (Tc = 8 hr: 8 hr) and 24 hr interval time (Tc = 24 hr: 24 hr) were comparable with those of continuous aeration, and had the benefit of being in use for only half of the time, consequently reducing energy consumption.

Bacterial Communities in Areas of Oil and Methane Seeps in Pelagic of Lake Baikal.

We have assessed the diversity of bacteria near oil-methane (area I) and methane (area II) seeps in the pelagic zone of Lake Baikal using massive parallel sequencing of 16S rRNA, pmoA, and mxaF gene fragments amplified from total DNA. At depths from the surface to 100 m, sequences belonging to Cyanobacteria dominated. In the communities to a depth of 200 m of the studied areas, Proteobacteria dominated the deeper layers of the water column. Alphaproteobacteria sequences were predominant in the community near the oil-methane seep, while the community near the methane seep was characterized by the prevalence of Alpha- and Gammaproteobacteria. Among representatives of these classes, type I methanotrophs prevailed in the 16S rRNA gene libraries from the near-bottom area, and type II methanotrophs were detected in minor quantities at different depths. In the analysis of the libraries of the pmoA and mxaF functional genes, we observed the different taxonomic composition of methanotrophic bacteria in the surface and deep layers of the water column. All pmoA sequences from area I were type II methanotrophs and were detected at a depth of 300 m, while sequences of type I methanotrophs were the most abundant in deep layers of the water column of area II. All mxaF gene sequences belonged to Methylobacterium representatives. Based on comparative analyses of 16S rRNA, pmoA, and mxaF gene fragment libraries, we suggest that there must be a wider spectrum of functional genes facilitating methane oxidation that were not detected with the primers used.

Isoprenoid Quinones Resolve the Stratification of Redox Processes in a Biogeochemical Continuum from the Photic Zone to Deep Anoxic Sediments of the Black Sea.

The stratified water column of the Black Sea serves as a model ecosystem for studying the interactions of microorganisms with major biogeochemical cycles. Here, we provide detailed analysis of isoprenoid quinones to study microbial redox processes in the ocean. In a continuum from the photic zone through the chemocline into deep anoxic sediments of the southern Black Sea, diagnostic quinones and inorganic geochemical parameters indicate niche segregation between redox processes and corresponding shifts in microbial community composition. Quinones specific for oxygenic photosynthesis and aerobic respiration dominate oxic waters, while quinones associated with thaumarchaeal ammonia oxidation and bacterial methanotrophy, respectively, dominate a narrow interval in suboxic waters. Quinone distributions indicate highest metabolic diversity within the anoxic zone, with anoxygenic photosynthesis being a major process in its photic layer. In the dark anoxic layer, quinone profiles indicate the occurrence of bacterial sulfur and nitrogen cycling, archaeal methanogenesis, and archaeal methanotrophy. Multiple novel ubiquinone isomers, possibly originating from unidentified intra-aerobic anaerobes, occur in this zone. The respiration modes found in the anoxic zone continue into shallow subsurface sediments, but quinone abundances rapidly decrease within the upper 50 cm below the sea floor, reflecting the transition to lower energy availability. In the deep subseafloor sediments, quinone distributions and geochemical profiles indicate archaeal methanogenesis/methanotrophy and potentially bacterial fermentative metabolisms. We observed that sedimentary quinone distributions track lithology, which supports prior hypotheses that deep biosphere community composition and metabolisms are determined by environmental conditions during sediment deposition.IMPORTANCE Microorganisms play crucial roles in global biogeochemical cycles, yet we have only a fragmentary understanding of the diversity of microorganisms and their metabolisms, as the majority remains uncultured. Thus, culture-independent approaches are critical for determining microbial diversity and active metabolic processes. In order to resolve the stratification of microbial communities in the Black Sea, we comprehensively analyzed redox process-specific isoprenoid quinone biomarkers in a unique continuous record from the photic zone through the chemocline into anoxic subsurface sediments. We describe an unprecedented quinone diversity that allowed us to detect distinct biogeochemical processes, including oxygenic photosynthesis, archaeal ammonia oxidation, aerobic methanotrophy, and anoxygenic photosynthesis in defined geochemical zones.

An Improved Quadrilateral Fitting Algorithm for the Water Column Contribution in Airborne Bathymetric Lidar Waveforms.

In this paper, an improved method based on a mixture of Gaussian and quadrilateral functions is presented to process airborne bathymetric LiDAR waveforms. In the presented method, the LiDAR waveform is fitted to a combination of three functions: one Gaussian function for the water surface contribution, another Gaussian function for the water bottom contribution, and a new quadrilateral function to fit the water column contribution. The proposed method was tested on a simulated dataset and a real dataset, with the focus being mainly on the performance of retrieving bottom response and water depths. We also investigated the influence of the parameter settings on the accuracy of the bathymetry estimates. The results demonstrate that the improved quadrilateral fitting algorithm shows a superior performance in terms of low RMSE and a high detection rate in the water depth and magnitude retrieval. What's more, compared with the use of a triangular function or the existing quadrilateral function to fit the water column contribution, the presented method retrieved the least noise and the least number of unidentified waveforms, showed the best performance in fitting the return waveforms, and had consistent fitting goodness for all different water depths.