Deep-sea Regions Research Articles

Metagenomic analysis of deep-sea bacterial communities in the Makassar and Lombok Straits

The extreme conditions of the deep-sea environment, including limited light, low oxygen levels, high pressure, and nutrient scarcity, create a natural habitat for deep-sea bacteria. These remarkable microorganisms have developed unique strategies to survive and adapt to their surroundings. However, research on the diversity of deep-sea bacteria, both culture-dependent and culture-independent, in Indonesian waters remains insufficient. This study focused on exploring the biodiversity of deep-sea bacteria, specifically in the Makassar and Lombok Strait, the main Indonesian throughflow pathway characterized by relatively fertile water, which serves as an important deep-sea region. High-throughput DNA sequencing of full-length 16S rRNA was employed to construct a genomic database. The results of the bioinformatic analysis revealed that two stations, 48 and 50 (Makassar Strait), exhibited a more similar community structure of deep-sea bacteria than did station 33 (Lombok Strait). Among the predominant phyla found at a depth of 1000 m, the top ten were Proteobacteria, Firmicutes, Bacteroidetes, Actinobacteria, Planctomycetes, Acidobacteria, Nitrospinae, Verrucomicrobia, Candidatus Melainabacteria, and Cyanobacteria. Furthermore, the genera Colwellia, Moritella, Candidatus Pelagibacter, Alteromonas, and Psychrobacter consistently appeared at all three stations, albeit with varying relative abundance values. These bacterial genera share common characteristics, such as psychrophilic, halophilic, and piezophilic tendencies, and are commonly found in deep-sea ecosystem. The environmental conditions at a depth of 1000 m were relatively stable, with an average pressure 10 MPa, temperature 4.68 °C, salinity 34.58 PSU, pH 8.06, chlorophyll-a 0.29 µg/L, nitrate 3.19 µmol/L, phosphate 6.32 µmol/L and dissolved oxygen (DO) 2.90 mg/L. The bacterial community structures at the three sampling stations located at the same depth (1000 m) exhibited similarities, as indicated by the closely aligned similarity index values.

Plastic-Degrading Enzymes from Marine Microorganisms and Their Potential Value in Recycling Technologies.

Since the 2005 discovery of the first enzyme capable of depolymerizing polyethylene terephthalate (PET), an aromatic polyester once thought to be enzymatically inert, extensive research has been undertaken to identify and engineer new biocatalysts for plastic degradation. This effort was directed toward developing efficient enzymatic recycling technologies that could overcome the limitations of mechanical and chemical methods. These enzymes are versatile molecules obtained from microorganisms living in various environments, including soil, compost, surface seawater, and extreme habitats such as hot springs, hydrothermal vents, deep-sea regions, and Antarctic seawater. Among various plastics, PET and polylactic acid (PLA) have been the primary focus of enzymatic depolymerization research, greatly enhancing our knowledge of enzymes that degrade these specific polymers. They often display unique catalytic properties that reflect their particular ecological niches. This review explores recent advancements in marine-derived enzymes that can depolymerize synthetic plastic polymers, emphasizing their structural and functional features that influence the efficiency of these catalysts in biorecycling processes. Current status and future perspectives of enzymatic plastic depolymerization are also discussed, with a focus on the underexplored marine enzymatic resources.

Ship detection in reefs and deep-sea with medium-high resolution images

ABSTRACT Accurate and efficient ship detection is crucial for ocean monitoring and management, especially in reefs and deep-sea, where fishing and illegal activities threaten sustainability of ecosystems. Obtaining the size of ships in reefs and deep-sea helps to identify ship types and to assess the impact of ships on marine ecosystems quantitatively. Ship detections were mainly applied at coast or river of the inland region using high spatial resolution remote sensing data due to its rich details and frequent coverage. However, the ships located in reefs and deep-sea regions were rarely studied because of price, and availability of high spatial resolution remote sensing data. Global covered medium-high resolution (10–30 m) remote sensing data (such as Sentinel-2) makes it possible to obtain the spatial-temporal distribution of ships, especially small ships. This study developed a deep learning ship detection algorithm – an enhanced Rotated-Ship Detector (RShipDet) to detect ships in reefs and deep-sea regions. RShipDet was applied to Nansha Islands based on two medium-high resolution ship detection datasets (Sentinel2-Ship and SDGSAT-Ship). These two datasets include various backgrounds of reefs and deep-sea, and complex scenarios such as cloud cover and parallel ships, adapting RShipDet to ship detection under complex circumstances in reefs and deep-sea. The results showed that: (1) Small gains: gains of 3.3% and 8.7% Average-Precision (AP) compared to Rotation-equivariant Detector (ReDet) and Faster-RCNN on Sentinel2-Ship dataset; (2) Strong generalization capabilities: 77.4% AP on SDGSAT-Ship dataset; (3) Better performance under complex conditions: RShipDet obtained more accurate ship detection results over regions with cloud cover, islands and reefs, deep-sea, and ports compared to other classical detectors. Our algorithm could be applied for better management of ocean resources and activities in reefs and deep-sea.

Research on seamount substrate classification method based on machine learning

The western Pacific seamount area is abundant in both biological and mineral resources, making it a crucial location for international investigation of regional seabed resources. An essential stage in comprehending and advancing seamounts is gaining knowledge about the distribution characteristics and laws governing the seabed substrate. Deep-sea geological sampling is challenging because of the intricate nature of the deep-sea environment, resulting in increased difficulty in identifying and evaluating substrates. This study addresses the aforementioned issues by utilizing in-situ video footage obtained from the “Jiaolong” manned deep submersible and shipborne deep-water multibeam data. This data is used as a foundation for constructing a Western Pacific seamount areas substrate classification point set. Additionally, the paper introduces the mRMR-XGBoost substrate classification model. Substrate categorization in deep sea and mountainous regions has been successfully accomplished, yielding a classification accuracy of 92.5%. The classification experiments and box sampling results demonstrate that the mRMR-XGBoost substrate classification model proposed in this paper can efficiently use acoustic and optical data to accurately divide the substrate types in seamount areas, with better classification accuracy, when compared with commonly used machine learning models. It has a significant application value and the best classification effect on the two types of substrates: nodules and gravel substrates.

Assessing the strength of deep-sea surface ultrasoft sediments with T-bar penetration: A machine learning approach

With the expansion of marine resource utilization, geological disaster prediction, and ecological protection in deep-sea regions, accurate identification of deep-sea engineering geological environments has become paramount, highlighting the significance of understanding the mechanical characteristics of deep-sea surface ultrasoft sediments (DSUSs). However, DSUSs typically exhibit low strength, high compressibility, and significant fluidity, making sampling for indoor strength testing a challenging task. On-site testing employing a T-bar penetrometer has become increasingly prominent for assessing DSUS strength, but the complexity of influencing parameters limits the application of this valuable method. This study utilizes a validated computational fluid dynamics (CFD) approach to model the complete process of T-bar penetration into a DSUS. The aim is to understand the quantitative effects and corresponding mechanisms of various significant complex parameters, including the undrained shear strength, dimensionless penetration depth, rate effect, and interface contact condition, on the dimensionless penetration resistance coefficient. Additionally, a machine learning model based on the random forest algorithm is introduced to establish a multiparameter evaluation method for the dimensionless penetration resistance coefficient. The findings illuminate the intricate interactions and effective evaluation of these factors when evaluating DSUS strength using a T-bar penetrometer, addressing the above challenges in marine engineering geology and the environment.

Deep-sea mining rock-fragment dispersal scenarios associated with submesoscale forcings: A case study in the Atlantic

In the last few years, the exploitation of deep-sea regions for minerals extraction raised international attention as an economically viable source for the mining industry. However, most of these minerals are found close to sensitive ecosystems that can be harmed by mining activities. Given the potential impact, there is a need for the establishment of best practices towards the adoption of preventive strategies for the sustainable management and exploitation of deep-sea environments. To accomplish this objective, numerical models have proven to be reliable tools to support decision-making. In the present study, a high-resolution eddy-resolving ocean numerical model was configured and integrated with a semi-Lagrangian model aiming to map the transport of rock-fragments associated with mining activities. The model was applied to an area rich in polymetallic sulphides at the Northern Mid-Atlantic Ridge (NMAR). Model results showed that local topography and circulation dynamics played an important role for the dispersion and settling of the rock-fragments. In the presence of local submesoscale processes, the residence time do not follow the neutral relation H/vs. It was demonstrated that, depending on the local hydrodynamics, rock-fragments released at sub-surface depth can impact wider areas, with a predicted impact on pelagic and benthic organisms.

Does the microplastics ingestion patterns and polymer composition vary across the oceanic zones? A case study from the Indian coast

This study explores microplastic (MP) presence in the gastrointestinal tracts of deep-sea fish from the Central Indian Ocean, off the Indian coast. Among the 27 species examined, 19 showed MP contamination, averaging 2.68 ± 0.30 (±SE) MPs per individual. Polymer analysis via FTIR and micro-Raman identified several types, including polyethylene terephthalate (PET), polyvinyl alcohol (PVA), polypropelene (PP), polyvinyl acetate (PVC), polyurethane (PU), polytetrafluoroethylene (PTFE), polyaniline (PANI), polymethyl methacrylate (PMMA), and polyethersulfone (PES), with PET being the most prevalent (33.33 %). MP ingestion was higher in benthopelagic fish and those at higher trophic levels, as indicated by comparisons across oceanic zones. Niche partitioning analysis suggests feeding behaviour as a primary influencer of MP ingestion in deep-sea fish rather than habitat or trophic level. The study proposes the potential use of deep-sea fish as indicators for assessing microplastic pollution across oceanic zones and deep-sea regions through bycatch monitoring.

Strong linkage between benthic oxygen uptake and bacterial tetraether lipids in deep-sea trench regions

Oxygen in marine sediments regulates many key biogeochemical processes, playing a crucial role in shaping Earth’s climate and benthic ecosystems. In this context, branched glycerol dialkyl glycerol tetraethers (brGDGTs), essential biomarkers in paleoenvironmental research, exhibit an as-yet-unresolved association with sediment oxygen conditions. Here, we investigated brGDGTs in sediments from three deep-sea regions (4045 to 10,100 m water depth) dominated by three respective trench systems and integrated the results with in situ oxygen microprofile data. Our results demonstrate robust correlations between diffusive oxygen uptake (DOU) obtained from microprofiles and brGDGT methylation and isomerization degrees, indicating their primary production within sediments and their strong linkage with microbial diagenetic activity. We establish a quantitative relationship between the Isomerization and Methylation index of Branched Tetraethers (IMBT) and DOU, suggesting its potential validity across deep-sea environments. Increased brGDGT methylation and isomerization likely enhance the fitness of source organisms in deep-sea habitats. Our study positions brGDGTs as a promising tool for quantifying benthic DOU in deep-sea settings, where DOU is a key metric for assessing sedimentary organic carbon degradation and microbial activity.

The Probability of Ship Collision during the Fully Submerged Towing Process of Floating Offshore Wind Turbines

As global warming intensifies, the development of offshore wind farms is swiftly progressing, especially deep-water Floating Offshore Wind Turbines (FOWTs) capable of energy capture in deep-sea regions, which have emerged as a focal point of both academic and industrial interest. Although numerous researchers have conducted comprehensive and multifaceted studies on various components of wind turbines, less attention has been paid to the operational stage responses of FOWTs to wind, waves, and currents and the reliability of their structural components. This study primarily employs a theoretical analysis to establish mathematical models under a series of reasonable assumptions, examining the possibility of collisions between FOWT transport fleets and other vessels in the passage area during the towing process. Using the model, this paper takes the Wanning Floating Offshore Wind Farm (FOWF) project, which is scheduled to be deployed in the South China Sea, as its research object and calculates the probability of collisions between FOWTs and other vessels in three months from the pier near Wanning, Hainan, to a predetermined position 22 km away. The findings of the analysis indicate that the mathematical model developed in this study integrates the quantities and velocities of navigational vessels within the target maritime area as well as the speeds, routes, and schedules of the FOWT transport fleet. By employing statistical techniques and geometric calculations, the model can determine the frequency of collisions between various types of vessels and the FOWT transport fleet during the transportation period. This has substantial relevance for future risk assessments and disaster prevention and mitigation measures in the context of FOWT transportation.

Environmental DNA metabarcoding of foraminifera for biological monitoring of bottom water and sediments on the Takuyo-Daigo Seamount in the northwestern Pacific

Foraminifera are adapted to a wide range of environments, and environmental DNA (eDNA) metabarcoding of foraminifera should facilitate development of new environmental indicators. In this study, we used eDNA metabarcoding to evaluate the discrepancy between planktic and benthic foraminifera molecular communities identified in bottom water and short sediment cores. The molecular community was compared to foraminiferal shells in sediment traps set on the seafloor. Samples were collected in June and August around the Takuyo-Daigo Seamount in the western subtropical Pacific Ocean. Approximately 40% of amplicon sequence variants (ASVs) pertained to unknown foraminiferal lineages in sediment samples, compared with only 22% in bottom water. Bottom water contained benthic foraminifera and taxonomically unassigned lineages, which were attributed to resuspended particles. In bottom water, 100 ASVs were assigned to planktic foraminifera. ASVs assigned to Candeina nitida were most abundant and accounted for 36%–86% of planktic foraminiferal ASVs. In sedimentary DNA, Globigerinita glutinata was the most abundant among 33 ASVs of planktic foraminifera. However, transparent shells in sediment traps contained more spinose species, such as Globigerinoides ruber, whereas C. nitida was not found and few G. glutinata were detected. This discrepancy between the three samples may be due to the species-specific preservation, to polymerase chain reaction biases, and/or to low abundance of planktic foraminifers. In sedimentary DNA, 893 ASVs were assigned to high-level foraminiferal taxa. Among benthic foraminiferal lineages, monothalamids were most abundant, as reported in other deep-sea regions. Molecular communities formed one cluster above the boundary at which ASVs sharply decrease across the three cores. Our results suggest that depth within the sediment core can affect foraminiferal ASVs, but the distance between sites up to 200 m did not strongly affect ASVs of sedimentary DNA at least above the boundary at which ASVs sharply decrease. Sequences of foraminiferal DNA in sediment decreased linearly in core PC02-A1, but exponentially in core PC03-B3. The decline of foraminiferal ASVs may reflect both the decreases in numbers of living foraminifera and degradation of DNA in sediment, related to the particle mixing depth.

The Recent Progresses of Electrodes and Electrolysers for Seawater Electrolysis

The utilization of renewable energy for hydrogen production presents a promising pathway towards achieving carbon neutrality in energy consumption. Water electrolysis, utilizing pure water, has proven to be a robust technology for clean hydrogen production. Recently, seawater electrolysis has emerged as an attractive alternative due to the limitations of deep-sea regions imposed by the transmission capacity of long-distance undersea cables. However, seawater electrolysis faces several challenges, including the slow kinetics of the oxygen evolution reaction (OER), the competing chlorine evolution reaction (CER) processes, electrode degradation caused by chloride ions, and the formation of precipitates on the cathode. The electrode and catalyst materials are corroded by the Cl− under long-term operations. Numerous efforts have been made to address these issues arising from impurities in the seawater. This review focuses on recent progress in developing high-performance electrodes and electrolyser designs for efficient seawater electrolysis. Its aim is to provide a systematic and insightful introduction and discussion on seawater electrolysers and electrodes with the hope of promoting the utilization of offshore renewable energy sources through seawater electrolysis.

Late Miocene to Early Pliocene benthic foraminifera from the Tasman Sea (International Ocean Discovery Program Site U1506)

Abstract. Modern and fossil benthic foraminifera have been widely documented from New Zealand, but detailed studies of material collected from drilling expeditions in the Tasman Sea are scarcer. This study aims to provide an updated taxonomic study for the Late Miocene–Early Pliocene benthic foraminifera in the Tasman Sea, with a specific focus on the paleoceanographic phenomenon known as the Biogenic Bloom. To achieve these goals, we analysed 66 samples from International Ocean Discovery Program (IODP) Site U1506 located in the Tasman Sea and identified a total of 98 taxa. Benthic foraminifera exhibit good preservation, allowing for accurate taxonomic identification. The resulting dataset serves as a reliable and precise framework for the identification and classification of the common deep-water benthic foraminifera in the region. The paleobathymetric analysis based on depth-dependent species indicates deposition at lower bathyal depths. Additionally, the quantitative analysis of the benthic foraminiferal assemblages allowed us to explore their response to the Biogenic Bloom at Site U1506. The paleoenvironmental analysis, focused on the Early Pliocene part of the Biogenic Bloom, points to high-productivity conditions driven by phytoplankton blooms and intensified vertical mixing of the ocean waters. These results provide valuable insights into the paleoceanographic events in the Tasman Sea, particularly the Biogenic Bloom, highlighting the significance of benthic foraminifera as reliable proxies for deciphering paleoenvironmental conditions. The taxonomic identifications and paleoenvironmental interpretations presented herein will aid in future paleoceanographic studies and facilitate comparisons with other deep-sea regions.

Investigating the effectiveness of deep cement mixing in deep sea: A static load testing case study

This research demonstrated a marine reclamation project in Hong Kong's deep-sea region, which employed the economically efficient and environmentally sustainable deep cement mixing (DCM) clusters for the reconstitution of marine sediments. This study offers a detailed introduction to the installation of DCM clusters and the conduction of subsequent static loading tests, providing experiences for forthcoming endeavors in marine reclamation, particularly in regions akin to Hong Kong. To ensure that both compressions and lateral movements do not exceed the acceptance criteria, the finite element method (FEM) was employed to navigate the construction of DCM clusters effectively. Subsequently, static load tests were conducted, with meticulous measurement of compressions and lateral movements. The results show that the maximum vertical compression and lateral movements are approximately 4 mm and 10.8 mm, respectively, which are significantly beneath the corresponding acceptance criteria (i.e., 40 mm and 60 mm for vertical and lateral movements). A comparison between field measurement outcomes and simulation results supported the capability of FEM in identifying the crucial movement characteristics of DCM clusters, albeit a discernible discrepancy, predominantly being attributed to the conservative parameters utilized in the FEM model as per existing specifications. This delineation underscores the imperative need for the development of region-specific guidelines.

Geochemical evaluation of cosmic spherules collected from the Central Indian Ocean Basin

Micrometeorites (MMs) significantly contribute to the extraterrestrial material the Earth receives and represent a broader range of precursors than known meteorites. Low sedimentation rates prevalent in the deep-sea regions far away from land provide a unique opportunity for collecting MMs from these least disturbed regions. In the present study, we have studied 305 cosmic spherules recovered from the Central Indian Ocean Basin (CIOB); that have undergone melting during hypervelocity entry into the Earth's atmosphere. During the atmospheric entry, primary signatures of MMs are lost depending upon the extent of heating, complicating the identification of the parent body. Nevertheless, we have tried to relate these cosmic spherules to their respective parent bodies based on elemental ratios present in them, considering atmospheric ablative losses of various elements. The chemical analyses indicate that many deep-sea cosmic spherules are linked to carbonaceous chondrites. Around 239 porphyritic olivines (PO), 42 relict olivines are studied for their textural development and composition during recrystallisation during atmospheric entry. Thirty-zoned olivines are analysed from rim to core to understand various elements behaviour during atmospheric entry. Seawater plays a vital role in eroding these cosmic spherules material, and its effect is also discussed. As most of the recent micrometeorite collections focus on the polar region, these deep-sea spherules will significantly add to the information about the extraterrestrial matter reaching the Earth.

Experimental investigation of the current induced local scour around a jacket foundation

The jacket foundation is a complex superstructure and has been recently used in offshore wind farms in the deep-sea regions. As a relatively new foundation structure, there lack the relevant data, such as topographic field surveys and laboratory tests that can be used to optimize the engineering design of such structure. This study presents the experimental results to investigate sediment transport and scour evolution around the jacket foundation under the unidirectional flow actions. Experimental data are analyzed to evaluate the effects of flow strength, water depth and the foundation angle on the development characteristics of the local scour around each pile leg of the jacket foundation. The influences of the superstructure and pile legs on the local scour are investigated. The results of this study are expected to be useful for assessing the stability of the jacket foundation and proposing the subsequent protective measures for such offshore structure.

Application of Synthetic DINCAE–BME Spatiotemporal Interpolation Framework to Reconstruct Chlorophyll–a from Satellite Observations in the Arabian Sea

Chlorophyll–a (Chl–a) concentration is an indicator of phytoplankton pigment, which is associated with the health of marine ecosystems. A commonly used method for the determination of Chl–a is satellite remote sensing. However, due to cloud cover, sun glint and other issues, remote sensing data for Chl–a are always missing in large areas. We reconstructed the Chl–a data from MODIS and VIIRS in the Arabian Sea within the geographical range of 12–28° N and 56–76° E from 2020 to 2021 by combining the Data Interpolating Convolutional Auto–Encoder (DINCAE) and the Bayesian Maximum Entropy (BME) methods, which we named the DINCAE–BME framework. The hold–out validation method was used to assess the DINCAE–BME method’s performance. The root–mean–square–error (RMSE) and the mean–absolute–error (MAE) values for the hold–out cross–validation result obtained by the DINCAE–BME were 1.8824 mg m−3 and 0.4682 mg m−3, respectively; compared with in situ Chl–a data, the RMSE and MAE values for the DINCAE–BME–generated Chl–a product were 0.6196 mg m−3 and 0.3461 mg m−3, respectively. Moreover, DINCAE–BME exhibited better performance than the DINEOF and DINCAE methods. The spatial distribution of the Chl–a product showed that Chl–a values in the coastal region were the highest and the Chl–a values in the deep–sea regions were stable, while the Chl–a values in February and March were higher than in other months. Lastly, this study demonstrated the feasibility of combining the BME method and DINCAE.

Spatial-temporal characteristics of the oceanic bottom mixed layer in the South China Sea

The oceanic bottom mixed layer (BML) plays an important role in transporting mass, heat, and momentum between the ocean interior and the bottom boundary. However, the spatial-temporal characteristics of the BML in the South China Sea (SCS) is not well understood. Using 514 full-depth temperature and salinity profiles collected during the time period from 2004 to 2018 and two particularly deployed hydrographic moorings, the temporal and spatial variations of the BML have been analyzed. The results show that the BML in the SCS exhibits significant inhomogeneity, with thickness and stability varying across different regions. Specifically, the BML is relatively thin and stable over the continental shelf and deep-sea regions, while it is thicker and less stable over the northern continental slope. The mean, median, and one standard deviation values of BML thickness over the entire SCS were found to be 73 m, 56 m, and 55 m, respectively. Further analysis reveals that energetic high-frequency dynamic processes, coupled with steep bottom topography, contribute to strong tidal dissipation and vertical mixing near the bottom over the continental slope, resulting in thicker BMLs. Conversely, dynamic processes in the deep ocean are less energetic and low-frequency, the topography is relatively smooth, and tidal dissipation and bottom vertical mixing are weaker, leading to a thinner BML. These findings enhance our understanding of the BML dynamics in the SCS and other marginal seas and provide insights to improve parameterizations of physical processes in ocean models.

Estimation of 226Ra and 228Ra Content Using Various Types of Sorbents and Their Distribution in the Surface Layer of the Black Sea

Radium isotopes have traditionally been used as tracers of surface and underground fresh waters in land-ocean interactions. The concentration of these isotopes is most effective on sorbents containing mixed oxides of manganese. During the 116 RV Professor Vodyanitsky cruise (22 April-17 May 2021), a study about the possibility and efficiency of 226Ra and 228Ra recovery from seawater using various types of sorbents was conducted. The influence of seawater flow rate on the sorption of 226Ra and 228Ra isotopes was estimated. It was indicated that the Modix, DMM, PAN-MnO2, and CRM-Sr sorbents show the best sorption efficiency at a flow rate of 4-8 column volumes per minute. Additionally, the distribution of biogenic elements (dissolved inorganic phosphorus (DIP), silicic acid, and the sum of nitrates and nitrites), salinity, and 226Ra and 228Ra isotopes was studied in the surface layer of the Black Sea in April-May 2021. Correlation dependencies between the concentration of long-lived radium isotopes and salinity are defined for various areas of the Black Sea. Two processes control the dependence of radium isotope concentration on salinity: conservative mixing of riverine and marine end members and desorption of long-lived radium isotopes when river particulate matter meets saline seawater. Despite the high long-lived radium isotope concentration in freshwater in comparison with that in seawater, their content near the Caucasus shore is lower mainly because riverine waters meet with a great open seawater body with a low content of these radionuclides, and radium desorption processes take place in an offshore area. The 228Ra/226Ra ratio derived from our data displays freshwater inflow spreading over not only the coastal region, but also the deep-sea region. The lowered concentration of the main biogenic elements corresponds to high-temperature fields because of their intensive uptake by phytoplankton. Therefore, nutrients coupled with long-lived radium isotopes trace the hydrological and biogeochemical peculiarities of the studied region.

Widespread Occurrence and Transport of p-Phenylenediamines and Their Quinones in Sediments across Urban Rivers, Estuaries, Coasts, and Deep-Sea Regions.

p-Phenylenediamines (PPDs) are widely used as antioxidants in tire rubber, and their derived quinone transformation products (PPD-Qs) may pose a threat to marine ecosystems. A compelling example is N-(1,3-dimethylbutyl)-N'-phenyl-p-phenylenediamine (6PPD)-derived quinone, called 6PPD-Q, as the causal toxicant for stormwater-linked acute mortality toward coho salmon. However, the knowledge of the co-occurrences of PPDs and PPD-Qs and their transport from freshwater to oceanic waterbodies on a large geographical scale remains unknown. Herein, we performed the first large-scale survey of these chemicals in sediments across urban rivers, estuaries, coasts, and deep-sea regions. Our results demonstrated that seven PPDs and four PPD-Qs are ubiquitously present in riverine, estuarine, and coastal sediments, and most of them also occur in deep-sea sediments. The most dominant chemicals of concern were identified as 6PPD and 6PPD-Q. Total sedimentary concentrations of PPDs and PPD-Qs presented a clear spatial trend with decreasing levels from urban rivers (medians: 39.7 and 15.2 ng/g) to estuaries (14.0 and 5.85 ng/g) and then toward coasts (9.47 and 2.97 ng/g) and deep-sea regions (5.24 and 3.96 ng/g). Interestingly, spatial variation in the ratios of 6PPD to 6PPD-Q (R6PPD/6PPD-Q) also presented a clear decreasing trend. Our field measurements implied that riverine outflows of PPDs and PPD-Qs may be an important route to transport these tire rubber-derived chemicals to coastal and open oceans.

Trends in Changes in Primary Phytoplankton Production According to Remote Sensing Data in the Deep-Sea Region of the Black Sea for 1998–2015

The analysis of long-term seasonal changes in the concentration of chlorophyll, the maximum rate of phytoplankton photosynthesis and water temperature in the surface layer of the open waters Black Sea from 1998 to 2015 has been carried out. The trends of these indicators were assessed. For the research, we used the data of satellite observations SeaWiFS and MODIS-Aqua, MODIS-Terra. Typical positive temperature trends of 4 % in the deep-water western part of the sea. An annual temperature rise in deep-water areas was noted in the western cyclonic circulation by 0.038 °C. According to average annual data in other areas, no increase was found. The increase was mainly due to the winter season. Negative trends of primary phytoplankton production within 16.4–18.6 % of the initial level according to average annual values throughout the deep-water area. Significance level — p < 0.1. A decrease in primary production was observed in the summer. There were no statistically significant directional changes in chlorophyll concentration based on averaged data over 18 years. In different parts of the deep-sea area, the direction of interannual and seasonal changes in all indicators was similar. The emerging trend towards a decrease in phytoplankton productivity in recent years may lead to a restructuring of the phytoplankton community.