Oceanologia最新文献

Sixty morphospecies of Decapoda (Malacostraca: Crustacea) representing 34 families were recorded in the material collected in 2012 from 265 van Veen grab (0.1 m²) samples, from the nine transects distributed along the coast of Ghana in the 25–1000 m depth range. The examined material was dominated by the Diogenidae, Panopeidae, Leucosiidae, Pilumnidae and Xanthidae families. Species accumulation curves showed undersampling of the studied area and a large number of the morphospecies comprised singletons and doubletons. Panopeus africanus was the most frequent morphospecies in the analysed material (9.1% of all samples). We observed a substantial decrease of diversity (Shannon Index) and abundance along a depth gradient. Species richness also decreased with depth, starting from the highest number of morphospecies ‒ 38 at 25 m depth, then 33 at 50 m, 17 at 100 m, 11 at 250 m, 8 at 500 m and ending with 1 morphospecies at 1000 m bottom depth. Higher diversity was observed on the continental shelf (25–250 m – 57 morphospecies), while on the slope (500–1000 m) only eight morphospecies were recorded. Numerous factors of natural and anthropogenic origin may affect decapod communities on the coast of Ghana. Since our material was collected using a sampler collecting material at a very small scale, the observed patterns might be affected by the sampling method.

In this study, we investigated zooplankton composition and seasonal dynamics, as well as the influence of selected environmental factors on the zooplankton community in three ports on the Polish Baltic coast: Władysławowo, Gdynia and Gdańsk. Our aim was to determine whether harbours’ heavy traffic, chemical pollution and physical disturbances affect the zooplankton community, and whether new nonindigenous planktonic species occur in these habitats. Forty three zooplankton taxa were found in all three ports; however, it is important to note that no new nonindigenous species were observed in the port basins. The most influential environmental factors affecting the zooplankton community were: seawater temperature (17% of explained zooplankton variability) and transparency (4%), which were related to seasonal changes. Acartia spp. (although of different development stages) was the dominant taxon during the study, and the examined ports/seasons differed in the presence and proportions of less abundant taxa: the autumn and winter assemblages were dominated by Acartia spp. nauplii, the spring assemblage by numerous Polychaeta larvae, while Cirripedia nauplii and early development stages of Eurytemora affinis were particularly abundant in summer. In addition, changes in salinity (2% explained variability) had a particular impact on the zooplankton community and especially on the assemblage of Gdańsk Port, which was influenced by freshwater inflow from the Motława and Dead Vistula rivers. Our study has clearly shown that, despite severe physical and chemical disturbances in all studied ports, the composition and seasonal dynamics of the zooplankton community were similar to those of the Gulf of Gdańsk outside the ports.

Particle size distribution (PSD) and concentration of mineral-suspended sediment released from melting glaciers are important factors affecting the local marine ecosystem, e.g. affecting the light availability in water columns, thus changing underwater light climate for photosynthetic organisms. We examined the characteristics of various samples of natural mineral assemblages suspended in different glacial bays in Hornsund and Kongsfjord at Spitsbergen. The concentrations of the total mass of particles (TSM) in suspended sediment as well as particular organic matter (POM) and particular inorganic matter mass (PIM) together with mineralogical composition and particular size distribution (PSD) were determined.

In this study, we investigated the PSD properties and variability in the front of different tidewater glaciers based, laser diffractometer measurements (LISST-100x), and XRD – techniques to obtain the mineralogical composition of the particles. The sampled sites are under the strong influence of freshwater discharge from the glacier. At each station, inorganic particulate matter contributed up to 98% to total suspended matter with the particle concentration of the particle reaches up to 111 mg/l with mean surface PSD slopes ranging from 3.24 to 3.85. The result provides valuable baseline information on the observed range of variability of the size of suspended particles due to glacial runoff and the presence of particles of different mineral origin in the glacial bays.

Coastal upwelling along the SE Baltic Sea coast is a common feature, especially during the warm season. It significantly lowers sea surface temperature (SST) in the coastal areas, and, therefore, may be responsible for modifying meteorological conditions in those coastal areas, where upwelling is most frequently observed. This study aims to assess the effect of coastal upwelling on the air temperature at the south-eastern coast of the Baltic Sea based on long-term period observations (2002–2021) from coastal hydrometeorological stations and satellite data. Overall, our study revealed that due to its high frequency and spatial extent, upwelling is responsible for lowering the mean summer season SST of the SE Baltic Sea coast by about 1°C. And even though upwelling is a short-term event, upwelling-induced SST drop results in cooling air temperatures in the coastal areas, i.e., the mean air temperatures during upwelling are typically 2−4°C lower than before. It was also observed that upwelling is favouring the development of advective fog. Thus, sudden changes in meteorological parameters during upwelling can have versatile effects on various socio-economic activities. The results of this study contribute to the understanding of upwelling feedback onto the lower atmosphere and, therefore, are important for advancing the accuracy of weather forecasts that are needed for coastal communities, including marine and coastal industries.

The goal of this study is to describe wind wave climate and wave extremes of the Gulf of Gdańsk in the southern Baltic Sea and associated meteorological conditions over the Baltic Sea. We obtain the characteristic features of 34 severe historical storms in the Gulf of Gdańsk during the period 1958–2001 and link them with extreme significant wave heights hindcast for five grid points in this gulf. The long-term statistics of atmospheric pressure systems over central and northern Europe, and the north-eastern Atlantic Ocean are derived from a 44-year REMO reanalysis database. A link between the mean, minimum and variability range of atmospheric pressure has been quantified. In general, the higher the mean pressure the smaller its variability and vice versa. Long-term characteristic features of winds over the Baltic Sea have been estimated from the REMO database. Strong winds directions vary from W, WSW to SW in the southern Baltic to more southerly SSW directions in the northern part of the Baltic Sea. The Empirical Orthogonal Functions (EOF) analysis shows that more than 50% of the variability in the atmospheric pressure in the Baltic Sea can be explained by the first EOF mode. The first four EOF modes can reproduce above 90% variability of the hindcast pressure time series. Statistical properties of the hindcast significant wave height over the Gulf of Gdańsk are computed based on the 44-year HIPOCAS database. All the computed statistics of wave heights reveal a very strong sheltering effect caused by the Hel Peninsula.

The seasonal reversal of ocean circulation associated with seasonal change in the direction of prevailing winds and the occurrence of several anomalous events in the Eastern Equatorial Indian Ocean (EEIO) make this region dynamic and complex in terms of its biogeochemical characteristics. Two multidisciplinary cruises were conducted to measure nutrients and associated physicochemical parameters across the water column (up to 1000 m) of the EEIO during boreal summer and winter monsoons to understand the distribution of nutrients and their spatio-temporal variability from a biogeochemical perspective. The seasonality in the thermohaline structure of the region is indistinct except for surface salinity drop during summer monsoon due to more precipitation on-site and in adjoining areas. Low concentrations of chlorophyll at the surface and in the deep chlorophyll maxima represent the oligotrophic nature of this region. Surface water was found nutrient-depleted (0.03–0.4 µM Nitrate, 0.02–0.13 µM Phosphate). The maxima of vertical profiles of nitrate and phosphate were recorded at a shallower depth (150–200 m) when compared to its maxima in usual oceanic conditions, but a silicate maximum was recorded in deeper water. In the surface and upper mixed layer paucity of nutrients resulted in low N:P and N:Si ratios. Therefore, nitrogen limitation is evident. The overall ratio of N:P yielded a mean value of 15.33 and matched with the representative literature value for the Indian Ocean. The minimum oxygen values (<50 µM) in the deep water (150–200 m) indicated a hypoxic condition. No signature of denitrification and a moderate nitrate deficit were observed in deep waters. The negative values of Nitrate anomaly (N-tracer) at 50–100 m depth were attributed to a Watermass influenced by denitrification. The prevailing oligotrophic condition caused limited synthesis of organic matter and subsequently little decomposition in deep water. The maxima in the apparent oxygen utilization (AOU) profile are confined to 150 to 200 m depth and represent the most active zone for regeneration that is limited to shallow depth. Regenerated nutrients reached maxima at shallower depth and primarily control material cycling in this region. Supply of nitrate to the surface water based on the preformed values of prevailing water mass was primarily by Bay of Bengal water. According to the findings of this study, preformed nitrate concentrations between 100 and 200 metres below the surface were found very low, indicating that Indonesian Through Flow (ITF) has little impact on the distribution of nutrients in this area.

This study aimed to trace the spatial and seasonal changes in pigment composition and to develop mathematical formulas to quantitatively describe their composition in different seasons in two regions: the open Baltic Sea region and the Gulf of Gdańsk. The analyses were carried out based on a 20-year database of empirical data from 1999 to 2018 obtained using the HPLC method. The proportion of chlorophyll a in the total content of pigments was stable irrespective of the season and region (62% ± 5%). In summer and autumn, a higher total amount of photoprotective carotenoids (about 15–17% in total pigment content) than photosynthetic ones was recorded. The concentrations of marker pigments are related to periodic increases in the corresponding algal classes. The spring bloom dominated by diatoms and dinoflagellates results in 40% of fucoxanthin and 70% of peridinin in relation to their total content throughout all seasons. The highest percentage of chlorophyll b (up to 10% in open waters) and other pigments specific to green algae (neoxanthin, violaxanthin, lutein) were observed during summer and autumn. The 30% percentage of fucoxanthin confirms the occurrence of diatoms in autumn. The concentrations of groups and individual pigments have been determined as a function of chlorophyll a concentration. The best approximation results were obtained for the seasonal dependence of marker pigments for specific classes of algae. In summer and autumn – for chlorophyll b concentrations – zeaxanthin, fucoxanthin, alloxanthin and peridinin standard error factor ranges between 1.56 and 1.84.

Underwater imagery (UI) is an important and sometimes the only tool for mapping hard-bottom habitats. With the development of new camera systems, from hand-held or simple “drop-down” cameras to ROV/AUV-mounted video systems, video data collection has increased considerably. However, the processing and analysing of vast amounts of imagery can become very labour-intensive, thus making it ineffective both time-wise and financially. This task could be simplified if the processes or their intermediate steps could be done automatically. Luckily, the rise of AI applications for automatic image analysis tasks in the last decade has empowered researchers with robust and effective tools. In this study, two ways to make UI analysis more efficient were tested with eight dominant visual features of the Southeastern Baltic reefs: 1) the simplification of video processing and expert annotation efforts by skipping the video mosaicking step and reducing the number of frames analysed; 2) the application of semantic segmentation of UI using deep learning models. The results showed that the annotation of individual frames provides similar results compared to 2D mosaics; moreover, the reduction of frames by 2–3 times resulted in only minor differences from the baseline. Semantic segmentation using the PSPNet model as the deep learning architecture was extensively evaluated, applying three variants of validation. The accuracy of segmentation, as measured by the intersection-over-union, was mediocre; however, estimates of visual coverage percentages were fair: the difference between the expert annotations and model-predicted segmentation was less than 6–8%, which could be considered an encouraging result.

The prediction of the coastal bed evolution at an annual scale utilizing process-based models is usually a complex task requiring significant computational resources. To compensate for this, accelerating techniques aiming at reducing the amount of input parameters are often employed. In the framework of this research, a comprehensive evaluation of the capacity of the widely-used K-Means clustering algorithm as a method to obtain representative wave conditions was undertaken. Various enhancements to the algorithm were examined in order to improve model results. The examined tests were implemented in the sandy coastline adjacent to the port of Rethymno, Greece, utilizing an annual dataset of wave characteristics using the model MIKE21 Coupled Model FM. Model performance evaluation was carried out for each test simulation by comparing results to a “brute force” one, containing the bed level changes induced from the annual time series of hourly changing offshore sea state wave characteristics, deeming the results very satisfactory. The best-performing configurations were found to be related to the implementation of a filtering methodology to eliminate low-energy sea states from the dataset. Employment of clustering algorithms utilizing “smart” configurations to improve their performance could become a valuable tool for engineers desiring to obtain an accurate representation of annual bed level evolution, while simultaneously reducing the required computational effort.

The present study focused on understanding the seasonality of the phytoplankton biomass (chlorophyll a) distribution in the oligotrophic, Equatorial, and Southern Tropical Indian Ocean (ESTIO; 0–30°S and 60–90°E). The long-term satellite data analyses (2003–2020) showed a strong seasonality in sea surface temperature (SST), wind, currents, mean sea level anomaly (MSLA), photosynthetically available radiation (PAR), euphotic depth (ZEU) and mixed layer depth (MLD). As a response to the hydrographical changes, the phytoplankton biomass showed noticeable seasonal variation with the highest biomass during the Austral Winter (AW; June–September; avg. 0.11 ± 0.03 mg/m³) and lowest during the Austral Summer (AS; November–February; avg. 0.07 ± 0.03 mg/m). High chlorophyll patches (>0.1 mg/m³) were found between 0°–8°S during the AS and expanded over 0°–18°S during the AW. As multi-year mean chlorophyll a was higher (>0.1 mg/m³) in the northern part of the ESTIO (north of ∼13°S; HCD: high chlorophyll a domain) than the southern side (LCD: low chlorophyll a domain), the study area was divided into two domains and all the variables were analysed. In the HCD, enhancement of chlorophyll a was positively correlated with variables such as wind speed, wind stress, Ekman pumping, stronger northward and westward winds, as well as the presence of cyclonic eddies. These features are likely to stimulate primary production by uplifting the thermocline and enhancing nutrient supply. In the LCD, mixed layer depth also showed a strong positive correlation with elevated chlorophyll a, apparently because it is deep throughout the year (thereby keeping lower biomass) and deepens more strongly in winter than in the HCD. Another contrast with the HCD is that the cyclonic eddies appear to be insufficiently abundant to influence its chlorophyll a. Pearson's multivariable correlation analysis and principle component analysis confirmed the statistical significance of the above parameters on the enhancement of chlorophyll a in the ESTIO.