Oceanologia No. 65 (2) / 23


Original research article


Original research article

Is there a significant long-term shift in phytoplankton in small pelagic fish diets along India's southwest coast?
Oceanologia 2023, 65(2), 297-309

Preetha Gopalakrishnan Nair1,2,*, Shoji Joseph1, Narayana Pillai1, Mohamed Hatha Ammanamveetil Abdulla2
e-mail: preethagnairgn@gmail.com
1Central Marine Fisheries Research Institute, Kochi, India;
2Department of Marine Biology, Microbiology, Biochemistry, Cochin University of Science and Technology, Kochi, India
*corresponding author

keywords: Indian oil sardine, Indian mackerel, Plankton, Climate change, Southeastern Arabian Sea

Received 4 August 2021, Revised 29 May 2022, Accepted 21 July 2022, Available online 2 August 2022, Version of Record 17 April 2023.


The two main small pelagic fishes along the southwest coast of India in the eastern Arabian Sea, the Indian oil sardine (Sardinella longiceps) and the Indian mackerel (Rastrelliger kanagurta) were studied to see if there was any notable long-term alteration in phytoplankton in their diets. The basic oceanographic features and the long-term sea surface warming in the study region are first examined using satellite data, which reveals clear seasonality in the wind, sea surface temperature, sea surface salinity, and chlorophyll-a as well as long-term ocean surface warming. We then considered a recent gut content data set of Indian oil sardine and Indian mackerel from the 2010–2011 period from two landing places along India's southwest coast, which was compared with numerous historical data sets to find out if there was any long-term phytoplankton compositional change in the diet. The recent data revealed the same dominant phytoplankton as those collected decades ago, such as Coscinodiscus, Nitzschia, Pleurosigma, and Thalassiosira in sardines and Coscinodiscus, Thalassiosira, Ceratium, Dinophysis, Protoperidinium, and Pyrophacus in mackerel. This suggests the lack of any significant long-term qualitative shift of phytoplankton in the Indian oil sardine and Indian mackerel over the last several decades. However, several phytoplankton genera found present in the recent data were absent in the historical data, including 10 genera for mackerel and 17 for Indian oil sardine. These recent phytoplankton records are intriguing, and we feel they could be an early sign of long-term phytoplankton compositional or relative abundance shift, although additional research is needed to confirm this.
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On the non-parametric changepoint detection of flow regimes in cyclone Amphan
Oceanologia 2023, 65(2), 310-317

Venkat Shesu Reddem1,*, Venkata Jampana1, Ravichandran Muthalagu2, Venkateswara Rao Bekkam3, Pattabhi Rama Rao Eluri1, Srinivasa Kumar Tummala1
1Indian National Centre for Ocean Information Services, Hyderabad, India;
e-mail: venkat@incois.gov.in
2Ministry of Earth Sciences, New Delhi, India
3Jawaharlal Nehru Technological University, Hyderabad, India
*corresponding author

keywords: Amphan, Changepoint detection, Cyclone

Received 31 August 2021, Revised 6 July 2022, Accepted 25 July 2022, Available online 8 August 2022, Version of Record 17 April 2023.


The Bay of Bengal was witness to a severe cyclone named Amphan during the summer of the year 2020. The National Institute of Ocean Technology (NIOT), INDIA moorings BD08 and BD09 happened to be in the vicinity of the cyclone. The highly instrumented mooring recorded near-surface meteorological parameters like wind speed, sea surface temperature, and near-surface pressure. This article explores the possibility of using a non-parametric algorithm to identify different flow regimes using a one-month long time-series data of the near-surface parameters. The changes in the structure of the time series signal were statistically segmented using an unconstrained non-parametric algorithm. The non-parametric changepoint method was applied to time series of near-surface winds, sea surface temperature, sea level pressure, air temperature and salinity and the segmentations are consistent with visual observations. Identifying different data segments and their simple parameterization is a crucial component and relating them to different flow regimes is useful for the development of parametrization schemes in weather and climate models. The segmentations can considerably simplify the parametrization schemes when expressed as linear functions. Moreover, the usefulness of non-parametric automatic detection of data segments of similar statistical properties shall be more apparent when dealing with relatively long time series data.
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Predicting sea surface salinity in a tidal estuary with machine learning
Oceanologia 2023, 65(2), 318-332

Nicolas Guillou1,*, Georges Chapalain1, Sébastien Petton2
1Cerema, DTecREM, HA, Technopôle Brest-Iroise, Plouzané, France;
e-mail: nicolas.guillou@cerema.fr
2Ifremer, University of Brest, CNRS, IRD, LEMAR, Argenton, France
*corresponding author

keywords: Multilayer perceptron, Support vector regression, Random forest, River plume, Numerical model, Bay of Brest

Received 14 April 2022, Revised 8 July 2022, Accepted 25 July 2022, Available online 10 August 2022, Version of Record 17 April 2023.


As an indicator of exchanges between watersheds, rivers and coastal seas, salinity may provide valuable information about the exposure, ecological health and robustness of marine ecosystems, including especially estuaries. The temporal variations of salinity are traditionally approached with numerical models based on a physical description of hydrodynamic and hydrological processes. However, as these models require large computational resources, such an approach is, in practice, rarely considered for rapid turnaround predictions as requested by engineering and operational applications dealing with the ecological monitoring of estuaries. As an alternative efficient and rapid solution, we investigated here the potential of machine learning algorithms to mimic the non-linear complex relationships between salinity and a series of input parameters (such as tide-induced free-surface elevation, river discharges and wind velocity). Beyond regression methods, the attention was dedicated to popular machine learning approaches including MultiLayer Perceptron, Support Vector Regression and Random Forest. These algorithms were applied to six-year observations of sea surface salinity at the mouth of the Elorn estuary (bay of Brest, western Brittany, France) and compared to predictions from an advanced ecological numerical model. In spite of simple input data, machine learning algorithms reproduced the seasonal and semi-diurnal variations of sea surface salinity characterised by noticeable tide-induced modulations and low-salinity events during the winter period. Support Vector Regression provided the best estimations of surface salinity, improving especially predictions from the advanced numerical model during low-salinity events. This promotes the exploitation of machine learning algorithms as a complementary tool to process-based physical models.
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Characteristics of internal solitary waves in the Maluku Sea, Indonesia
Oceanologia 2023, 65(2), 333-342

Adi Purwandana1,*, Yannis Cuypers2
1 Research Center for Oceanography, National Research and Innovation Agency (RCO-BRIN), Jakarta, Indonesia;
e-mail: adip003@brin.go.id
2Laboratory of Oceanography and Climatology via Experimentation and Numerical Approach (LOCEAN), Sorbonne University, Paris, France
*corresponding author

keywords: Internal tide, Internal wave, Ternate waters, Lifamatola Passage, Sangihe Passage

Received 22 February 2022, Revised 6 June 2022, Accepted 26 July 2022, Available online 14 August 2022, Version of Record 17 April 2023.


The appearance of internal solitary waves (ISWs) in the Maluku Sea is often captured by satellite imagery. However, no study has revealed details on this phenomenon to date. Here, the characteristics of such ISWs were investigated based on their appearance in synthetic aperture radar (SAR) imagery on 20 February 2015. Two different sources of ISW packets were observed: one packet propagating from the Lifamatola Passage and another from the Sangihe Passage. The vertical structure of the waves was constructed using the Korteweg-de Vries (KdV) model, which suggests an average phase speed of ∼2.8 and 2.7 m s−1 for the first and the second sources, respectively. ISWs originating from the first source had a typical amplitude of O(80 m), while those from the second source were characterized by a lower amplitude of O(40 m). The waves generated horizontal and vertical currents with typical magnitudes of O(1 m s−1) and O(10 cm s−1) for the first source and O(0.6 m s−1) and O(4 cm s−1) for the second source, respectively. The mean energy densities of the first and second sources reached 461 MJ m−1 and 185 MJ m−1, respectively. Single leading solitary wave contained a fraction of approximately 20% and 15% of the baroclinic tidal energy generated in the Lifamatola Passage and Sangihe Passage, respectively.
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Generation and Assessment of ARGO Sea Surface Temperature Climatology for the Indian Ocean Region
Oceanologia 2023, 65(2), 343-357

Ravi Kumar Jha*, T.V.S. Udaya Bhaskar
Indian National Centre for Ocean Information Services (INCOIS), Ministry of Earth Sciences (MoES), Government of India
e-mail: ravikumar.jha@incois.gov.in

keywords: ARGO, SST, Indian Ocean, Climatology, DIVA, In-situ, Satellite

Received 3 February 2022, Revised 8 July 2022, Accepted 31 August 2022, Available online 11 September 2022, Version of Record 17 April 2023.


ARGO program was conceived with an aim to generate near real-time ocean observations as the primary in-situ sources for use in operational oceanography studies. Two decades-long ARGO near-surface temperature data set was used for generating monthly gridded ARGO sea surface temperature (ASST) product on a climatological scale. Data interpolating variational analysis (DIVA) method was employed for generating the product with a spatial resolution of 0.25° x 0.25° for the Tropical Indian Ocean. This monthly ASST product was evaluated using five different climatological SST products derived from in-situ and satellite measurements. Various statistics such as BIAS, RMSE, coefficient of correlation, and skill scores were generated to evaluate the reliability of the ASST product. Further, the ASST product was validated with climatological in-situ SST obtained from RAMA and OMNI moorings deployed in the Indian Ocean. Statistical comparisons showed low BIAS and RMSE, and high correlation and skill scores with most of the buoys locations and the gridded SST products. Results concluded that the near-surface temperature data from ARGO can be used along with other SST data sets in the generation of high-resolution blended SST products.

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Above- and belowground habitat complexity created by emergent and submerged vegetation drives the structure of benthic assemblages
Oceanologia 2023, 65(2), 358-370

Krzysztof Pawlikowski*, Ryszard Kornijów
National Marine Fisheries Research Institute, Gdynia, Poland;
e-mail: kpawlikowski@mir.gdynia.pl
*corresponding author

keywords: Vistula Lagoon, Littoral, Trophic guilds, Macrophytes, Vertical distribution

Received 1 February 2022, Revised 2 October 2022, Accepted 17 October 2022, Available online 31 October 2022, Version of Record 17 April 2023.


The contrast in habitat complexity between emergent (EMV) and submerged vegetation (SUV) zones in aquatic ecosystems results from the differences in the structure of plant above- and belowground parts, subject to seasonal changes. Comparative studies on the influence of habitat complexity created by vegetation on benthic macroinvertebrates in coastal areas are scarce. In order to fill this knowledge gap, we performed a study on a seasonal basis in the brackish Vistula Lagoon (southern Baltic Sea) in two zones: EMV, dominated by a dense belt of Phragmites australis (Cav.) Trin. ex Steud, and SUV, with scattered stands of Potamogeton perfoliatus L. We assumed the following: i. Species richness, diversity, and density of invertebrates are higher in the EMV zone due to greater and less seasonally variable structural complexity than in the SUV zone, ii. High belowground complexity in the EMV zone due to the presence of the rhizome/root matrix, much more robust and denser than in the SUV zone limits the vertical distribution of macroinvertebrates. Both hypotheses were supported. Overall, our results pointing to higher animal diversity and density in more complex aquatic habitats are consistent with other studies, inferred mostly from comparative surveys of bare bottom and that covered with submerged vegetation. The results of this study highlight potentially far-reaching implications for benthic invertebrate fauna and their role in the aquatic ecosystem in the context of increasingly rapid loss of aquatic vegetation due to multiple anthropogenic stressors.
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Latitudinal and archipelago effect on the composition, distribution, and abundance of zooplanktonic organisms in the Gulf of California
Oceanologia 2023, 65(2), 371-385

Benjamín Quiroz-Martínez1,*, David Alberto Salas-de-León1, Antonio Gil-Zurita2, María Adela Monreal-Gómez1, Erik Coria-Monter1, Elizabeth Durán-Campos3
1Ecology and Aquatic Biodiversity Unit, Institute of Marine Sciences and Limnology, National Autonomous University of Mexico (UNAM), Mexico City, Mexico;
e-mail: bquirozm@cmarl.unam.mx
2Doctoral Program in Environmental Sciences, Institute of Basic Sciences and Engineering, the Autonomous University of the State of Hidalgo, Pachuca, Hidalgo, Mexico
3Mazatlán Academic Unit, Institute of Marine Sciences and Limnology, National Autonomous University of Mexico (UNAM), Mazatlán, Sinaloa, Mexico
* corresponding author

keywords: Zooplankton, Taxon richness, Latitudinal distribution, Geometric constraints, Gulf of California

Received 8 December 2021, Revised 5 October 2022, Accepted 15 November 2022, Available online 25 November 2022, Version of Record 17 April 2023.


The upper Gulf of California is one of the most energetic regions owing to its tidal range and strong tidal currents, making the upper gulf and the archipelago zone highly turbulent regions; the abundance of zooplankton should be associated with mixing phenomena. We aimed to determine the latitudinal distribution of zooplanktonic organisms in this region and the influence of the islands on their distribution and abundance using historical data. Distribution of abundance followed the current patterns, the archipelago influences abundance favorably but does not affect diversity. Latitudinal zooplankton richness had a quasi-parabolic shape. A decrease in richness was observed at 27.5°N, in the archipelago region, with maximum richness at 26.5°N and 28.5°N. The distribution of latitudinal ranges is consistent with geometric constraints models; taxa with wide ranges are in the central area, while those with narrow ranges are near the boundaries and the Upper Gulf. Zooplankton responds in some way to the existence of the southern boundary as shown by the decrease of richness in this region. At the whole scale of the Gulf, the distribution of richness followed geometric constraints model, while at smaller scales, distribution and abundance are conditioned by the hydrodynamics of the Gulf. We compared zooplankton spatial distribution with Sea Level Anomaly, Sea Surface Temperature, and Chlorophyll-a concentrations from Copernicus to establish relationships between these factors. We performed Cluster and Redundancy Analysis to characterize similarities between stations in terms of biomass and taxon composition and to assess the importance of environmental variables on the distribution of zooplankton.
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Analysis of the impact of nutrients deposited from the land side on the waters of Puck Lagoon (Gdańsk Basin, Southern Baltic): A model study
Oceanologia 2023, 65(2), 386-397

Dawid Dybowski*, Lidia Dzierzbicka-Głowacka
Physical Oceanography Department, Institute of Oceanology, Polish Academy of Sciences, Sopot, Poland;
e-mail: ddybowski@iopan.pl
*corresponding author

keywords: Coastal zone, Agricultural impact, Water quality, Eutrophication, Nutrients

Received 9 September 2022, Revised 24 November 2022, Accepted 30 November 2022, Available online 16 December 2022, Version of Record 17 April 2023.


The article analyzes the impact of nutrients (nitrates and phosphates) supplied from the land on the waters of the Puck Lagoon (Gdańsk Basin, southern Baltic). The study is based on the numerical modelling. The model data was verified by comparison with the in situ measurement data. The spatial and temporal variability of the concentrations of nitrate, phosphate, and chlorophyll a were analyzed. We came to the conclusion that the load of nutrients deposited from the land side to the waters of the Puck Lagoon is relatively small (but not negligible compared to the Vistula River). However, even when a little runoff enters the reservoir with a very limited water exchange, like the Puck Lagoon, there are periods when riverine nutrients load significantly affects the functioning of the ecosystem.
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Seasonal variation in size structure and production of autotrophic plankton community in eutrophied, low-light environment: A focus on Mesodinium rubrum
Oceanologia 2023, 65(2), 398-409

Atis Labucis*, Astra Labuce, Iveta Jurgensone, Ieva Barda, Ingrida Andersone, Anda Ikauniece
Latvian Institute of Aquatic Ecology, Riga, Latvia;
e-mail: atis.labucis@lhei.lv
*corresponding author

keywords: Primary production, Coastal, Brackish, Gulf of Riga, Baltic Sea, Ciliate

Received 10 July 2021, Revised 18 October 2022, Accepted 30 November 2022, Available online 11 December 2022, Version of Record 17 April 2023.


Temporal variations in the primary production of the size-fractionated autotrophic plankton community were studied in coastal-estuarine waters of the eutrophic Gulf of Riga, Baltic Sea. The community was net-autotrophic during spring and summer and net-heterotrophic during autumn. The results of the present study clearly demonstrate strong covariation between net primary production (NPP) and <56 µm fractionated community biomass, particularly small-sized (16–33 µm) Mesodinium rubrum, implying that the majority of NPP stems from the lower end of the size spectrum. A pronounced size distribution shift was observed within the M. rubrum population. Large-sized (length ≥34 µm) M. rubrum was the most abundant in the first half of the productive season (until week 24), whereas small-sized M. rubrum dominated during the stratified period.
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Extreme separations of bottle posts in the southern Baltic Sea – tentative interpretation of an experiment-of-opportunity
Oceanologia 2023, 65(2), 410-422

Ulrich Callies*, Hans von Storch*
Helmholtz-Zentrum Hereon, Geesthacht, Germany;
e-mail: ulrich.callies@hereon.de, ulrich.callies@hereon.de, hvonstorch@web.de
*corresponding author

keywords: Drift bottles, Drift simulations, Random dispersion, Leeway, Lagrangian coherent structures, Noise

Received 26 August 2022, Accepted 30 November 2022, Available online 14 December 2022, Version of Record 17 April 2023.


During an experiment-of-opportunity in July 2019, 27 drift bottles were released in the southern Baltic Sea. Ten of these bottles were found and reported at locations that were surprisingly widespread. In this study, we explore the chances to reproduce these findings with a numerical drift model. While trajectories may be considered as completely deterministic, in practice their prediction as well as reconstruction has a strong stochastic component, because of ubiquitous gradients on even the smallest scales. We illustrate different aspects of uncertainty including specification of leeway, random dispersion, and stretching along Lagrangian coherent structures. By and large, the results of numerical ensemble simulations seem to be in reasonable agreement with the observational evidence available. Some drift bottle findings suggest a bias in simulations, but without knowing the drift bottles’ full drift paths, a basis for more detailed model tuning is missing.
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Spatial distribution of arsenic in surface sediments of the southern Baltic Sea
Oceanologia 2023, 65(2), 423-433

Marta Szubska*, Jacek Bełdowski
Institute of Oceanology, Polish Academy of Sciences, Sopot, Poland;
e-mail: szubi@iopan.pl
*corresponding author

keywords: Arsenic, Sediment properties, Arsenic cycle, Chemical Warfare Agents

Received 1 September 2022, Revised 5 December 2022, Accepted 27 December 2022, Available online 4 January 2023, Version of Record 17 April 2023.


Arsenic is a ubiquitous chemical element, occurring naturally worldwide. Yet due to its global cycle, its concentrations in the marine environment are manifold higher than the terrestrial background and may pose harm to biota. This is especially relevant for the Baltic Sea, which is very susceptible to any kind of pollution. Arsenic transported to the sea is adsorbed on iron oxides or precipitating as flocculating particulates and finally bounded in sediments. Therefore, despite the contemporary emission cuts, the existing pollution remains or constantly circulates in marine habitats. The purpose of the research was to recognize the spatial distribution of arsenic in the surface sediments of the southern parts of the Baltic Sea. The number of 483 samples allowed us to prepare reliable interpolation of arsenic contents in surface sediments. Although arsenic concentrations in the Baltic Sea can be considered low, in particular areas the levels are significantly higher. The observed arsenic concentrations distribution pattern could be mostly explained by natural transportation and accumulation bottom-type distribution.
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A study of the seasonal and interannual variability of phytoplankton and zooplankton assemblages in a significant marine ecosystem
Oceanologia 2023, 65(2), 434-451

Jochen Kämpf1,*, Michelle Newman1, Mark Doubell2, Luciana Möller1, Ryan Baring1, Alex Shute1, Ana Redondo Rodriguez2
1Flinders University, College of Science & Engineering, Bedford Park, Australia;
e-mail: jochen.kaempf@flinders.edu.au
2South Australian Research and Development Institute (SARDI), West Beach, Australia
*corresponding author

keywords: Marine ecosystem, Plankton research, Marine productivity

Received 28 August 2022, Revised 9 December 2022, Accepted 27 December 2022, Available online 6 January 2023, Version of Record 17 April 2023.


The eastern Great Australian Bight (GAB) is a significant marine ecosystem, featuring a range of marine mammals and large pelagic fish including blue whales, sharks and tuna. Previous research has classified the region as generally oligotrophic, apart from late austral summer months when seasonal upwelling triggers phytoplankton blooms in the region. Based on multi-year field observations, this study analysed the interannual and interdecadal variability of the plankton community structure in this region. Pigment data indicate that nano- and pico-phytoplankton generally dominated the phytoplankton community structure with averages of 39% and 30% of the total biomass, including a relatively large proportion of nanophytoplankton (cryptophytes, haptophytes and prasinophytes) with cell sizes <5 µm, not resolved in microscopic cell counts. Nano- and pico-phytoplankton alone contributed ∼0.3 mg/m3 to the chlorophyll-a signal and therefore sustained an overall mesotrophic environment year-round. Distinct diatom blooms developed during the upwelling season within concentrated subsurface layers where chlorophyll-a concentrations increased to >1 mg/m3, characterising eutrophic conditions. The biomass of diatoms increased from <10% to ∼30% of total biomass. Diatom blooms coincided with relatively high abundances of three dominant zooplankton species (Oithona similis, Penilia avirostris and Microsetella norvegica) and/or the dinophyta Noctiluca scintillans, but events of high zooplankton abundance also occurred outside the upwelling season. The observational findings also show the occurrence of significant subsurface phytoplankton blooms in late spring, not reported before, that may also contribute to the ecosystem functioning of the region.
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Corrigendum to “Sea spray volume flux estimation using joint statistics of wind and waves” [Oceanologia 64(4)/(2022), 789–793]
Oceanologia 2023, 65(2), V

Dag Myrhaug*, Bernt J. Leira, Gowtham Radhakrishnan, Håvard Holm
Department of Marine Technology, Norwegian University of Science and Technology (NTNU), Trondheim, Norway;
e-mail: dag.myrhaug@ntnu.no
*corresponding author

Available online 22 October 2022, Version of Record 17 April 2023.
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