Oceanographic Phenomena Research Articles

A two-stage deep learning architecture for detection global coastal and offshore submesoscale ocean eddy using SDGSAT-1 multispectral imagery

Submesoscale ocean eddies are essential oceanic phenomenon that control and influence the ocean energy cascade. Most existing eddy detection methods rely on low-resolution satellite altimeter data, which fail to capture submesoscale ocean features and oceanographic phenomena in shallow water. Introducing high-resolution multispectral data can alleviate these problems, yet it has been largely overlooked. A generalized and efficient deep learning architecture that combines developments in deep learning with Sustainable Development Goals Science Satellite 1 (SDGSAT-1) multispectral data from earth observations offers a potential pathway for more fine detection of ocean eddies. Considering that oceanic eddy exhibits spatially sparse characteristics on high-resolution remote sensing scenes, the oceanic eddy detection (OED) model suitable for global coastal and offshore regions is divided into two stages: eddy information judgment and eddy position determination. Correspondingly, SDGSAT-1 multispectral data from November 2021 to December 2022 were carried out to construct two submesoscale eddy datasets for training and testing each stage model. The union validation of multiple metrics demonstrates that the proposed OED model and its stage models achieve state-of-the-art (SOTA) performance, especially in optically complex coastal and offshore waters. We applied the model to real-world scenes captured by SDGSAT-1 in 2023, and found that the detected results were mainly located at the water depth below 200 m. The authenticity of the recognition results is validated using sea surface chlorophyll concentration, temperature, and topography data, indicating that the OED model has achieved remarkable effectiveness under various sea conditions. In addition, the temporal distributions and statistical characteristics of detected submesoscale eddies are analyzed over an extended period (November 2021 to November 2023). Finally, HISEA-2, Landsat-9, and Sentinel-2 served as testing grounds to validate the generalization of the proposed methodology, with experimental results demonstrating that the OED model possesses significant developmental potential for multi-source remote sensing data. This paper presents a comprehensive deep learning framework for the global-scale detection of submesoscale eddies and underscores the pivotal role of high-resolution multispectral imagery as an innovative data source for global coastal and offshore eddy identification.

Enhancing Data Accessibility and Usability: Insights from Observation Data at the Ieodo Ocean Research Station (2005-2023)

The Ieodo Ocean Research Station (IORS) has been a critical site for collecting oceanic and atmospheric data over 19 years (2005-2023). This study analyzes key parameters including tide, wave, water temperature, salinity, wind, air temperature, etc. While these datasets have provided valuable insights into regional climatic and oceanographic phenomena, significant incorrect data were identified, particularly in the records from 2015 to 2019. Issues such as overlapping data spanning multiple years, non-chronological ordering, and discrepancies in decimal precision were detected likely due to inadequate data handling during the adjustment process in programs like Excel. These errors, which persisted for years without detection or correction, highlight a lack of responsibility and verification among both government and private sector employees involved in data management. Given the substantial investment of government resources in the IORS, the continuous presence of incorrect data on official platforms raises concerns that extend beyond the responsible parties to the broader scientific and public communities. To prevent future occurrences, the study emphasized the need for stringent data management practices and ongoing accuracy in data handling, ensuring that the IORS continues to serve as a reliable resource for oceanographic research in Korea and globally.

A physical explanation for an unusually long-duration slow slip event in the Nankai Trough

The Dense Oceanfloor Network System for Earthquakes and Tsunamis (DONET) and the Long Term Borehole Monitoring System (LTBMS), installed above the source region of the 1944 Tonankai earthquake, revealed that crustal deformation is driven by slow slip events (SSEs) in the shallower extension of megathrust earthquakes. However, there are unresolved questions about (A) the duration of the SSE in February 2012, which was longer than expected for SSEs with similar magnitudes, and (B) the relationship of the spatial distribution of fault slip between the SSEs in February and December 2012 under the condition of drilling disturbance. To clarify these questions, we re-analyzed the pore/seafloor pressure data associated with the SSEs. Our refined fault models show that the SSE in February had a significantly slower propagation speed and a longer duration than others, while the SSE in December was comparable to others. We interpret that the difference in duration and propagation speed is related to external and internal stress perturbations, respectively. Using the ocean modeling JCOPE (Japan Coastal Ocean Predictability Experiment), we identified that the decrease and subsequent increase in seafloor pressure due to the passage of the Kuroshio meander coincided with the latter part of the longer duration of the SSE in February and its termination, respectively. This suggests that the Kuroshio meander might affect the duration of SSEs. Our refined fault model also indicates that the amount of shear stress accumulation was small before the occurrence of the SSE in February, which triggered the slow propagation of aseismic slip based on a rate- and state-dependent friction law. These results imply that we need to consider the variety of SSEs from the viewpoint of stress perturbation due to not only interaction between fault segments but also external forces from oceanographic phenomena.

Early Investigation of Tropical Cyclones Blake-Claudia’s Effect on Seasonal Downwelling in Southern Indonesia Waters

Abstract Indonesia southern waters area is one of the places where tropical storms form and develop into tropical cyclones. Apart from cyclones, southern Indonesia waters also experienced other oceanographic phenomena, the seasonal upwelling and downwelling. This study aims to investigate the physical conditions in southern Indonesia waters during the TC Blake-Claudia which occurred during seasonal downwelling period. Historical data shows that tropical cyclones in southern Indonesia generally occur in DFJ and almost never occur in JJA. Meanwhile, the downwelling period occurs during the DJF season. The results show TC Blake-Claudia has weaken or disrupted seasonal downwelling by decreasing SSHA and increasing chlorophyll concentration. This change in oceanographic parameter expected to be occur not only as the result of cyclonic activity which creates a void of water on the coast, but also supported by the initial conditions of the study area which tend to remain unstable just after upwelling event ends.

Drivers of rising monthly water temperature in river estuaries

AbstractRiver estuaries are habitats for a variety of organisms, including many temperature‐sensitive species; water temperatures in estuaries are affected by several factors as they are influenced by both terrestrial and marine environments. Therefore, understanding the factors that influence river estuaries are essential for environmental management. However, no information exists on temperature change at high temporal resolution and over a wide area; moreover, the relationship with environmental factors has not yet been clarified. Here, we have described the actual status of water temperature change in riverine estuaries and its relationship with environmental factors for a wide area of the Japanese archipelago. Our results indicated that 217 of 294 rivers showed a significant monthly increase in water temperature. The average annual change in rates of water temperature increase was the highest in October at 0.090°C yr−1 and lowest in February at 0.068°C yr−1. Furthermore, snowfall, air temperature increase, sea water temperature, and land use were identified as factors increasing the rate of water temperature increase. Factors influencing the increase in river estuarine water temperature varied from month to month—with meteorological factors being the strongest influencers from spring to fall, and anthropogenic factors in winter. Our findings emphasize the importance of considering not only meteorological and oceanographic phenomena, but also anthropogenic influences and topographic features to understand the pattern of water temperature changes in river estuaries.

Transformation of dense shelf water cascade into turbidity currents: Insights from high-resolution geophysical datasets

Dense shelf water cascade (DSWC) is a common oceanographic phenomenon on many continental shelves. Previous studies indicate that the DSWC could shape seabed physiography and carry seawater, sediment, and organic carbon a long distance from the continental shelf to the basin floor. However, it remains enigmatic how these DSWC's interact with seabed geomorphology and travel long distances from the shallow to deep marine environments. In this study, we employed high-resolution multibeam bathymetry, 2D and 3D seismic reflection, core description, and sediment grain size data from the Gippsland Basin, southeast offshore Australia. The continental shelf of the central Gippsland Basin stores sediment supplied by the along-shelf transported DSWC. By calculating the sediment motion threshold, we demonstrate that the DSWC is capable of entraining sediment from, and forming dense bottom nepheloid layers above, the seabed. Seismic reflection data reveal that cyclic steps are common on the shelf and slope, indicating a downslope-transported, supercritical current-dominated environment. Core observation and grain size analyses reveal that coarse-grained, Ta-typed turbidites are the major facies, indicating the presence of high-intensity downslope-traversing turbidity currents. Thus, supercritical turbidity currents are the dominant sedimentary process in the central Gippsland Basin. We illuminate that DSWC can interact with pre-existing seabed bathymetry created by a buried submarine landslide, resuspending sediment and igniting downslope-transported turbidity currents. The presence of numerous cyclic steps indicates that the turbidity current can evolve into a supercritical regime upon ignition, leaving complex seabed geomorphology and allowing the forming currents to travel across the shelf and extend more than 80 km down the lower slope. As revealed by our literature review, we imply that the transformation of DSWC into turbidity currents should be a common sedimentary process on outer continental shelves globally, significantly sculpting the seabed morphology and facilitating sediment and other marine particles transportation from shallow to deep sea.

Using meta-analysis to explore the roles of global upwelling exposure and experimental design in bivalve responses to low pH

Low pH conditions, associated with ocean acidification, represent threats to many commercially and ecologically important organisms, including bivalves. However, there are knowledge gaps regarding factors explaining observed differences in biological responses to low pH in laboratory experiments. Specific sources of local adaptation such as upwelling exposure and the role of experimental design, such as carbonate chemistry parameter changes, should be considered. Linking upwelling exposure, as an individual oceanographic phenomenon, to responses measured in laboratory experiments may further our understanding of local adaptation to global change. Here, meta-analysis is used to test the hypotheses that upwelling exposure and experimental design affect outcomes of individual, laboratory-based studies that assess bivalve metabolic (clearance and respiration rate) responses to low pH. Results show that while bivalves generally decrease metabolic activity in response to low pH, upwelling exposure and experimental design can significantly impact outcomes. Bivalves from downwelling or weak upwelling areas decrease metabolic activity in response to low pH, but bivalves from strong upwelling areas increase or do not change metabolic activity in response to low pH. Furthermore, experimental temperature, exposure time and magnitude of the change in carbonate chemistry parameters all significantly affect outcomes. These results suggest that bivalves from strong upwelling areas may be less sensitive to low pH. This furthers our understanding of local adaptation to global change by demonstrating that upwelling alone can explain up to 49 % of the variability associated with bivalve metabolic responses to low pH. Furthermore, when interpreting outcomes of individual, laboratory experiments, scientists should be aware that higher temperatures, shorter exposure times and larger changes in carbonate chemistry parameters may increase the chance of suppressed metabolic activity.

3-D Adaptive AUV Sampling for Classification of Water Masses

Autonomous underwater vehicles with onboard computing units foster innovative approaches for sampling oceanographic phenomena. Feedback of observations via the onboard model for planning algorithms enable adaptive sampling for such robotic units. In this work, we develop, implement, and test an adaptive sampling algorithm for efficient sampling of water masses in a 3-D frontal system. Focusing on a river plume, salinity variations are used to characterize the water masses. A threshold in salinity is assumed to distinguish the ocean and river waters, so that excursions below the threshold define river waters. The onboard model builds on a Gaussian random field representation of the salinity variations in (north, east, depth) coordinates. This model is initially trained from numerical ocean model data, and then updated with data gathered by the vehicle sensor. The Gaussian random field model further allows closed-form expressions of the expected spatially integrated Bernoulli variance of the salinity excursion set, which is used to reward sampling efforts. Combining these results with forward-looking planning algorithms, we suggest a workflow for 3-D adaptive sampling to map river plume systems. Simulation studies are used to compare the suggested approach with others. Results of field trials in the Nidelva river plume in Norway are presented and discussed.

The Catch of Little Tuna (Euthynnus sp.) in Relation to Thermal Front in the Makassar Strait

The Makassar Strait waters area is a potential area for the utilization of marine fishery resources in Indonesia especially for large pelagic fisheries because it is one of the migration trajectories of little tuna (Euthynnus sp.). In order to optimally utilize tuna resources, remote sensing technology based on oceanographic satellite imagery can be relied upon to facilitate identification, prediction, and spatial and temporal mapping of potential fishing areas. This study aims to study the phenomenon of oceanography (thermal front) as an indicator of potential for little tuna fishing areas in the Makassar Strait. Primary data was obtained through in-situ data collection (direct observation in the field by following fishing operations using the purse seine, while secondary data consisting of oceanographic data such as sea surface temperature and sea surface chlorophyll-a concentrations sourced from satellite imagery data (Aqua satellite with MODIS sensor). The distribution of the thermal front was analyzed using ArcGIS 10.4 software to determine the relationship between little tuna fishing productivity and the oceanographic phenomenon. Based on the analysis results, total of 61 positions for little tuna fishing using a purse seine, five (5) fishing positions were in the thermal front area, where the catch of little tuna is higher than the average catch outside the area. These results indicate that the thermal front can be used as an indicator of potential for little tuna fishing areas in the Makassar Strait.

Integrating fishers’ knowledge with oceanographic observations to understand changing ocean conditions in the Northeast United States

Recent warming in the Northeast United States continental shelf ecosystem has raised several concerns about the impacts on the ecosystem and commercial fisheries. In 2014, researchers from the Commercial Fisheries Research Foundation and Woods Hole Oceanographic Institution founded the Shelf Research Fleet to involve fishers in monitoring the rapidly changing ocean environment and encourage sharing of ecological knowledge. The Shelf Research Fleet is a transdisciplinary, cooperative program that trains commercial fishers to collect oceanographic information by deploying conductivity, temperature, and depth (CTD) instruments while commercially fishing. A total of 806 CTD profiles have been collected by the Shelf Research Fleet through December 2022. Participating vessels can view the conductivity and temperature water column profiles they collect in real-time. These profiles help inform their fishing practices and give insights when unexpected species appear in their gear or if their catch composition changes from previous years. The data collected by the Shelf Research Fleet are shared with and processed by researchers from numerous partnering institutions. The Shelf Research Fleet data have been used by researchers to better understand oceanographic phenomena including marine heatwaves, shelf-break exchange processes, warm core rings, and salinity maximum intrusions onto the continental shelf. The scope of the Shelf Research Fleet has grown over time to include efforts to more directly link oceanographic results with biological observations to better understand how changing ocean conditions are affecting commercially important species. This article describes the approach, successes, challenges, and future directions of the Shelf Research Fleet and aims to outline a framework for a cost-effective research program that engages fishers in the collection of oceanographic data, strengthening partnerships between fishing industry members and the scientific community.

Deriving Sea Subsurface Temperature Fields From Satellite Remote Sensing Data Using a Generative Adversarial Network Model

AbstractAccurately inverting global and regional subsurface temperature (ST) by multisource satellite observations is a challenging but hot topic. This study proposes a new method to invert daily ST from the sea surface information in China's marginal seas based on generative adversarial network (GAN) model. The proposed GAN‐based model can project the STs from sea surface information (SLA, SSTA, SST) with a high resolution of 1/12°. A traditional regression‐based model, Modular Ocean Data Assimilation System (MODAS), is set up same experiments for comparison. The results show that the averaged root mean square error results are less than 1.45°C in the upper 200 m and the highest averaged R2 of 0.97 at the 70 m level, which is better than that of MODAS. Errors analysis and typical oceanographic phenomena analysis results show the superiority of the proposed GAN‐based model in this study. This study can provide high‐precision daily ST data from sea surface information, which can be expanded to further studies on the interior ocean variation characteristics.

Habitat changes and catch rate variability for greater amberjack in the Taiwan Strait: The effects of El Niño–southern oscillation events

El Niño–Southern Oscillation (ENSO) is a crucial oceanographic phenomenon that leads to interannual fluctuations in the climate and ecosystem productivity of tropical and subtropical areas. These fluctuations affect the suitability of habitats for many commercial fish species. However, detailed information on the effects of this major phenomenon and the resulting environmental changes on the habitat and catch rates of the economically and ecologically crucial species of the greater amberjack (Seriola dumerili) in the Taiwan Strait (TS) is lacking. In this study, we employed a weighted habitat suitability index (HSI) modeling method and used remotely sensed marine environmental data as well as data from recorders in Taiwanese fishing vessels (in 2014–2019) to understand the effects of ENSO events on the habitat suitability and catch rates for greater amberjack in the TS. Analysis of variance revealed that environmental factors substantially influenced greater amberjack habitats and catch rates during ENSO events across seasons. The catch rates were high in spring and summer in the southern and northern TS and in autumn and winter in the southern TS. The catch rates were higher in spring, summer, and autumn (>9.0 kg/h) in El Niño years, and in winter, the catch rates were higher in normal years (>12.0 kg/h) and lower in La Niña years. The predicted HSI for the southern and northern TS revealed that greater amberjack populations were predominantly distributed at 20–24°N and 24–28°N, respectively. Opposite habitat suitability was synchronously found in spring and summer during ENSO events, with higher HSI values recorded in spring in El Niño and normal years and higher HSI values recorded in summer in La Niña years. In winter, the HSI values of the southern and northern TS were higher in El Niño and normal years and substantially lower in La Niña years. Habitat suitability was extremely low in autumn. These findings imply that ENSO events play a key role in regulating environmental conditions and affect the catch rates and habitat suitability for the greater amberjack in the TS.

Feeding ecology of the pandalid shrimp, Plesionika semilaevis (Spence Bate 1888) in South Eastern Arabian Sea

The feeding ecology of deep-sea crustaceans is crucial in understanding the ecological roles and interactions of deep-sea organisms as they play a critical role in deep-sea food webs as intermediate trophic level organisms. This study provides the first examination of the feeding ecology of deep-sea shrimp Plesionika semilaevis (Spence Bate 1888) and provides new insights into deep-sea community structure. An aggregate number of 2213 individuals (842 males, 1016 berried and 355 non-berried females) were collected from the South Eastern Arabian Sea from 2019 to 2022 and their feeding ecology was studied in relation to the environmental (season) and biological (maturity, sex and size) factors. The index of preponderance values indicates the species has a diversified diet with a wide trophic niche ranging from smaller foraminifera to larger crustaceans and fishes. Frequency of occurrence (FOC) reveals that crustaceans, detritus and foraminifera forms the main prey while fishes, molluscs and sponges form the secondary prey. Berried females had the highest feeding intensity compared to males and non-berried females. Among the studied groups,the percentage of full stomachs was higher during the pre-monsoon period than post-monsoon. Feeding intensity was highest for smaller individuals and decreased gradually with an increase in size. Statistical analyses (ANOVA) also confirmed the significant differences (p<0.05) in the diet composition and feeding intensity of berried and non-berried females, pre-monsoon and post-monsoon samples and, juveniles and adults. The PERMANOVA test showed that there were significant differences in diet in the interaction between sex and size (p=0.003) and between sex and season (p=0.001). The present study also suggests that the seasonal variation in feeding intensity could be attributed to oceanographic phenomena like upwelling prevailing in the South Eastern Arabian Sea.

High-Resolution Model of Clew Bay—Model Set-Up and Validation Results

Clew Bay is an important aquaculture production area in Ireland. In this study, we focused on a high-resolution simulation of the Clew Bay region based on a regional ocean modeling system (ROMS). Freshwater discharges from eight rivers are included in the model and a wetting–drying scheme has been implemented. The Clew Bay model simulation was validated and calibrated with available observations (e.g., acoustic Doppler current profiler (ADCP), vertical salinity and temperature profiles, and a tide gauge) in the geographic area of the model domain. High correlations were found between the model data and observed temperature, salinity and water levels, along with small root mean square errors. This indicates that the model is able to reproduce the oceanographic phenomena in the study area. The Taylor diagram analysis showed a high correlation coefficient (R = 0.99) between the observed bottom temperature in the Inner Bay and Clew Bay model, along with a small centered root mean square error (RMSD = 0.5 °C). High correlation coefficients (R &gt; 0.80) were found between the model and the two ADCPs for the zonal current component. There was a resemblance in structure between the model and the observed salinity profiles, indicating that freshwater was correctly implemented in the model. Moreover, the correlation coefficient between the model and the tidal sea surface height (SSH) was 0.99, with an RMSD of 0.09 m. We discovered that wind direction and speed had a significant impact on the bay’s water inflow rate. The model outputs can be used to provide scientists, fishermen, and decision-makers with hydrodynamic information on ocean conditions in the bay.

Tomographic reconstruction of 3D sound speed fields to reveal internal tides on the continental slope of the South China Sea

Mirror-type coastal acoustic tomography (MCAT) is an advancement of coastal acoustic tomography (CAT) with a mirror function that enables the nearshore transmission of offshore observation data. Subsurface MCATs are used to monitor small-scale oceanographic phenomena over large areas on the continental slope of the South China Sea (300–1,000 m). This study investigated the performance of MCAT network observation for internal tide monitoring using 3D tomographic inversion. MCAT facilitates communication with each other and is networked. Results of 3D tomographic inversion were highly consistent with the Stanford unstructured nonhydrostatic terrain-following adaptive Navier–Stokes (SUNTANS) model data. The root-mean-square difference of the sound speed obtained by the inversion method was&amp;lt; 1.0 m/s. The high sound speeds induced by the internal tide were well captured by the results of 3D inversion. A high sound speed band of &amp;gt; 1,516 m/s was used as an index of internal tides, which propagated at a speed of 1.9 m/s. Sensitivity experiments demonstrated that a swing of the anchor tether of&amp;lt; 5 m had less impact on sound speed inversion, while distance drifts caused by human activities of &amp;gt; 50 m had a significant influence. The missing of one or several stations owing to natural factors did not generate significant variations in the results of network observation. This study demonstrated that the MCAT network observation strategy, equipped with numerous stations, is more effective in capturing the characteristics of internal tides.

After Two Decades, Argo at PMEL, Looks to the Future

The NOAA Pacific Environmental Laboratory (PMEL) has contributed to the revolutionary Argo ocean observing system since its inception, developing CTD calibration algorithms and software that have been adopted by the international Argo community. PMEL has provided over 1,440 Argo floats—~13% of the global array—with ~500 currently active. PMEL scientific contributions using Argo data have ranged from regional to global analyses of ocean circulation and water-mass variability, to ocean warming and its contributions to sea level rise and Earth’s energy imbalance, to estimates of global ocean deoxygenation. In recent years, PMEL has initiated both Deep Argo (with a regional pilot array of full-ocean-depth profiling floats in the rapidly changing and dynamic western South Atlantic) and Biogeochemical (BGC) Argo (with a pilot array in the biogeochemically diverse and economically important California Current Large Marine Ecosystem). PMEL is also developing innovative near-global maps of ocean physical and biogeochemical parameters using machine learning algorithms that enable investigations of societally important oceanographic phenomena, and an Adopt-A-Float program. Future challenges include growing the financial, infrastructure, and human resources necessary to take the Deep and BGC Argo missions global and to fulfill the One Argo mission of a global, full-depth, multidisciplinary ocean observing array.

MarineMetagenomeDB: a public repository for curated and standardized metadata for marine metagenomes

BackgroundMetagenomics is an expanding field within microbial ecology, microbiology, and related disciplines. The number of metagenomes deposited in major public repositories such as Sequence Read Archive (SRA) and Metagenomic Rapid Annotations using Subsystems Technology (MG-RAST) is rising exponentially. However, data mining and interpretation can be challenging due to mis-annotated and misleading metadata entries. In this study, we describe the Marine Metagenome Metadata Database (MarineMetagenomeDB) to help researchers identify marine metagenomes of interest for re-analysis and meta-analysis. To this end, we have manually curated the associated metadata of several thousands of microbial metagenomes currently deposited at SRA and MG-RAST.ResultsIn total, 125 terms were curated according to 17 different classes (e.g., biome, material, oceanic zone, geographic feature and oceanographic phenomena). Other standardized features include sample attributes (e.g., salinity, depth), sample location (e.g., latitude, longitude), and sequencing features (e.g., sequencing platform, sequence count). MarineMetagenomeDB version 1.0 contains 11,449 marine metagenomes from SRA and MG-RAST distributed across all oceans and several seas. Most samples were sequenced using Illumina sequencing technology (84.33%). More than 55% of the samples were collected from the Pacific and the Atlantic Oceans. About 40% of the samples had their biomes assigned as ‘ocean’. The ‘Quick Search’ and ‘Advanced Search’ tabs allow users to use different filters to select samples of interest dynamically in the web app. The interactive map allows the visualization of samples based on their location on the world map. The web app is also equipped with a novel download tool (on both Windows and Linux operating systems), that allows easy download of raw sequence data of selected samples from their respective repositories. As a use case, we demonstrated how to use the MarineMetagenomeDB web app to select estuarine metagenomes for potential large-scale microbial biogeography studies.ConclusionThe MarineMetagenomeDB is a powerful resource for non-bioinformaticians to find marine metagenome samples with curated metadata and stimulate meta-studies involving marine microbiomes. Our user-friendly web app is publicly available at https://webapp.ufz.de/marmdb/.

Revealing coastal upwelling impact on the muscle growth of an intertidal fish

Upwelling oceanographic phenomenon is associated with increased food availability, low seawater temperature and pH. These conditions could significantly affect food quality and, in consequence, the growth of marine species. One of the most important organismal traits is somatic growth, which is highly related to skeletal muscle. In fish, skeletal muscle growth is highly influenced by environmental factors (i.e. temperature and nutrient availability) that showed differences between upwelling and downwelling zones. Nevertheless, there are no available field studies regarding the impact of those conditions on fish muscle physiology. This work aimed to evaluate the muscle fibers size, protein content, gene expression of growth and atrophy-related genes in fish sampled from upwelling and downwelling zones. Seawater and fish food items (seaweeds) samples were collected from upwelling and downwelling zones to determine the habitat's physical-chemical variations and the abundance of biomolecules in seaweed tissue. In addition, white skeletal muscle samples were collected from an intertidal fish to analyze muscular histology, the growth pathways of protein kinase B and the extracellular signal-regulated kinase; and the gene expression of growth- (insulin-like growth factor 1 and myosin heavy-chain) and atrophy-related genes (F-box only protein 32 and muscle RING-finger protein-1). Upwelling zones revealed higher nutrients in seawater and higher protein content in seaweed than samples from downwelling zones. Moreover, fish from upwelling zones presented a greater size of muscle fibers and protein content compared to downwelling fish, associated with lower protein ubiquitination and gene expression of F-box only protein 32. Our data indicate an attenuated use of proteins as energy source in upwelling conditions favoring protein synthesis and muscle growth. This report shed lights of how oceanographic conditions may modulate food quality and fish muscle physiology in an integrated way, with high implications for marine conservation and sustainable fisheries management.

Rapid spin up and spin down of flow along slopes

Abstract The near-bottom mixing that allows abyssal waters to upwell tilts isopycnals and spins up flow over the flanks of mid-ocean ridges. Meso- and large-scale currents along sloping topography are subjected to a delicate balance of Ekman arrest and spin down. These two seemingly disparate oceanographic phenomena share a common theory, which is based on a one-dimensional model of rotating, stratified flow over a sloping, insulated boundary. This commonly used model, however, lacks rapid adjustment of interior flows, limiting its ability to capture the full physics of spin up and spin down of along-slope flow. Motivated by two-dimensional dynamics, the present work extends the one-dimensional model by constraining the vertically integrated cross-slope transport and allowing for a barotropic cross-slope pressure gradient. This produces a closed secondary circulation by forcing Ekman transport in the bottom boundary layer to return in the interior. The extended model can thus capture Ekman spin up and spin down physics: the interior return flow is turned by the Coriolis acceleration, leading to rapid rather than slow diffusive adjustment of the along-slope flow. This transport-constrained one-dimensional model accurately describes twodimensional mixing-generated spin up over an idealized ridge and provides a unified framework for understanding the relative importance of Ekman arrest and spin down of flow along a slope.

Seascape genomics of common dolphins (Delphinus delphis) reveals adaptive diversity linked to regional and local oceanography

BackgroundHigh levels of standing genomic variation in wide-ranging marine species may enhance prospects for their long-term persistence. Patterns of connectivity and adaptation in such species are often thought to be influenced by spatial factors, environmental heterogeneity, and oceanographic and geomorphological features. Population-level studies that analytically integrate genome-wide data with environmental information (i.e., seascape genomics) have the potential to inform the spatial distribution of adaptive diversity in wide-ranging marine species, such as many marine mammals. We assessed genotype-environment associations (GEAs) in 214 common dolphins (Delphinus delphis) along > 3000 km of the southern coast of Australia.ResultsWe identified 747 candidate adaptive SNPs out of a filtered panel of 17,327 SNPs, and five putatively locally-adapted populations with high levels of standing genomic variation were disclosed along environmentally heterogeneous coasts. Current velocity, sea surface temperature, salinity, and primary productivity were the key environmental variables associated with genomic variation. These environmental variables are in turn related to three main oceanographic phenomena that are likely affecting the dispersal of common dolphins: (1) regional oceanographic circulation, (2) localised and seasonal upwellings, and (3) seasonal on-shelf circulation in protected coastal habitats. Signals of selection at exonic gene regions suggest that adaptive divergence is related to important metabolic traits.ConclusionTo the best of our knowledge, this represents the first seascape genomics study for common dolphins (genus Delphinus). Information from the associations between populations and their environment can assist population management in forecasting the adaptive capacity of common dolphins to climate change and other anthropogenic impacts.