Ocean Circulation Research Articles

Machine learning models to predict rare earth elements distribution in Tethyan phosphate ore deposits: Geochemical and depositional environment implications

The global market for rare earth elements (REE) is growing rapidly, driven by rising demand and limited production sources, prompting interest in recovering REE from secondary sources such as phosphate deposits. The Tethyan belt, extending across North Africa and the Middle East contains substantial Upper Cretaceous to Eocene REE-rich phosphorite deposits but with limited geochemical data available. This study provides a novel machine-learning (ML) method to predict REE contents in these deposits and verify a useful geochemical classification based on the concentrations of nine major element oxides. Four ML models are developed to achieve this: eXtreme Gradient Boosting (XGBoost), Random Forest (RF), Support Vector Regression (SVR), and Decision Tree (DT). The datasets are divided geochemically into oxic and sub-oxic patterns and these are evaluated with the ML models separately and in combination to accurately predict light REE (LREE), heavy REE (HREE), and total REE contents (∑REE). For the oxic pattern dataset, Fe2O3 and K2O exhibit the highest feature importance consistent with a glauconite influence. For the sub-oxic pattern dataset, MnO and SiO2 exhibit the highest feature importance consistent with high terrigenous inputs (MnO), and silicification. The ML results support the importance of the local deposition environment in determining REE distributions in these deposits. Paleogeography, ocean-margin tectonics, sea-level oscillations, and marine currents exert influence on the local depositional environments. The eXtreme Gradient Boosting model generates the lowest REE prediction errors for all the datasets evaluated.

Impact of surface current and temperature feedback on kinetic energy over the North-East Atlantic from a coupled ocean / atmospheric boundary layer model

A one-dimensional Atmospheric Boundary Layer (ABL1D) model is coupled with the NEMO ocean model and implemented over the Iberian–Biscay–Ireland (IBI) area at 1/36° resolution to investigate the damping effect of the current and the thermal feedback on the kinetic energy (KE) at the mesoscale. This type of coupling between an ocean model and an ABL1D is a newly proposed approach as an alternative of intermediate complexity between bulk forcing and full coupling with an atmosphere model. In ABL1D, the prognostic tracers are nudged toward large-scale variables and the wind is guided by a low-frequency geostrophic wind provided from the ERA-Interim reanalyses.First, the ABL1D is successfully validated against satellite observations regarding the wind, and the dynamic coupling coefficient (linking the near surface wind and wind-stress to the curl of the surface currents) are consistent with the literature, over the period 2016-2017. Our results show that the thermal feedback has a negligible impact on kinetic energy (KE) and does not influence the strength of the current feedback in the region. Given the ABL1D physics, this further indicates that the changes in the vertical wind structure caused by CFB are primarily governed by local mechanical mechanisms associated with surface wind-stress condition, rather than by thermodynamic or non-local processes within the planetary boundary layer.The induced KE reduction by the current feedback amounts to 14% at the surface and propagates down to 2000 m, indicating that it can modify the vertical distribution of KE throughout the water column. KE reductions in the surface boundary layer (0 – 300m) and in the interior (300 – 2000m) are attributed to a reduction of the surface wind work by 4%, and of the pressure work by 7%, respectively. The Ekman pumping anomalies induced by the current feedback tend to attenuate eddy activity and horizontal pressure gradients at depth, illustrating the potential of the current feedback to induce a geostrophic adjustment on the water column. These results illustrate the relevance of the proposed ABL1D coupling approach for reproducing the wind-current coupling (a.k.a. current feedback effect) which cannot be taken into account straightforwardly with simple bulk forcing.

Lagrangian surface drifter observations in the North Sea: an overview of high-resolution tidal dynamics and surface currents

Abstract. A dataset of 85 Lagrangian surface drifter trajectories covering the central North Sea area and the Skagerrak from 2017–2021 of 17 deployments is presented. The data have been quality-controlled, uniformly structured, and assimilated in a standard NetCDF format (https://doi.org/10.1594/PANGAEA.963166, Meyerjürgens et al., 2023a). Using appropriate methods presented in detail here, surface currents were calculated from the drifter position data. Based on a drifter deployment in the Skagerrak, it is demonstrated that the Lagrangian measurements can be converted into an Eulerian representation by calculating mean current velocities. Tidal energy spectra were analyzed separately for the southern and northern areas of the North Sea, and tidal ellipses were calculated to determine the tidal impact on surface currents. Significant differences between the shallow shelf and the deeper areas of the North Sea are evident. While the shallow nearshore areas are dominated by tidal currents, deeper areas such as the Skagerrak record a high mean residual circulation driven by high-density gradients. Measurements using Eulerian approaches and remote sensing methods are restricted in temporal and spatial coverage, in particular, to capture fine-scale dynamics. For this reason, Lagrangian measurements, to a large extent, provide new insights into the complex submesoscale dynamics of the North Sea. Exemplarily, the Skagerrak region is used to demonstrate that high-resolution drifter observations capture both mesoscale and small-scale current patterns. This unique dataset, covering the entire southeastern North Sea and the Skagerrak, offers further analysis possibilities and can be used for the investigation of various hydrodynamic and environmental issues, e.g., the analysis of submesoscale current dynamics at ocean fronts, the determination of the kinetic eddy energy, and the propagation of pollutants in the North Sea.

The annual update GLODAPv2.2023: the global interior ocean biogeochemical data product

Abstract. The Global Ocean Data Analysis Project (GLODAP) is a synthesis effort providing regular compilations of surface to bottom ocean biogeochemical bottle data, with an emphasis on seawater inorganic carbon chemistry and related variables determined through chemical analysis of seawater samples. GLODAPv2.2023 is an update of the previous version, GLODAPv2.2022 (Lauvset et al., 2022). The major changes are as follows: data from 23 new cruises were added. In addition, a number of changes were made to the data included in GLODAPv2.2022. GLODAPv2.2023 includes measurements from more than 1.4 million water samples from the global oceans collected on 1108 cruises. The data for the now 13 GLODAP core variables (salinity, oxygen, nitrate, silicate, phosphate, dissolved inorganic carbon, total alkalinity, pH, chlorofluorocarbon-11 (CFC-11), CFC-12, CFC-113, CCl4, and SF6) have undergone extensive quality control with a focus on the systematic evaluation of bias. The data are available in two formats: (i) as submitted by the data originator but converted to World Ocean Circulation Experiment (WOCE) exchange format and (ii) as a merged data product with adjustments applied to minimize bias. For the present annual update, adjustments for the 23 new cruises were derived by comparing those data with the data from the 1085 quality-controlled cruises in the GLODAPv2.2022 data product using crossover analysis. SF6 data from all cruises were evaluated by comparison with CFC-12 data measured on the same cruises. For nutrients and ocean carbon dioxide (CO2), chemistry comparisons to estimates based on empirical algorithms provided additional context for adjustment decisions. The adjustments that we applied are intended to remove potential biases from errors related to measurement, calibration, and data-handling practices without removing known or likely time trends or variations in the variables evaluated. The compiled and adjusted data product is believed to be consistent to better than 0.005 in salinity, 1 % in oxygen, 2 % in nitrate, 2 % in silicate, 2 % in phosphate, 4 µmol kg−1 in dissolved inorganic carbon, 4 µmol kg−1 in total alkalinity, 0.01–0.02 in pH (depending on region), and 5 % in the halogenated transient tracers. The other variables included in the compilation, such as isotopic tracers and discrete CO2 fugacity (fCO2), were not subjected to bias comparison or adjustments. The original data, their documentation, and DOI codes are available at the Ocean Carbon and Acidification Data System of NOAA National Centers for Environmental Information (NCEI), which also provides access to the merged data product. This is provided as a single global file and as four regional ones – the Arctic, Atlantic, Indian, and Pacific oceans – under https://doi.org/10.25921/zyrq-ht66 (Lauvset et al., 2023). These bias-adjusted product files also include significant ancillary and approximated data, which were obtained by interpolation of, or calculation from, measured data. This living data update documents the GLODAPv2.2023 methods and provides a broad overview of the secondary quality control procedures and results.

Holocene sedimentary distribution and morphological characteristics reworked by East Asian monsoon dynamics in the Mekong River shelf, South Vietnam

The distribution of Holocene sediments in the Mekong River shelf area was investigated using shallow seismic and core data. The results show that the shelf depositional stratigraphy since the last glacial period can be classified into four depositional units (U1, U2, U3 and U4). The average thickness of the Holocene deposit in the nearshore area of the Mekong River estuary is approximately 20 m and decreases seaward. In addition to a thickened deposit in the palaeo-river channel, two sedimentary centres have developed, namely, the Mekong River estuary and the Cape Ca Mau area. In contrast to nearshore deposition, the Holocene sedimentation rate rapidly decreased offshore, even in the transgressive systems tract. To understand the driving mechanisms for the variation in Holocene deposition, a three-dimensional numerical model and Geographic Information System(GIS)-based model were applied to reconstruct the oceanographic and sediment transport patterns on the South Vietnam shelf. The simulation results reveal that the Mekong River shelf has undergone significant transformations since the Last Glacial Maximum (LGM). During the LGM, the coastline was situated near the shelf break, and as the sea level rose rapidly, the shoreline retreated. When the sea level reached its peak, the modern Mekong Delta emerged. Furthermore, the distribution of Holocene deposits is controlled by monsoon-influenced seasonal variations in currents, resulting in a triangular delta and narrow strip-like subaqueous clinoform. Our simulation results also show obvious erosional capacity in the offshore area, leading to an evident erosional through to the east of Cape Ca Mau and erosion of Pleistocene sediments in the shelf break area. By combining stratigraphic interpretation and oceanographic simulations, our study provides new insights into sediment transport and erosion processes mediated by ocean currents driven by East Asian monsoons.

Arrival of crocodilians to São Tomé Island, Gulf of Guinea, Western Africa, highlights the role of sea currents to the natural colonization of islands

Abstract Historical and recent arrivals of crocodilians to the Gulf of Guinean Oceanic Island of São Tomé have intrigued naturalists for several centuries. Here we present the revision of the historical records, and present data regarding the recent arrival of a single specimen in 2021. After being killed by the local authorities, the specimen was preserved and studied both through morphological and molecular methods. Our findings suggest that the specimen was a sub-adult Nile crocodile, Crocodylus niloticus Laurenti, 1768, which most likely drifted from the Congo or Ogooué river mouths in West Africa by the oceanic current acting on the Gulf of Guinea. The story of this individual highlights the dispersion paths that have contributed by the past biological colonization of São Tomé Island.

Intercomparisons of Tracker v1.1 and four other ocean particle-tracking software packages in the Regional Ocean Modeling System

Abstract. Particle tracking is widely utilized to study transport features in a range of physical, chemical, and biological processes in oceanography. In this study, a new offline particle-tracking package, Tracker v1.1, is introduced, and its performance is evaluated in comparison to an online Eulerian dye, one online particle-tracking software package, and three offline particle-tracking software packages in a small, high-resolution model domain and a large coarser model domain. It was found that both particle and dye approaches give similar results across different model resolutions and domains when they were tracking the same water mass, as indicated by similar mean advection pathways and spatial distributions of dye and particles. The flexibility of offline particle tracking and its similarity against online dye and online particle tracking make it a useful tool to complement existing ocean circulation models. The new Tracker was shown to be a reliable particle-tracking package to complement the Regional Ocean Modeling System (ROMS) with the advantages of platform independence and speed improvements, especially in large model domains achieved by the nearest-neighbor search algorithm. Lastly, trade-offs of computational efficiency, modifiability, and ease of use that can influence the choice of which package to use are explored. The main value of the present study is that the different particle and dye tracking codes were all run on the same model output or within the model that generated the output. This allows some measure of intercomparison between the different tracking schemes, and we conclude that all choices that make each tracking package unique do not necessarily lead to very different results.

Assessment of the Added Value of the GOCE GPS Data on the GRACE Monthly Gravity Field Solutions

The time-varying gravity field models derived from the Gravity Recovery and Climate Experiment (GRACE) satellite mission suffer from pronounced longitudinal stripe errors in the spatial domain. A potential way to mitigate such errors is to combine GRACE data with observations from other sources. In this study, we investigate the impacts on GRACE monthly gravity field solutions of incorporating the GPS data collected by the Gravity Field and Steady-State Ocean Circulation Explorer (GOCE) mission. To that end, we produce GRACE/GOCE combined monthly gravity field solutions through combination on the normal equation level and compare them with the GRACE-only solutions, for which we have considered the state-of-the-art ITSG-Grace2018 solutions. Analysis in the spectral domain reveals that the combined solutions have a notably lower noise level beyond degree 30, with cumulative errors up to degree 96 being reduced by 31%. A comparison of the formal errors reveals that the addition of GOCE GPS data mainly improves (near-) sectorial coefficients and resonant orders, which cannot be well determined by GRACE alone. In the spatial domain, we also observe a significant reduction by at least 30% in the noise of recovered mass changes after incorporating the GOCE GPS data. Furthermore, the signal-to-noise ratios of mass changes over 180 large river basins were improved by 8–20% (dependent on the applied Gaussian filter radius). These results demonstrate that the GOCE GPS data can augment the GRACE monthly gravity field solutions and support a future GOCE-type mission for tracking more accurate time-varying gravity fields.

Temperature Structure Inversion of Mesoscale Eddies in the South China Sea Based on Deep Learning

Mesoscale eddies are common in global oceans, playing crucial roles in ocean dynamics, ocean circulation, and heat transport, and their vertical structures can affect the water layers from tens to thousands of meters. In this study, we integrated sea surface height and sea surface temperature data into deep learning methods to study the mesoscale eddy subsurface temperature structure and to explore the relationship between sea surface data and eddy subsurface layers. In this study, we introduce Dual_EddyNet, a deep learning algorithm designed to invert the subsurface temperature structure of mesoscale eddies. Using this algorithm, we explore the impact of the sea surface height and sea surface temperature on the subsurface temperature structure inversion of mesoscale eddies. Furthermore, we compare different data fusion strategies, namely single-stream neural networks and dual-stream neural networks, to validate the effectiveness of the dual-stream model. To capture the interrelations among surface data and integrate feature information across various dimensions, we introduce the Triplet Attention Mechanism. The experimental results demonstrate that the proposed Dual_EddyNet performs well in reconstructing the three-dimensional structure of mesoscale eddies in the South China Sea (within a depth of 1000 m), with an inversion accuracy of 91.44% for cyclonic eddies and 95.25% for anticyclonic eddies. This algorithm provides a new method for inverting the subsurface temperatures of mesoscale eddies, and can not only be directly deployed in systems, embedded in ship moving platforms, etc., but can also provide a data reference for assimilations and numerical simulations, demonstrating its rich application potential.

Interacciones tierra-mar-tierra, con énfasis en la actividad pesquera en la región norte del Ecosistema Costero Bonaerense, Argentina

[Introduction]: Coastal areas constitute the interface between land and marine environments, connected through multiple natural and socioecological processes that contribute to human well-being. [Objective]: Identify land and marine uses and activities with mutual implications and biophysical processes in the northern region of the Bonaerense Coastal Ecosystem (Argentina), in order to evaluate the degree of compatibility or conflict between these activities, with emphasis on the fishing activity. [Methodology]: The land-sea-land (T-M-T) methodological analysis was applied. Uses and activities (U&A) and biophysical processes of marine and land origin were determined. Interactions between marine-land and biophysical processes T-M-T were identified for further categorization and analysis. [Results]: A total of 121 U&A sea-land-sea (L-S-L) interactions related to fishing were detected. Medium conflicts were mainly caused by competition for space or resources and were associated with the coexistence of U&A (tourism, fishing, and communication activities), both spatially and temporally. Of the total, 68 negative interactions were observed between biophysical processes and U&A L-S-L, which were linked to climatic events and the effects of climate change (variation in sea surface temperature, atmospheric and oceanic circulation, as well as variations in sediment transport and coastal erosion). [Conclusions]: The analysis carried out constitutes an advancement in the study of U&A T-M-T in coastal-marine areas of the Atlantic coast and their interactions, with emphasis on fishing activities, as a contribution to their management with an ecosystemic approach.

Surface current prediction based on a physics-informed deep learning model

Sea surface current is an important factor that affects various aspects of oceanic climate, energy, and shipping. Traditional methods for simulating current based on ocean dynamic equations are computationally complex, while existing data-driven deep learning methods overlook the constraints of actual physical processes, limiting the further improvement of prediction accuracy. In this paper, we address the issue of sea surface current prediction by proposing a deep learning model that incorporates physical processes. The model combines physical information with deep learning techniques to overcome the limitations of low computational efficiency in numerical models and the lack of interpretability in data-driven deep learning methods. This integration allows us to improve the prediction accuracy of sea surface current. Furthermore, we propose a weighted loss function into the model to address the challenge of accurately predicting high-magnitude current. The research results demonstrate that our proposed prediction model for sea surface current outperforms the baseline model, particularly in predicting high-magnitude current. Simultaneously, the model demonstrates favorable generalization performance and lower data dependency. This paper provides a new and effective method and strategy for sea surface current prediction.

Bacterial magnetofossil evidence for enhanced Pacific Ocean respired carbon storage during buildup of Antarctic glaciation

Global cooling with the onset of Antarctic glaciation ca. 34 Ma across the Eocene–Oligocene transition (EOT) terminated the early Cenozoic greenhouse climate state and marked the beginning of icehouse conditions. Although a pCO2 decline is considered to have been a major cause of this climate shift, the associated carbon-sequestration mechanism remains unclear. Here, we assessed ocean production and circulation changes across the EOT using numerical simulations combined with a novel proxy, namely, bacterial magnetofossils, the abundance and morphology of which are sensitive to sedimentary organic matter accumulation and oxygenation. We detected production and oxygenation declines in the equatorial Pacific Ocean coeval with increased biological production in the Southern Ocean after the EOT. Corroborated by simulation results and evidence from the Subantarctic region, we interpret this counterintuitive combination as a result of enhanced bottom-water formation and biological pump efficiency in the Southern Ocean due to Antarctic glacial buildup across the EOT. These results provide key evidence for deep Pacific Ocean deoxygenation and increased respired carbon concentrations, which amplified CO2 decline across the EOT.

Hydrologic cycle weakening in hothouse climates.

The hydrologic cycle has wide impacts on the ocean salinity and circulation, carbon and nitrogen cycles, and the ecosystem. Under anthropogenic global warming, previous studies showed that the intensification of the hydrologic cycle is a robust feature. Whether this trend persists in hothouse climates, however, is unknown. Here, we show in climate models that mean precipitation first increases with rising surface temperature, but the precipitation trend reverses when the surface is hotter than ~320 to 330 kelvin. This nonmonotonic phenomenon is robust to the cause of warming, convection scheme, ocean dynamics, atmospheric mass, planetary rotation, gravity, and stellar spectrum. The weakening occurs because of the existence of an upper limitation of outgoing longwave emission and the continuously increasing shortwave absorption by H2O and is consistent with atmospheric dynamics featuring the strong increase of atmospheric stratification and marked reduction of convective mass flux. These results have wide implications for the climate evolutions of Earth, Venus, and potentially habitable exoplanets.

Design of a broadband multifunctional switchable absorber/reflector based on active frequency selective surfaces

Metamaterial absorbers are candidates for stealth systems due to their excellent wave modulation capabilities. With the rapid development of radar detection technology, the switching ability of metamaterial absorbers is becoming more demanding. A broadband multifunctional switchable absorber/reflector based on active frequency selective surfaces (AFSS) is presented in this paper. The proposed structure comprises an absorbing layer, a switching layer, and a ground with air spacers sandwiched between each layer. The PIN diodes can realize significant broadband conditioning performance between absorption and reflection functions by switching four operating states: ‘00’, ‘01’, ‘10’, and ‘11’. The bias network of this structure features horizontal and vertical configurations that independently coordinate the two polarization directions. It is worth noting that the bias network of the designed structure is very simple to minimize the impact on the structure. Distributions of surface current, an equivalent circuit model, and structural parameters are analyzed for a better professional insight into the working mechanism of the absorber/reflector. Finally, a prototype is fabricated and measured to verify the simulation.

Miocene vanishing of the Central American Seaway between the Panamá Arc and the South American Plate

A controversy has developed in recent years regarding the timing of the closure of the Central American Seaway. This tectonic event significantly impacted oceanic circulation between the tropical Pacific and Atlantic oceans and resulted in the formation of a land bridge connecting the South and North American continents. The long-held view of a Pliocene age (ca. 3 Ma) for the closure of the Central American Seaway has been challenged by the proposal that the Panamá Arc collided with South America during the Middle Miocene (15−13 Ma) as a deep oceanic gap between them closed along the Uramita suture zone. However, direct geologic evidence from this suture zone to support either interpretation has been lacking. Here, we report on a comprehensive study of three stratigraphic transects across the Uramita suture zone, using a host of methodologies including sedimentological, ichnological, micropaleontological, U-Pb detrital geochronological, and provenance analyses. Our data reveal that lower offshore to slope conditions prevailed in the Central American Seaway along the suture zone during the latest Early to earliest Middle Miocene (16.4−15.1 Ma) and that oceanic conditions there ceased to exist between the Middle and Late Miocene. These results agree with the Middle Miocene age proposed for the Central American Seaway closure along the tectonic boundary. However, other deeper portions of the Central American Seaway persisted in western Colombia, which challenges the notion of a Central American Seaway confined to the suture zone between the Panamá Arc and South American Plate during the Middle Miocene.

Machine Learning Based Modeling of Thermospheric Mass Density

AbstractIn this study, we propose a machine learning based approach to construct an empirical model of thermospheric mass densities, based on the MultiLayer Perceptron and bi‐directional Long Short‐Term Memory for ensemble learning model (MBiLE). The MBiLE model was trained by using only the thermospheric mass density from Swarm C satellite at ∼450 km altitude. To assess the performance of the MBiLE model, the model predictions were compared with observations from several satellites, namely, the Swarm C, the Challenging Minisatellite Payload (CHAMP) and the Gravity Field and Steady‐State Ocean Circulation Explorer (GOCE) satellites. The determination coefficients (R2) for the three satellites are 0.98, 0.99, and 0.98, respectively. The MBiLE model predicts the thermospheric mass density well not only at Swarm C altitude but also at lower altitudes. Earlier empirical models based on multivariate least‐square‐fitting approach failed to achieve this good altitude generalization (e.g., Liu et al., 2013, https://doi.org/10.1002/jgra.50144; Xiong et al., 2018a, https://doi.org/10.5194/angeo‐2018‐25). Further tests have been made by checking the MBiLE model prediction deviations in relation to magnetic local time, day of year, solar flux level, and magnetic activities. No obvious dependences are found for these parameters. Comparing with the NRLMSIS‐2.0 model, the MBiLE model improves prediction accuracy by 91%, 66%, and 56% at the three satellites altitudes. The results indicate that the MBiLE model has the ability to predict well the thermospheric mass density over a wide altitude range, for example, from 224 to 528 km, offering potential for atmospheric research applications.

Combining population genomics and biophysical modelling to assess connectivity patterns in an Antarctic fish.

Connectivity is a fundamental process of population dynamics in marine ecosystems. In the last decade, with the emergence of new methods, combining different approaches to understand the patterns of connectivity among populations and their regulation has become increasingly feasible. The Western Antarctic Peninsula (WAP) is characterized by complex oceanographic dynamics, where local conditions could act as barriers to population connectivity. Here, the notothenioid fish Harpagifer antarcticus, a demersal species with a complex life cycle (adults with poor swim capabilities and pelagic larvae), was used to assess connectivity along the WAP by combining biophysical modelling and population genomics methods. Both approaches showed congruent patterns. Areas of larvae retention and low potential connectivity, observed in the biophysical model output, coincide with four genetic groups within the WAP: (1) South Shetland Islands, (2) Bransfield Strait, (3) the central and (4) the southern area of WAP (Marguerite Bay). These genetic groups exhibited limited gene flow between them, consistent with local oceanographic conditions, which would represent barriers to larval dispersal. The joint effect of geographic distance and larval dispersal by ocean currents had a greater influence on the observed population structure than each variable evaluated separately. The combined effect of geographic distance and a complex oceanographic dynamic would be generating limited levels of population connectivity in the fish H. antarcticus along the WAP. Based on this, population connectivity estimations and priority areas for conservation were discussed, considering the marine protected area proposed for this threatened region of the Southern Ocean.

The impact of construction of detached breakwaters on wave system and sea currents

The impact of construction of detached breakwaters on wave system and sea currents

Seaweed diversification driven by Taiwan’s emergence and the Kuroshio Current: insights from the cryptic diversity and phylogeography of Dichotomaria (Galaxauraceae, Rhodophyta)

Ocean currents play a role in both facilitating and impeding connectivity of marine organisms’ populations, serving as key drivers and potential barriers. The emergence of Taiwan around five million years ago (Mya) impacted the Kuroshio Current which later shaped the distribution of marine organisms. In this study, we examined how the Kuroshio Current influenced the distribution and population divergence of the marine red alga Dichotomaria elegans (Galaxauraceae, Nemaliales). Through phylogenetic analysis, species delimitation, and morphological comparison of Taiwanese species, we determined its phylogenetic position relative to other species within the D. marginata complex of the genus Dichotomaria. We uncovered the hidden cryptic diversity within the D. marginata complex in Taiwan and proposed the new combinations D. elegans and D. latifolia based on Galaxaura elegans and G. latifolia. Genetic analysis based on three loci (mitochondrial cox2-3 and cox1, and plastid rbcL) from 32 locations across the Philippines, Taiwan, and Japan revealed three allopatric lineages within D. elegans. The first lineage is restricted to the northern Philippines and southern Taiwan, while the second has a broader latitudinal range along the Kuroshio Current. The third lineage is found in southeast Luzon, Philippines, close to the bifurcation of the North Equatorial Current, near the start of the Kuroshio Current. The divergence of the first two lineages during the mid-Pliocene (~3.7 Mya) coincided with the emergence of Taiwan, with the current dynamics accentuating their separation. The Kuroshio Current exhibited a dual impact on the biogeography of D. elegans: promoting the dispersal of the second lineage towards higher latitudes and preventing the first lineage from moving northward. Principal component analysis showed that habitat conditions and morphologies differed between the two D. elegans lineages. This study provides insights into the cryptic diversity of Dichotomaria in Taiwan, as well as the genetic divergence, biogeographical patterns, and ecological associations of D. elegans, highlighting the interplay of island formation and currents shaping the diversification of seaweeds in the Northwest Pacific Ocean.

Sparus Docking Station: A current aware docking station system for a non‐holonomic AUV

AbstractThis paper presents the design and development of a funnel‐shaped Sparus Docking Station intended for the non‐holonomic torpedo‐shaped Sparus II Autonomous Underwater Vehicle. The Sparus Docking Station is equipped with sensors and batteries, allowing for a stand‐alone long‐term deployment of the vehicle. An inverted Ultra Short Base‐Line system is used to locate the Docking Station as well as to provide long‐term drift‐less vehicle navigation. The Sparus Docking Station is able to observe the ocean currents using a Doppler Velocity Log, being motorized to allow its self‐alignment with the current. Moreover, a docking algorithm accounting for the current is used to guide the robot during the docking maneuver. The paper reports consecutive successful experimental results of the docking maneuver in sea trials in two different countries.