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Ship-hull mediated introduction risk of Colaconema formosanum: barnacle-associated dispersal and ecophysiological potential for coastal establishment
No full textHuman-mediated biological introductions, particularly via ship hull fouling in international maritime transport, present a significant threat to coastal marine ecosystems. Barnacles, despite antifouling measures, often colonize vessel surfaces and may facilitate the cryptic dispersal of epizoic macroalgae. In this study, we isolated and cultured a filamentous red alga from barnacles attached to a commercial vessel hull to clarify its taxonomic identity and assess its ecophysiological traits. Molecular phylogenetic analyses based on rbcL and COI-5P gene regions identified the alga as Colaconema formosanum, a subtropical species previously reported as an endophyte in Taiwan. Laboratory experiments revealed that C. formosanum exhibits optimal growth and photosynthetic performance at 25 degrees C and under high light intensity (100 mu mol photons m(-)2 s(-)1), while maintaining active growth across a wide range of temperature (10-30 degrees C) and light conditions (20-100 mu mol photons m(-)2 s(-)1). These physiological traits suggest strong potential for C. formosanum to establish viable populations along the Korean coastline, especially under warming sea surface temperatures. The role of barnacle fouling in facilitating the covert spread of this alga highlights the need for targeted biosecurity and hull management strategies. Our findings underscore the risk posed by shipping activities in facilitating the potential introduction and invasiveness of subtropical seaweeds in temperate regions.11Nsciescopu
Vertical biochemical composition of particulate organic matter in the Seychelles-Chagos Thermocline Ridge (SCTR), southwestern Indian Ocean
No full textThe Seychelles-Chagos Thermocline Ridge (SCTR) in the southwestern Indian Ocean is characterized by upwelling-driven nutrient enrichment and enhanced biological activity compared to adjacent non-SCTR regions. This study investigated the vertical distribution and biochemical composition of particulate organic matter (POM) within these contrasting environments. The SCTR featured a shallower thermocline and cooler sea surface temperatures, indicative of upwelling, which correlated with significantly higher chlorophyll-a concentrations (t-test, p < 0.05). A notable dominance of micro-sized phytoplankton was observed in the SCTR, contributing 13.6 ± 3.0 % of the total phytoplankton biomass, compared to 5.6 ± 1.6 % in the non-SCTR. CHEMTAX analysis revealed distinct phytoplankton communities, with diatoms being approximately four times more abundant in the SCTR (16.5 ± 4.5 %) than in the non-SCTR (4.2 ± 1.2 %). Meanwhile, Prochlorococcus dominated both regions but contributed less in the SCTR (25.2 ± 3.9 %) than non-SCTR (46.8 ± 7.1 %). The biological macromolecular composition of POM showed clear regional differences, with lipid concentrations in the SCTR's photic layer significantly higher (61.3 μg L−1) than in the non-SCTR (23.4 μg L−1). Total biological macromolecule concentrations in the SCTR's photic zone was more than double that of the non-SCTR (96.3 μg L−1 vs. 40.9 μg L−1), reflecting enhanced biological productivity. Elevated macromolecule concentrations were also detected in the aphotic layer of the SCTR. Notably, the less pronounced decline in the protein-to-carbohydrate ratio from photic to aphotic layers in the SCTR suggests that POM sinking to the deep ocean in this region is relatively fresher and less degraded, indicating a more efficient biological carbon pump and enhanced potential for carbon sequestration. These findings highlight the SCTR as a key region of elevated biological productivity and distinct environmental mechanisms driving biogeochemical cycling, providing critical insights into organic matter preservation and carbon export processes in tropical upwelling systems and their role in global marine ecosystems. © 2025 Elsevier B.V.11Nsciescopu
Geliboluols A–D: Kaurane-Type Diterpenoids from the Marine-Derived Rare Actinomycete Actinomadura geliboluensis
No full textFour new kaurane-type diterpenoids, geliboluols A–D (1–4), along with one known analog (5), were isolated from the culture broth of the marine-derived rare actinomycete Actinomadura geliboluensis. The structures of compounds 1–4 were determined by spectroscopic analysis (HR-ESIMS, 1D, and 2D NMR), the MPA method, and by comparing their optical rotation values with those in the literature. The new compounds were evaluated for their cytotoxicity against seven blood cancer cell lines by a CellTiter-Glo (CTG) assay and six solid cancer cell lines by a sulforhodamine B (SRB) assay. Among the new compounds, compound 4 exhibited moderate cytotoxic activity against some blood cancer cell lines, with GI50 values ranging from 2.59 to 19.64 µM, and against solid cancer cell lines with GI50 values ranging from 4.34 to 7.23 µM.11Ysciescopu
Vibration-Based Anomaly Detection for Induction Motors Using Machine Learning
No full textPredictive maintenance of induction motors continues to be a significant challenge in ensuring industrial reliability and minimizing downtime. In this study, machine learning techniques are utilized to enhance fault diagnosis through the use of the Machinery Fault Database (MAFAULDA). A detailed extraction of statistical features was performed on multivariate time-series data to capture essential patterns that could indicate potential faults. Three machine learning algorithms—deep neural networks (DNNs), support vector machines (SVMs), and K-nearest neighbors (KNNs)—were applied to the dataset. Optimization strategies were carefully implemented along with oversampling techniques to improve model performance and handle imbalanced data. The results achieved through these models are highly promising. The SVM model demonstrated an accuracy of 95.4%, while KNN achieved an accuracy of 92.8%. Notably, the combination of deep neural networks with fast Fourier transform (FFT)-based autocorrelation features produced the highest performance, reaching an impressive accuracy of 99.7%. These results provide a novel approach to machine learning techniques in enhancing operational health and predictive maintenance of induction motor systems.11Ysciescopu
Estimation and Validation of Photosynthetically Available Radiation at the Sea Surface Using GOCI-II Data
No full textPhotosynthetically available radiation (PAR), used in primary productivity research, is calculated from the amount of solar radiation reaching the sea surface in the 400-700 nm wavelength band. This study developed and validated a Geostationary Ocean Color Imager II (GOCI-II)-based PAR algorithm to increase the utilization of GOCI-II and contribute to the production of accurate input data for primary productivity research in the waters around the Korean Peninsula. The algorithms used in MODIS and GOCI PAR studies were improved to suit the spatiotemporal and spectral resolution of GOCI-II, and daily PAR was calculated from GOCI-II hourly PAR. As a result of examining the hourly and daily PAR images on April 27, 2024, it was found that the daily PAR distribution in areas heavily affected by clouds was about 30% lower than in clear atmosphere areas. As a result of validation using ECO-PAR sensor field observation data installed at the Socheong-cho Ocean Research Station, GOCI-II daily PAR showed an underestimation tendency with 11.10% root-mean-square error (RMSE) and 9.89% mean bias error (MBE) compared to field observation data, but the determination coefficient (R2) value showed a high linear correlation of 0.98. As a result of comparing GOCI and GOCI-II daily PAR between sensors in the GOCI-II slot 4 areas on March 10, 11, and 14, 2021, after randomly selecting areas A, B, and C, high consistency was shown in areas A and B with little cloud cover, but a maximum RMSE of 6.24% was shown in area C, which was heavily affected by clouds. In the future, we plan to research to improve the accuracy of GOCI-II PAR through algorithm verification and correction by adding field observation data. The development and verification of the GOCI-II PAR algorithm are expected to help monitor the marine environment and research activities in the waters around the Korean Peninsula, which have been continued from GOCI and contribute to research on responding to changes through long-term observation data.33Nscopuskc
Modeling Seasonal Variations of Sediment Transport and Morphological Changes in Delta Ecosystem: A Case Study of the Wulan Delta, Indonesia
No full textThe suspended sediment from the Serang River plays a crucial role in the development of the Wulan Delta. This study employs the open-source DELFT3D model to investigate seasonal hydrodynamics, sediment distribution, and morphodynamic changes in the delta. Sediment dynamics during both the rainy and dry seasons were analyzed using the DELFT3D-Flow model. Tidal data were sourced from TPXO 9v1 and field measurements, while bathymetric data from GEBCO were validated against in-situ observations. Model results indicate seasonal sediment concentration patterns, which were further validated against satellite imagery, demonstrating consistency between simulated and observed sediment distribution. Statistical analysis revealed an RMSE range of 0.001 to 0.061. The estimated sediment deposition rate is approximately 1.2 t·yr⁻¹, with a deposition rate of 2.74 t·m⁻²·yr⁻¹ at both river mouths. About 12% of the sediment accumulates near the river mouth, while the remainder is redistributed by currents influenced by the Java Sea's bed morphology. Erosion was primarily observed in the eastern part of the delta and at the OWR mouth, whereas the western delta exhibited significant deposition due to strong river currents and substantial sediment supply. This sediment distribution suggests potential delta expansion from the west to the north. Findings contribute to the understanding of sediment transport processes in deltas, with implications for mitigating coastal erosion, enhancing delta resilience, and preserving ecosystems in similar regions across northern Java.33Nscopu
Requirements and Detailed Design for The Underwater Sojourn
No full text해저에서 인류의 체류를 위해서는 수압 및 해저환경을 견딜 수 있는 구조물과 체류자의 생활을 위한 설비의 요구 조건을 도출할 필요가 있다. 본 연구에서는 인류의 생활 영역을 해저로 확장하기 위해서 5인이 수심 50m에서 28일간 체류할 수 있도록 필요한 공간의 정의와 필수 설비의 요구 조건을 도출하였으며, 각 장비의 배치를 수행하였다. 장비를 배치하는 과정에서 해저공간을 운영하기 위한 개념을 도출하여 공간의 구획 및 상세설계를 수행하였다. 최종적으로 계획된 해저공간은 전력과 통신을 육상에서 공급받고, 공간적 단절을 이루어내었다. 여기서, 공간적 단절이란 체류자가 소비하는 공기, 생활용수 등을 자체 생산하고, 육상과의 이동경로가 연결되어 있지 않음을 의미한다. 최종 설계는 5인이 28일 체류할 수 있도록 내부공간을 구성하였으며, 체류자의 28일 생활을 위한 기본적 생활 요건을 도출하였다.2
Satellite-based mapping of mackerel habitat suitability in the exclusive economic zone of South Korea
No full textTo examine the spatial distribution of mackerel catches within South Korea's Exclusive Economic Zone (EEZ) from 2011 to 2019, we evaluated the habitat suitability index (HSI) for mackerel using satellite-derived environmental data combined with government-provided catch data. The HSI is widely recognized for its capability in identifying and predicting potential fishing areas. By integrating mackerel catch records with satellite-based environmental variables such as Chlorophyll-a concentration (CHL), Sea Surface Temperature (SST), Sea Surface Height (SSH), and Primary Productivity (PP), we established optimal environmental ranges: CHL (0.32 to 1.6 mg m−3), SST (14.45 to 26.72°C), SSH (0.61 to 0.84 m), and PP (654.94 to 1,731.3 mg C m−2 d−1). Using these thresholds, we generated seasonal habitat suitability maps for mackerel, which were validated against catch data. The findings suggest that our HSI model is a reliable tool for predicting mackerel fishing grounds within the South Korean EEZ. This research offers valuable insights into the spatial distribution and environmental preferences of mackerel in these waters, contributing to improved fisheries management strategies.1
Estimating diurnal variability of photosynthetically available radiation at the ocean surface from EPIC observations
No full textCurrent satellite radiation products from polar-orbiting sensors like MODIS, SGLI, VIIRS, and OCI provide only daily averaged quantities, missing critical diurnal variations. These fluctuations in light energy, ranging from none to ample throughout the day, significantly influence photosynthetic communities, impacting carbon export, nutrient cycling, and ecosystem functions. Incorporating hourly changes in phytoplankton light absorption and irradiance, as shown with GOCI data, has enhanced estimates of net primary productivity. However, the global oceans cannot be fully observed from a single geostationary platform, especially at high latitudes. EPIC, positioned at the first Lagrange point (L1) about 1.5 million km from Earth, offers a unique advantage by simultaneously capturing the entire sunlit ocean with high temporal resolution, enabling detailed observation of evolving systems and diurnal phenomena. Unlike polar orbiters, EPIC provides better coverage at low and middle latitudes, effectively mitigates Sun glint, and offers adequate views of polar regions. Utilizing EPIC data, we estimate hourly photosynthetically available radiation (PAR) over the global ocean. The algorithm is developed and validated through radiative transfer simulations under realistic conditions. Comparisons with geostationary AHI and GOCI data show strong performance. The diurnal PAR estimates, when combined with other ocean color products, are expected to advance studies of aquatic photosynthesis and biogeochemistry.1
I-ORS2004_2023_OCN_ATM
No full textI-ORS2004_2023_OCN_ATM comprises a comprehensive record of oceanographic and meteorological observations collected at the Ieodo Ocean Research Station (I-ORS) over 20 years, from 2004 to 2023. The dataset contains hourly averaged values, with precipitation data representing hourly accumulation, based on measurements recorded at 10-minute intervals. All data have undergone automated and manual quality control processes, followed by subsequent height corrections.
The accompanying MATLAB scripts, used to process these 10-minute raw observations into the final hourly products, are also provided.
- Period: 2004–2023
- Location: 32.1228°N, 125.1822°E
- Dataset (variables)
· I-ORS_2004_2023_OCN_1hr.nc (water temperatures at 5, 21, and 38 m)
· I-ORS_2004_2023_ATM_1hr.nc (air temperature, winds, air pressure, relative humidity, and precipitation)
[Version 1.1 Update]
- Algorithms for computing hourly averages and for standard height adjustment to air pressure and wind (zonal and meridional) have been revised.
- The algorithm for calculating precipitation data has been revised.
- Data have been rounded to one decimal place.
- The variable name for water temperature has been updated.
- Filenames have been updated:
· I-ORS_2004_2023_TS_OCN.nc to I-ORS_2004_2023_OCN_1hr.nc
· I-ORS_2004_2023_TS_ATM.nc to I-ORS_2004_2023_ATM_1hr.nc
- The data processing code has been included