In the Arabian Sea, South Asian monsoon (SAM)-induced high surface water productivity coupled with poor ventilation of intermediate water results in strong denitrification within the oxygen minimum zone (OMZ). Despite the significance of denitrification in the Arabian Sea, we have no long-term record of its evolution spanning the past several million years. Here, we present the first record of denitrification evolution since Late Miocene (~10.2 Ma) in the Eastern Arabian Sea, where the SAM generates moderate surface water productivity, based on the samples retrieved during the International Ocean Discovery Program (IODP) Expedition 355. We find that (i) the SAM was persistently weaker from ~10.2 to 3.1 Ma; it did not intensify at ~8 Ma in contrast to a few previous studies, (ii) on tectonic timescale, both the SAM and the East Asian Monsoon (EAM) varied synchronously, (iii) the first evidence of denitrification and productivity/SAM intensification was at ~3.2–2.8 Ma that coincided with Mid-Pliocene Warm Period (MPWP), and (iv) the modern strength of the OMZ where denitrification is a permanent feature was attained at ~1.0 Ma.

Detailed diatom records within surface and core sediments from the Southern Bering Continental Shelf (SBCS) reveal that the Holocene evolution of sea-ice distribution is associated with low pressure patterns. Holocene sea-ice distribution over the SBCS was mainly controlled by the location of the Aleutian Low. The corresponding paleoceanographic and paleoclimate conditions can be divided into three stages: (1) the early Holocene (before 7000 cal. yr BP) was characterized by extensive sea-ice distribution under two low-pressure cells, which covered the western Bering Sea and the Gulf of Alaska, respectively. (2) Between 3000 and 7000 cal. yr BP, the low-pressure system over the Gulf of Alaska became weak, causing total sea-ice mass over the SBCS to retreat. (3) In the past 3000 years, prevailing southwesterly winds over the SBCS due to the developing Aleutian Low have reduced further sea-ice cover on the SBCS. These paleoclimatic changes were probably a response to ENSO variation. The timings of water mass exchanges on the SBCS coincided with sea-level change along the Alaskan Peninsula. As a result, subsequent morphologic alterations have also influenced the paleoceanographic condition of the SBCS. The effect of the surface coastal water and bottom marine water on the SBCS intensified about 6000 cal. yr BP when sea level increased.

A record-breaking agglomeration of Sargassum was packed along the northern Jeju coast in Korea in 2021, and laborers suffered from removing them from the beach. If remote sensing can be used to detect the locations at which Sargassum accumulated in a timely and accurate manner, we could remove them before their arrival and reduce the damage caused by Sargassum. This study aims to detect Sargassum distribution on the coast of Jeju Island using the Geostationary KOMPSAT 2B (GK2B) Geostationary Ocean Color Imager-II (GOCI-II) imagery that was launched in February 2020, with measurements available since October 2020. For this, we used GOCI-II imagery during the first 6 months and machine learning models including Fine Tree, a Fine Gaussian support vector machine (SVM), and Gentle adaptive boosting (GentleBoost). We trained the models with the GOCI-II Rayleigh-corrected reflectance (R_hoC) image and a ground truth map extracted from high-resolution images as input and output, respectively. Qualitative and quantitative assessments were carried out using the three machine learning models and traditional methods such as Sargassum indexes. We found that GentleBoost showed a lower false positive (6.2%) and a high F-measure level (0.82), and a more appropriate Sargassum distribution compared to other methods. The application of the machine learning model to GOCI-II images in various atmospheric conditions is therefore considered successful for mapping Sargassum extent quickly, enabling reduction of laborers’ efforts to remove them.