Abstract One of the major sources of iron supply to the Okhotsk Sea and the Oyashio region, which both have high biological productivity, is thought to be regions of the East Sakhalin Current and its upstream, originating from the Amur River. This study suggests that the Soya Warm Current (SWC) region could also be a possible source of iron via resuspension of bottom sediments. We derived the volume backscatter strength from acoustic Doppler current profilers (ADCP) data that had previously been collected in the SWC region. The backscatter strength data indicate that prominent sediment resuspension occurs in both the upstream and downstream regions of the SWC when the bottom current exceeding 0.5 m/s continues to some extent. In the upstream region, strong current events that induced the sediment resuspension occurred through the SWC intensification caused by the increase in sea-level difference across the Soya Strait excited by the southerly winds. Such events frequently occur from September to December, because of frequent passages of cyclone. By contrast, in the downstream region, sediment resuspension occurred due to the strong northerly winds via the current increase caused by the coastal trapped waves over the shelf in winter. The sediment resuspension in the downstream region was also supported by direct observations of high turbidity near the bottom. High iron concentrations in the coastal Oyashio water possibly originate from the SWC water. The occurrence of the resuspension during the sea ice season suggests the potential local incorporation of sediment into sea ice.

Abstract The temporal drift of the ARO-FTs, the new optical dissolved oxygen (DO) sensors mounted on 13 Argo floats, was analyzed for two periods: the storage period before float deployment and the period after float deployment. ARO-FTs exhibited a common issue of optical DO sensors, resulting in greater deviations from the reference data at higher concentrations. The storage drift of the ARO-FTs mounted on floats in this study was on the order of 5 μmol kg –1 . Although this storage drift was larger than that of the Aanderaa Optode 4330, the first ARO-FT DO profiles could be corrected to within ± 2% of the ship-based bottle sampling data, even at layers with large vertical DO gradients, using a linear first-order equation, owing to the fast response time of ARO-FTs. The average temporal drift of ARO-FTs after float deployment was estimated at – 0.31 ± 0.17% year –1 in oxygen concentration using the method of a previous study. Although the drift of ARO-FTs was greater than that of the Aanderaa Optode 4330 for both periods, the DO profiles corrected for drift remained within ± 2% of the nearby reference data at 210 days after float deployment. The seasonal variations in oxygen saturation rate near the surface and their amplitudes during the study period were consistent with those observed in monthly climatology. These results indicate that the corrected DO measurement by ARO-FTs was comparable to that of the Aanderaa Optode 4330.

Abstract Understanding marine surface fish diversity is crucial for ecosystem management. However, the traditional sampling methods are often invasive, costly, or unsuitable for certain species or locations. Environmental DNA (eDNA) metabarcoding provides a non-invasive and relatively cheap alternative to explore patterns of diversity. It is important to recognize that, eDNA-based inference can vary across sampling methods, potentially impacting the validity of biodiversity assessments. To evaluate and compare the effectiveness of three eDNA sampling methods—ship-bottom intake (4.5 m), Niskin bottles (5 or 10 m), and bucket (0 m)—for assessing fish diversity and fish community composition in the western North Pacific near Japan, we analyzed fish communities from 83 stations sampled during nine research cruises. Taxonomic analysis revealed that each method detected over 324 taxa, contributing to a total of 465 taxa. Hierarchical clustering generally identified similar species composition across methods at a station. The exception was when intake samples, collected at different times, diverged from bucket and Niskin samples at the same station. Hill’s number rarefaction and extrapolation curves across all clusters showed similar results among methods, with exceptions in a few clusters where bucket samples exhibited higher biodiversity indices than intake and Niskin samples. Non-metric multidimensional scaling indicated significant relationships between cluster composition and environmental factors like temperature, salinity, and chlorophyll-a. Some clusters were also controlled by integrated seasonal factors. Overall, fish community composition was convincingly similar among methods. This finding suggests that any of these eDNA sampling methods can be effective and may be prioritized based on logistical considerations.

Abstract Ocean bottom temperature is affected by waves propagating along the seafloor. Understanding fluctuations in ocean bottom temperature caused by such wave phenomena can enhance the accuracy of geophysical observations. If seafloor seismic observation networks such as the Dense Ocean floor Network system for Earthquakes and Tsunamis (DONET), which was installed for earthquake disaster prevention in the Nankai Trough region, can detect ocean waves generated along the continental slope, they may serve broader multidisciplinary research objectives across various ocean bottom seismic networks. Here, we investigated the spatiotemporal characteristics of ocean bottom temperature data recorded by DONET and identified in-phase wave patterns. Our findings reveal that temperature correlations are more strongly dependent on relative water depths than on the horizontal distances between observation sites. Such in-phase variations observed in DONET thermometers suggest that seafloor seismic networks can indeed detect and assess oceanographic phenomena such as wave propagation. Furthermore, we discuss the implications of such wave activity on the accuracy of distributed acoustic sensing (DAS) data used in geophysical studies, highlighting potential applications of DAS in oceanography and its relevance to crustal deformation observation.