The offshore China (OC) region is a significant sea area in the Western Pacific and many researchers have been interested in the distribution of sea surface temperature (SST) fronts in this area. In this study, the Cayula and Cornillon single image edge detection algorithm was used to detect SST fronts using the Daily Optimum Interpolation Sea Surface Temperature data from 1982 to 2021. The results revealed that there are eighteen SST fronts in OC— three in the Bohai Sea, seven in the Yellow Sea, two in the East China Sea, five in the South China Sea, one in the Pacific Ocean east of Taiwan province, China—and among them a new front was detected in the Yellow Sea and named the Yellow Sea Ring Front. The frequency of most fronts showed a tendency of initially increasing and then decreasing from January to September, followed by a trend of growing steadily from October to December. The frequency of a few fronts showed a decreasing tendency from January to September and an increasing tendency from October to December. The frequency of most fronts is highest in winter and lowest in summer. In spring and autumn, the frequency of most fronts is lower than that in winter and higher than that in summer. The annual average frontal probability of five-ninths of the fronts showed an upward trend, and the annual average frontal probability value of one-third of the fronts showed a downward trend. The rest of the fronts showed a stable trend. The results of this paper also showed that the Liaodong Bay Front and the Bohai-Laizhou Bay Front did not form a complete front, as previously reported. In addition, the frontal probability of the Bohai Front to the north of 39° N was in the tendency of decreasing.

Yangjiang coastal waters provide vital spawning grounds, feeding grounds, and nursery areas for many commercial fish species. It is important to understand the spatial distribution of fish for the management, development, and protection of fishery resources. In this study, an acoustic survey was conducted from 29 July to 5 June 2021. Meanwhile, remote sensing data were collected, including sea surface temperature (SST), chlorophyll concentration (Chla), sea surface salinity (SSS), and sea surface temperature anomaly (SSTA). The spatial distribution of density and biomass of fish was analyzed based on acoustic survey data using the geostatistical method. Combining with remote sensing data, we explored the relation between fish density and the environment based on the GAMs model. The results showed that fish are mainly small individuals. The horizontal distri-bution of fish density had a characteristic of high nearshore and low offshore. In the vertical direc-tion, fish are mainly distributed in surface-middle layers in shallow waters (10 m), respectively. The deviance explained in the optimal GAM model was 59.2%. SST, Chla, SSS, and longitude were significant factors influencing fish density distribu-tion with a contribution of 35.3%, 11.8%, 6.5%, and 5.6%, respectively. This study can pro-vide a scientific foundation and data support for rational developing and protecting fishery re-sources in Yangjiang coastal waters.

Biosiliceous sedimentation, closely related to carbon sedimentation in water, has a significant impact on the marine biogeochemical cycle. However, large-scale monitoring data are scarce due to the constraints of biosiliceous sedimentation flux (BSF) gathering methods. There are few reports on the spatiotemporal variation of BSF in estuaries and offshore waters. Additionally, few studies have used satellite remote sensing methods to retrieve BSF. In the paper, satellite images from 2000 to 2020 were used for the first time to estimate the BSF distribution of the Pearl River Estuary (PRE) over the past 20 years, based on a remote sensing model combined with particulate organic carbon (POC) deposition data and water depth data. The results showed that the BSF ranged from 100 to 2000 mg/(m² × d). The accuracy tests indicated that the correlation coefficient (R²) and significance (P) of Pearson correlation analysis were 0.8787 and 0.0018, respectively. The BSF value varied seasonally and increased every year. The BSF did not follow a simple trend of decreasing along the coast to open water. Shenzhen Bay (SZB) generally had a higher BSF value than the Dragon’s Den Waterway (DDW). The BSF in autumn and winter was investigated using empirical orthogonal function analysis (EOF). In autumn, the BSF of the PRE’s eastern bank showed little change, while the BSF of the western bank showed obvious differences. In winter, the BSF in Hong Kong waters and inlet shoals fluctuated less, whereas the BSF in DDW and Lingding Waterway (LW) fluctuated more. The grey correlation analysis (GRA) identified two factors affecting BSF: chromophoric dissolved organic matter (CDOM) and total suspended solids (TSS). Most BSF were primarily affected by TSS during winter. In spring, the two effects were balanced. TSS affected the east coast in summer, and CDOM was the dominant effect in autumn. Four main parameters influencing the distribution of BSF in the PRE were analyzed: ecosystem, reef, flow field and flocculation. This study showed that using satellite remote sensing to estimate BSF has excellent potential, which is worthy of further discussion in terms of spatiotemporal resolution and model optimization.