The East/Japan Sea (hereafter, the East Sea) is highly dynamic in its physical phenomena and biological characteristics, but it has changed substantially over the last several decades. In this study, a recent decadal trend of primary productivity in the East Sea was analyzed based on Moderate-Resolution Imaging Spectroradiometer (MODIS)-derived monthly values to detect any long-term change. The daily primary productivities averaged using monthly values from 2003 to 2012 were 719.7 mg·C·m⁻²·d⁻¹ (S.D. ± 197.5 mg·C·m⁻²·d⁻¹, n = 120) and 632.3 mg·C·m⁻²·d⁻¹ (S.D. ± 235.1 mg·C·m⁻²·d⁻¹, n = 120) for the southern and northern regions of the East Sea, respectively. Based on the daily productivities, the average annual primary production in the East Sea was 246.8 g·C·m⁻²·y⁻¹, which was substantially higher than that previously reported in deep oceans. However, a decreasing trend (13% per 10 years) in the annual primary production was observed in the East Sea within the study period from 2003 to 2012. The shallower mixed layers caused by increased temperature could be a potential cause for the decline in annual production. However, this decline could also be part of an oscillation pattern that is strongly governed by the Pacific Decadal Oscillation (PDO). A better understanding of primary productivity patterns and their subsequent effects on the marine ecosystem is required for further interdisciplinary studies in the East Sea.

Although the Ulleung Basin is an important biological “hot spot” in East/Japan Sea (hereafter the East Sea), very limited knowledge for seasonal and annual variations in the primary productivity exists. In this study, a recent decadal trend of primary production in the Ulleung Basin was analyzed based on MODIS‐derived monthly primary production for a better annual production budget. Based on the MODIS‐derived primary production, the mean daily primary productivity was 766.8 mg C m⁻² d⁻¹ (SD = ±196.7 mg C m⁻² d⁻¹) and the annual primary productivity was 280.2 g C m⁻² yr⁻¹ (SD = ±14.9 g C m⁻² yr⁻¹) in the Ulleung Basin during the study period. The monthly contributions of primary production were not largely variable among different months, and a relatively small interannual production variability was also observed in the Ulleung Basin, which indicates that the Ulleung Basin is a sustaining biologically productive region called as “hot spot” in the East Sea. However, a significant recent decline in the annual primary production was observed in the Ulleung Basin after 2006. Although no strong possibilities were found in this study, the current warming sea surface temperature and a negative phase PDO index were suggested for the recent declining primary production. For a better understanding of subsequent effects on marine ecosystems, more intensive interdisciplinary field studies will be required in the Ulleung Basin.

The climate-induced decrease in fish catches in South Korea has been a big concern over the last decades. The increase in sea surface temperature (SST) due to climate change has led to not only a decline in fishery landings but also a shift in the fishing grounds of several fish species. The habitat suitability index (HSI), a reliable indicator of the capacity of a habitant to support selected species, has been widely used to detect and forecast fishing ground formation. In this study, the catch data of the chub mackerel and satellite-derived environmental factors were used to calculate the HSI for the chub mackerel in the South Sea, South Korea. More than 80% of the total catch was found in areas with an SST of 14.72–25.72 °C, chlorophyll-a of 0.30–0.92 mg m⁻³, and primary production of 523.7–806.46 mg C m⁻² d⁻¹. Based on these results, the estimated climatological monthly HSI from 2002 to 2016 clearly showed that the wintering ground of the chub mackerel generally formed in the South Sea of South Korea, coinciding with the catch distribution during the same period. This outcome implies that our estimated HSI can yield a reliable prediction of the fishing ground for the chub mackerel in the East/Japan Sea and South Sea of South Korea.

The most problematic issue in the ocean color application is the presence of heavy clouds, especially in polar regions. For that reason, the demand for the ocean color application in polar regions is increased. As a way to overcome such issues, we conducted the reconstruction of the chlorophyll-a concentration (CHL) data using the machine learning-based models to raise the usability of CHL data. This analysis was first conducted on a regional scale and focused on the biologically-valued Cape Hallett, Ross Sea, Antarctica. Environmental factors and geographical information associated with phytoplankton dynamics were considered as predictors for the CHL reconstruction, which were obtained from cloud-free microwave and reanalysis data. As the machine learning models used in the present study, the ensemble-based models such as Random forest (RF) and Extremely randomized tree (ET) were selected with 10-fold cross-validation. As a result, both CHL reconstructions from the two models showed significant agreement with the standard satellite-derived CHL data. In addition, the reconstructed CHLs were close to the actual CHL value even where it was not observed by the satellites. However, there is a slight difference between the CHL reconstruction results from the RF and the ET, which is likely caused by the difference in the contribution of each predictor. In addition, we examined the variable importance for the CHL reconstruction quantitatively. As such, the sea surface and atmospheric temperature, and the photosynthetically available radiation have high contributions to the model developments. Mostly, geographic information appears to have a lower contribution relative to environmental predictors. Lastly, we estimated the partial dependences for the predictors for further study on the variable contribution and investigated the contributions to the CHL reconstruction with changes in the predictors.