Monitoring shoreline movements is essential for understanding the impact of anthropogenic activities and climate change on the coastal zone dynamics. The use of remote sensing allows for large-scale spatial and temporal studies to better comprehend current trends. This study used Landsat 5 (TM), Landsat 8 (OLI), and Sentinel-2 (MSI) remote sensing images, together with the Otsu algorithm, marching squares algorithm, and tidal correction algorithm, to extract and correct the coastline positions of the east coast of Laizhou Bay in China from 1984 to 2022. The results indicate that 89.63% of the extracted shoreline segments have an error less than 30 m compared to the manually drawn coastline. The total length of the coastline increased from 166.90 km to 364.20 km, throughout the observation period, with a length change intensity (LCI) of 3.11% due to the development of coastal protection and engineering structures for human activities. The anthropization led to a decrease in the natural coastline from 83.33% to 13.89% and a continuous increase in the diversity and human use of the coastline. In particular, the index of coastline diversity (ICTD) and the index of coastline utilization degree (ICUD) increased from 0.39 to 0.79, and from 153.30 to 390.37, respectively. Over 70% of the sandy beaches experienced erosional processes. The shoreline erosion calculated using the end point rate (EPR) and the linear regression rate (LRR) is 79.54% and 85.58%, respectively. The fractal dimension of the coastline shows an increasing trend and is positively correlated with human activities. Coastline changes are primarily attributed to interventions such as land reclamation, aquaculture development, and port construction resulting in the creation of 10,000.20 hectares of new coastal areas. Finally, the use of Kalman filtering for the first time made it possible to predict that approximately 84.58% of the sandy coastline will be eroded to varying degrees by 2032. The research results can provide valuable reference for the scientific planning and rational utilization of resources on the eastern coast of Laizhou Bay.

Tidal flats, a critical part of coastal wetlands, offer unique ecosystem services and functions. However, in China, these areas are under significant threat from industrialization, urbanization, aquaculture expansion, and coastline reconstruction. There is an urgent need for macroscopic, accurate and periodic tidal flat resource data to support the scientific management and development of coastal resources. At present, the lack of macroscopic, accurate and periodic high-resolution tidal flat maps in China greatly limits the spatio-temporal analysis of the dynamic changes of tidal flats in China, and is insufficient to support practical management efforts. In this study, we used the Google Earth Engine (GEE) platform to construct multi-source intensive time series remote sensing image collection from Sentinel-2 (MSI), Landsat 8 (OLI) and Landsat 9 (OLI-2) images, and then automated the execution of improved MSIC-OA (Maximum Spectral Index Composite and Otsu Algorithm) to process the collection, and then extracted and analyzed the tidal flat data of China in 2018 and 2023. The results are as follows: (1) the overall classification accuracy of the tidal flat in 2023 is 95.19%, with an F1 score of 0.92. In 2018, these values are 92.77% and 0.88, respectively. (2) The total tidal flat area in 2018 and 2023 is 8300.34 km² and 8151.54 km², respectively, showing a decrease of 148.80 km². (3) In 2023, estuarine and bay tidal flats account for 54.88% of the total area, with most tidal flats distribute near river inlets and bays. (4) In 2023, the total length of the coastline adjacent to the tidal flat is 10,196.17 km, of which the artificial shoreline accounts for 67.06%. The development degree of the tidal flat is 2.04, indicating that the majority of tidal flats have been developed and utilized. The results can provide a valuable data reference for the protection and scientific planning of tidal flat resources in China.

Four short sediment cores were collected to explore the impacts of bay scallop farming on the composition and accumulation of sedimentary organic matter (SOM). The results revealed that SOM was mainly composed of relatively easily biodegradable substances as evidenced by the high contribution rate of biopolymeric carbon (77.8–94.4%). The sediment accumulation rate in the scallop farming area (SFA) was 28.6% higher than that in the non-scallop farming area (NSFA). The total organic carbon (TOC) and total nitrogen (TN) burial fluxes in the SFA were 33.1 and 36.6% higher than those in the NSFA, respectively. A rough estimate showed that the burial fluxes of TOC, TN, scallop-derived OC, and marine algal-derived OC in the ~150 km² SFA could increase by 1.08, 0.11, 0.39, and 0.68 g m⁻² yr⁻¹, respectively, with annual scallop production increasing 10⁴ t. This study highlights the significant effects of scallop farming on the biogeochemistry of SOM in coastal waters, which provides a direct reference for future research on the carbon cycle in shellfish culture areas.

Laboratory experiments were conducted to study the effects of oil spills and dispersants on the growth of the red tide organism Chaetoceros sp. Crude oil produced from the Chinese Bohai Sea, diesel oil, and the chemical dispersant (GM-2) produced in China were added into Chaetoceros sp. cultures. The results showed that both crude oil and diesel oil could enhance the growth of Chaetoceros sp. Data were analyzed by one-way ANOVA, and the confidence interval was 95%. At a concentration of 20 mg L⁻¹ crude oil and a concentration of 10 μL L⁻¹ diesel oil, Chaetoceros sp. bloomed to 1.57 × 10⁵ cells mL⁻¹ (p < 0.01) at day 14 and 3.55 × 10⁴ cells mL⁻¹ (p < 0.05) at day 10, respectively. A concentration of 10 μL L⁻¹ diesel oil stimulated the specific growth rate for Chaetoceros sp. of 0.49 d⁻¹ over 10 days. The specific growth rate of Chaetoceros sp. with 20 mg L⁻¹ crude oil alone was 0.46 d⁻¹ over 14 days. However, the mixture of oil and dispersant did not enhance the growth of Chaetoceros sp. as significantly as oil alone. These results implied that oil spills in coastal waters can stimulate Chaetoceros sp., and the specific dispersant GM-2 applied following oil spills may be unlikely to further enhance the growth of Chaetoceros sp.