This study aimed to investigate the allelopathic effects of Sesuvium portulacastrum (Aizoaceae) on typical red tide algae and identify the sources of the active compounds. Three red tide algae species, Prorocentrum micans, Karenia mikimotoi, and Alexandrium catenella, were selected as test subjects. The planting water of the coastal salt-tolerant plant Sesuvium portulacastrum served as the research material. Root exudates from the plant were adsorbed using a C₁₈ solid-phase extraction column and then extracted with methanol, ethyl acetate, dichloromethane, and n-hexane. The four extracts exhibited varying degrees of inhibition on the growth of the algae, with the dichloromethane extract showing the most significant inhibitory effect. At a concentration of 10 g/L, the inhibition rates for the three algae species were 50.83%, 97.30%, and 81.41%, respectively. Gas chromatography-mass spectrometry (GC-MS) analysis identified 19 fatty acids and their derivatives. Among these, stearic acid, oleamide, and docosanol exhibited algicidal activity, with docosanol showing the strongest effect. At a concentration of 2 mg/L, the inhibition rates for the three algae species were 90%, 100%, and 81.04%, respectively. These results indicate that Sesuvium portulacastrum can release fatty acids and their derivatives to inhibit the growth of red tide algae, demonstrating its potential as a plant-based tool for red tide control and environmental remediation.

Phytoplankton blooms in polar regions with seasonal sea ice cover show a unimodal seasonality. However, the bloom processes are controlled by multiple physical and biogeochemical factors, including sea ice, light availability, mixed layer depth, and nutrients; those may result in great uncertainties in simulating phytoplankton bloom by the Earth System Models (ESMs). In this study, the results of 11 Coupled Model Intercomparison Phase-6 (CMIP6) ESMs were analyzed and evaluated with various types of observational products in order to determine whether those ESMs can correctly model the phytoplankton blooms in three Arctic shelf seas, Barents Sea, Chukchi Sea, and Bering Sea. By calculating multiple indices that represent light and nutrient limitations, the error sources of simulated surface chlorophyll a concentrations were comprehensively analyzed. Our results show that the 11 ESMs can be divided into three groups based on ice-adjusted photoperiod, rate of change of mixed layer depth, and surface nitrate concentration. Some groups are characterized by the smallest bias between modeled indices and observation-based reference, and those ESMs perform best in simulating phytoplankton bloom characteristics. The other groups of ESMs differ significantly from the reference values in terms of surface nitrate and/or rate of change of mixed layer depth, resulting in delayed occurrences of annual chlorophyll a peak concentration and greater differences in corresponding peak values. In general, in addition to the two primary constraints of light and nutrients, the ESMs should also well represent the upper mixed layer controlled by temperature and salinity distributions, so as to accurately simulate the seasonal variation of surface chlorophyll a concentration. The above analyses indicate ESMs can be used in assessing polar planktonic ecosystems, and there is room for improving ecosystem-related parametrization in future ESM development.

Due to the limitations of the Rayleigh criterion, classical harmonic analysis (CHA) model requires half a year of data records to analyze the eight main tidal constituents, namely, M₂, S₂, N₂, K₂, K₁, O₁, P₁, Q₁. For short-term tidal records, the unresolved constituents typically rely on the ratio differences from nearby long-term tidal stations for estimation. However, there is a scarcity of publicly available long-term tidal data in the coastal areas of Zhejiang, which currently prevents the accurate extraction of the main constituents from short-term records. This paper introduces a modified harmonic analysis model, referred to as the Modified Harmonic Analysis model based on the Credo of Smoothness (MHACS). Based on the smooth functions established by the intrinsic connections between major constituents, it breaks through the Rayleigh criterion, significantly reducing the length of tidal records required, especially suitable for coastal areas with abundant short-term data. This algorithm was applied to the multi-island area of Zhejiang offshore, using tidal records shorter than 15 days. The results show that the harmonic constants of the eight main constituents at the Shipu station are very close to the results obtained by the CHA method, and the required data length is reduced from 8760 hours to 336 hours, which can be used to calculate characteristic parameters such as the theoretical depth datum. For analyzing the eight main constituents along the Zhejiang coast using MHACS, a minimum data length of 5 days is recommended.

In order to identify the functional diversity of the adjacent waters of the Changshan Islands in the ecotone between the Yellow Sea and the Bohai Sea, based on the quarterly survey of fish biological resources and environment factors from October 2016 to August 2017, combined with 13 functional traits such as feeding habit, trophic level, migration type, thermophily, resilience and fish eggs type, the spatio-temporal pattern of functional diversity and its relationship with environmental factors were studied by using community weighted mean index (CWM), functional diversity index and Spearman rank correlation analysis. The results showed that the dominant species of fish community in spring and winter were depressiform, warm temperate and demersal species with the characteristics of anterior or upper mouth, low growth coefficient, high vulnerability, low resilience and non-migration or short distance migration. The dominant species in summer and autumn showed more functional traits, such as long distance migration, pelagic, fusiform and compressiform. FRic in summer and autumn was significantly higher than that in spring and winter, FEve was the highest in spring, and FDiv was the lowest in autumn and was significantly lower than other seasons. FEve in spring and season and FDiv in spring and autumn showed a trend of high in the west and low in the east, while FRic in summer and winter and FEve in autumn showed a trend of high in the east and low in the west. There was a certain correlation between environmental factors and functional diversity index. As an ecotone between the Yellow Sea and the Bohai Sea, the functional traits of the dominant species and functional diversity show seasonal variations made by the fish migration, and the spatial pattern of functional diversity shows complexity and heterogeneity made by environment changing in the adjacent waters of the Changshan Islands.

Beach is a common and vulnerable coastal ecosystem with huge ecological service functions. Due to the multiple impacts of climate change and human activities, beach ecosystem has been seriously damaged. Beach nourishment is an effective approach to prevent coastal erosion and improve the beach environment by using sand replenishment to restore beach morphology. Previous nourishments have often neglected the impacts on beach ecosystem. Many studies show that beach nourishment have multifaceted, multi-scale and complex impacts on beach ecosystem. Based on reviewing previous researches, the compositions, characteristics and functions of beach ecosystem are summarized. The basic characteristics of beach ecological damage, the impact process and mechanism of beach nourishment on beach ecosystem at various scales are analyzed. Then, some adaptive measures for beach nourishment are suggested from the perspective of reducing negative ecological impacts, which would support coastal management and sustainable utilization of beach.

This article is focus on the distribution and source of organic matter in tidal flat in the Jiulong River Estuary, and to seek effective organic geochemistry proxies for recognize sedimentary microfacies, and thus to help that organic carbon is better applied to identify sedimentary microfacies and paleo-environment. Forty one surficial sediment samples were obtained and measured their grain size, total organic carbon (TOC), total nitrogen (TN), and organic carbon stable isotopes (δ¹³C) in the tidal flat from three sedimentary environments: upper tidal flat, middle tidal flat and lower tidal flat in summer and winter. The results show that, from upper tidal flat to lower tidal flat, the grain size of sediments becomes coarser gradually with decreasing TOC, TN and C/N, and the increase of δ¹³C. The sources of organic matter in the upper tidal flat are dominated by terrestrial organic matter and mangrove, marine organic matter and Spartina alterniflora in middle tidal, and marine organic matter in lower tidal flat. The distribution and sources of organic carbon in tidal flat from the Jiulong River Estuary are controlled by the seasonal changes of land-ocean interaction, sedimentary hydrodynamic sorting, and plants. There is a significant difference in TOC, and a highly significant difference in TN and δ¹³C in sediments of the tidal flat. We thus proposed that organic geochemistry properties TOC, TN and δ¹³C are the effective indicators to identify upper tidal flat and middle-lower tidal flat in the Jiulong River Estuary.

Mangroves represent the most productive ecosystem along the coastline. The mangrove forest is a source of diverse organic carbon, which contributes to the complexity of the trophic structure of the benthic food web. This study employed the benthic animals in the mangroves along Yanpu Bay as the research object, analysing the community trophic structure and determining the potential food sources through the utilisation of the stable isotope technique in conjunction with the Stable Isotope Bayesian Ellipses (SIBER) model and the Stable Isotope Mixing Models (Simmr). The study demonstrated that the carbon stable isotope (δ¹³C) values of benthic animals ranged from −22.04‰ to −11.27‰, while the nitrogen stable isotope (δ¹⁵N) values ranged the trophic levels ranged from 1.33 (Cerithidea rhizophorarum) to 3.95 (Periophthalmus cantonensis), with carbon stable isotope (δ¹³C) values from 5.86‰ to 16.21‰. The trophic level of fish is relatively high, ranging from 2.38 to 3.95, while that of crustaceans is 2.61 to 3.52. In contrast, the trophic level of mollusc is relatively low, ranging from 1.33 to 3.15. These differences are related to the feeding preferences of the different groups. The analysis of the nutritional structure indicates that the length of the food chain and the nutritional diversity of fish are greater than those of crustaceans and mollusc. The diversity of food sources and nutritional uniformity of crustaceans are the highest, while the nutritional diversity and similarity of mollusc are the highest. Overall, there is a varying degree of overlap between the core nutritional niches of fish, crustaceans and mollusc. An analysis of the potential food sources of benthic animals based on a Simmr mixed model revealed that SOM was the primary carbon source, accounting for 78.2% of the total, followed by phytoplankton, which constituted 21.6% of the total, while litter and POM represented the lowest proportions, at 3.7% and 3.3%, respectively. The findings of this study enhance our comprehension of the trophic relationships of benthic animals in mangrove ecosystems along the northern coast of China. They will facilitate more effective conservation and restoration of mangrove biodiversity from a trophic regulation perspective.

Sea ice is a typical environmental feature of polar sea areas, and pixel-level classification of ship-borne video images can provide high-resolution sea ice information. Due to the complex light conditions and sea ice morphology in polar scenes, traditional computer graphics methods lack the generalization needed for intelligent identification of sea ice elements. Therefore, this paper deploys a deep learning approach based on the DeeplabV3+ semantic segmentation network structure to identify sea ice elements in polar scenes. The dataset consists of sea ice images captured by the icebreaker Xuelong during its navigation in ice-covered regions, and also is used to train and validate the deep learning model. To meet the requirements of sea ice element identification and the characteristics of the underway observation video images, the pixel information is divided into four semantic categories: sea ice, sky, seawater, and ship. The deep learning model is built based on the correlation between image information and semantic information in the training set. The model trained is used to predict the semantic information of pixels in the validation set or other images, thereby achieving automatic identification of sea ice information. To study the robustness of this method, the influences of sea ice concentration, lighting conditions, and sea ice types on the identification results was further analyzed. Additionally, the effects of dataset size and the number of iterations on identification accuracy were examined. The recognition results for images show that the mean Intersection over Union (mIoU) for the four types of semantic information exceeds 95%, indicating that the deep learning method can accurately classify various elements in the polar environment.

The dynamics of microplastic pollution in coastal zones, in the context of climate change, is a crucial global environmental issue. This study investigated and analyzed changes in microplastic abundance, composition, and diversity in beach sediments in Xiamen City before and after Typhoon Haikui. The results showed that the abundance of microplastics on the beaches in Xiamen City before Typhoon Haikui was (251.5 ± 27.9) n/kg, which significantly decreased to (127.0 ± 18.8) n/kg post-typhoon. Before and after the typhoon, the composition of microplastics on the beaches exhibited distinct variations. In particular, the abundance of smaller particles (<500 μm) significantly decreased, while the proportion of fibrous particles increased. Moreover, the typhoon event led to a general decrease in the Shannon-Wiener diversity index, while the Pielou’s evenness index increased. Based on the results of this study and previous research, it is concluded that heavy rainfall is the driving factor behind the changes in microplastic abundance and composition on Xiamen’s beaches caused by Typhoon Haikui. The impact of typhoons on the dynamics of microplastic pollution in coastal zones results from the coupling of multiple physical processes, influenced by a complex combination of factors, such as dynamic conditions, sediment physical and chemical factors, and topography. In the future, it will be necessary to conduct long-term monitoring of hydrological and meteorological data, and to carry out more in-depth, systematic, and comprehensive research on the underlying mechanisms.

Typhoons, as one of the common natural disasters in coastal zones, have severe impacts on tidal flats. However, there is a significant lack of field data on typhoons, and studies on how salt marsh vegetation protects tidal flats during typhoon events are still very limited. This study selected Chongming Dongtan in the Changjiang River Estuary as the research site. During the passage of Typhoon In-Fa in July 2021, hydrodynamic instruments and UAV photogrammetry (elevation measurements) were used to monitor hydrodynamics and sediment in both salt marsh and the marsh front areas, as well as to monitor the salt marsh ecosystem before and after the typhoon. The findings are as follows: (1) During the typhoon, wind speed, water depth, and wave height were 1.1−2.8 times those before and after the typhoon, and the hydrodynamic forces in the marsh front area were higher than those in the salt marsh area, with water depth, wave height, and flow velocity being 1.3 times, 1.2 times, and 1.9 times those of the salt marsh area, respectively. (2) Under the influence of Typhoon In-Fa, vegetation patches at the marsh front, directly exposed to strong winds and waves, experienced hydrodynamic forces such as water depth and wave height that were 1.1−1.9 times those of the salt marsh area, resulting in erosion at the marsh front being 1.2−1.8 times that of the inland vegetation patches under the same vegetation coverage conditions. (3) In the marsh-front area, densely vegetated patches demonstrated stronger sediment accretion capacity compared to sparsely vegetated patches, with the maximum accretion thickness in densely vegetated areas reaching 45 cm, whereas sparse patches were mainly subject to erosion, with a maximum erosion depth of 17 cm. This indicates that the density of vegetation patches directly affects the sedimentation and erosion dynamics of the tidal flat. This study reveals that the arrangement and location of vegetation patches are crucial to the sedimentation and erosion of tidal flats under extreme weather events, which has significant implications for tidal flat management and ecological protection. It also provides theoretical support for establishing a robust natural barrier in response to extreme weather conditions.