Journal of Sea Research最新文献

The modern society faces a major challenge of environmental protection and achieving sustainable development due to the rapid expansion of the world economy and sustained population growth. This research focuses on the degree of synchronization between marine ecology and the economy. The objective of this study is to address this issue. The aim of this study was to determine the level of synchronization between marine ecology and the economy in nine coastal provinces of China from 2017 to 2022. This study examined the coordination between marine ecology and economy, using sustainable development theory and systems theory. The main focus was on the degree of synchronization between marine ecology and the economy. The study employed the coupling coordination model to evaluate the degree of coordination between marine ecology and economy selected for the study. The study analyzed differences in the degree of coordination and overall trends over time, as well as factors affecting the coordination of marine ecology and the economy. Kernel density and barrier degree models were used for the analysis. Finally, the study examined the key factors that affect the coordination of marine ecology and the economy in these regions using the barrier degree model. The evaluation index for coastal areas decreased from 0.179 to 0.153, indicating a decline in the marine environment. The eastern and southern marine economic circles exhibited a fluctuating upward trend. To enhance coordination between the economy and the ecological environment, this study recommends that coastal provinces prioritize environmental protection, adopt green development principles, increase investment in science and technology, and accelerate the transformation of marine science and technology.

This study investigated the presence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNAs on the surface of microplastics (MPs) collected from a hospital wastewater treatment plant (WWTP) and the Qara-sou river in Kermanshah, Iran. The MPs were characterized using stereo-, scanning electron-, and Fourier-transform infrared spectroscopies to determine their appearance, quantification, qualification, and morphology. The virus RNAs were extracted by rinsing the surface of the MPs with distilled water, followed by swapping and transferring the scratched material into viral transport medium. Identification was performed using SARS-CoV-2 molecular detection kits and real-time quantitative polymerase chain reaction (RT-qPCR). The most common type of MPs found in the wastewater acted as a vector for the virus RNA, whereas virus RNA was only identified in one sample of river water. These findings suggest that MPs can facilitate the spread of the virus through WWTPs and into receiving water bodies. Thus, research on MPs acting as carriers of COVID-19 should be emphasized as determining the presence of the coronavirus on the surface of MPs is crucial in determining a country's health strategies. Furthermore, this study shows that MPs have the potential to act as vectors for pathogens and create new microbial niches in aquatic environments.

Microplastics were discovered in sea salts worldwide because they are directly supplied by seawater. This study explores the contamination of five traditionally produced and 10 branded sea salts with microplastics. The highest number of particles was found in the traditionally produced salt (563 items) an abundance of 106.67–3753.33 items/kg. Branded salts had abundance of 25.67 to 866.67 items/kg. There was no significant difference (p > 0.540) in the amount and abundance between these salts. The most predominant shape of microplastics was fiber. The particles sizes ranged from 17 μm to 4.86 mm. The predominant polymers were polyethylene terephthalate and polypropylene. The results indicate both traditionally produced and branded salts are contaminated with microplastics. It is necessary to implement technology to eliminate microplastics from abiotic sea salt to protect health and the environment.

The marine economy constitutes a regional economic system centered around a specific marine geographical area, including coastal zones, and is dependent on marine resources and the environment. This study focuses on investigating the developmental spatial environment of marine cities, specifically examining the evolution of economic development capacity and resource spatial structure. Shenzhen is chosen as the research subject. Utilizing a set of comprehensive evaluation indices and a regression method based on the spatially expanded Tobit model, we conduct a thorough assessment of the city's economic development capacity. Additionally, an analysis of the spatial and temporal distribution patterns, as well as the changes in marine economic density and the evolution of marine city resources, unveils the profound alterations in the spatial structure of marine city resources during rapid economic development. This research not only provides a theoretical foundation but also practical insights for the sustainable development of marine cities.

With the advancement of technology, ocean observation techniques have become increasingly prevalent in estimating marine variables such as Sea Surface Temperature (SST). This progress has led to a substantial surge in the volume of marine data. Presently, the abundance of available data presents a remarkable opportunity for training predictive models. The prediction of SST poses a challenge due to its temporal-dependent structure and multi-level seasonality. In this study, we propose a deep learning approach that combines the Bidirectional Long Short-Term Memory (BiLSTM) model with the attention mechanism to forecast SST. By leveraging the BiLSTM's ability to effectively capture long-term dependencies through both forward and backward LSTM processing, the attention mechanism accentuates salient features, thereby enhancing the model's evaluation accuracy.

To evaluate the effectiveness of the Attention-BiLSTM model in predicting SST, we conducted a case study in the Moroccan Sea, focusing on four distinct regions. We compared the performance of the Attention-BiLSTM model against alternative models such as LSTM, Attention-BiGRU, XGBoost, Random Forest (RF), Support Vector Regression (SVR), and Transformers in forecasting the SST time series.

The experimental results unequivocally demonstrate that the Attention-BiLSTM model achieves significantly superior prediction outcomes and is a good candidate for deployment in the field.

High-resolution assessment of future wind resources is crucial for formulating appropriate energy strategies. However, the response of offshore wind energy to changing climate remains inconclusive. This study uses bias-corrected CMIP6 and time-varying sea surface temperature data to drive the Weather Research and Forecasting (WRF) model and project future changes in wind energy resources in the northern South China Sea (SCS) under SSP2–4.5 and SSP5–8.5 scenarios for 2050 and 2100. The findings indicate that wind resources in the waters north of 18°N in the northern SCS generally show an increased change, with greater wind resources in 2100 than in 2050. The SSP5–8.5 scenario exhibits a more significant increase than the SSP2–4.5 scenario. The future wind energy changes in the western and eastern nearshore waters of Guangdong, where numerous offshore wind power plants are currently established, are largely consistent with the overall change in the northern SCS. Nevertheless, there may be a decreased change in future wind resources in the central and eastern regions of the SCS.

Marine and port economy estimation is conducive to the understanding of the development law of marine economy degree. This study proposes a neural-learning network estimation model of the marine economy degree based on a priori architectural knowledge and adopts time-combined class array columns and multivariate modeling methods to estimate the indicators reflecting the development level of the marine economy degree in the ZJP region. The study adopts the PK_NN multivariate modeling method, taking cargo transportation volume, cargo turnover, cargo carrying value of ports near the sea, foreign trade throughput, port container throughput, and port container throughput as multivariate model inputs, and compared with the other modeling methods, the model of the time combination class array columns of type GM_11, which has a better comprehensive performance. Finally, the PK_NN time-combined class array column model is used to estimate the development level of the marine economy in the ZJP region near the seaport from 2011 to 2020, and the results show that the estimated value of the marine economy in the ZJP region is close to the actual planning value of the ZJP region. The algorithm was applied to estimate the economic degree curves of the five near-seaport areas of ABCDE under different harbor head construction art modes, and the results showed that the relative value error of the estimation was controlled between 4% and 10%, and the fluctuation ranges of each month's specific growth value area estimation were comparable. This proves the effectiveness and accuracy of the a priori marine neural-learning-based network algorithm in this paper.

Laboratory experiments were conducted to determine the thermal tolerance of the living shallow-water and intertidal gastropods from lagoons in Bahrain and Saudi Arabia, in the western Arabian Gulf. Our experimental trials, run in duplicate using a semi-controlled thermal incubator, quantify the thermal limits of two species of gastropods, the tropical periwinkle Planaxis sulcatus (Born, 1778) and the mud creeper Pirenella conica (Blainville, 1829), which are commonly found in the region. The two species display different thermal tolerances to heat exposure during this study. In the case of Planaxis sulcatus, we observe that half of the test specimens that are fully exposed to the air enter an inactive state or become comatose at about 39 °C, while half of specimens that are fully immersed in sea water become immobile around 42 °C. For Pirenella conica half of test specimens that are fully exposed enter become inactive at about 37.5 °C, while for specimens that are fully immersed in sea water this temperature is around 45 °C. At 60 °C total mortality is observed with no indication of recovery. These observations have implications for climate change predictions in the western Gulf region, as water temperatures in the lagoon already reach 42 °C in summer, while the substrate temperatures on mud flats exposed during low tide exceed the lethal limit of the gastropods during the summer months.

Mangrove ecosystems are vital coastal habitats with rich biodiversity and play a significant role in carbon sequestration, these habitats are facing mounting threats from rapid urbanization. This study delves into assessing the sediment bacterial communities from the urban mangrove habitats of Campal and Panaji, within the Mandovi estuarine environment of Goa, to understand the intricate interplay between urbanization and bacterial dynamics in the mangrove habitats. We used a combined approach of 16S amplicon and shotgun sequencing methodologies to understand the bacterial taxonomic composition and functional profiles. The community structure revealed the dominance of bacterial groups from phylum Proteobacteria, Chloroflexi and Actinobacteria at both locations. The impact of urbanization was evident from the increased abundance of pathogenic groups at class and genus levels in this region. The core microbiome analysis showed the presence of Shewanella, Pseudomonas and Clostridium which are mostly pathogenic, anaerobic taxa Woeseia, Rheinheimera, like genera that are involved in the organic matter cycling and unclassified bacteria. Though increased pathogenic forms are reported, it is evident that the dominant taxa also included groups that contributed to the biogeochemical cycling of organic matter in sediment from these locations. Functional diversity elucidated through shotgun metagenomics analysis showcased the predominance of carbohydrate metabolism and the presence of glycoside hydrolases degrading plant-based starch, pectin and cellulosic organic matter. The occurrence of xenobiotic biodegradation pathways is an indication of the presence of xenobiotic degrading microbes as a natural means of degrading high amounts of pollutants at this location. Comparative analysis of the metagenomes from this study with similar earlier studies at Ribandar, Mandovi and Cortalim, Zuari mangrove habitats of Goa with varying pollution levels also reiterates the terrestrial influence on the microbial community in these habitats. It showed that Panaji and Campal locations had the presence of dominant pathogenic forms which was absent in the other two locations. The Ribandar and Coratlim location which is reported to have a comparatively lesser impact due to anthropogenic activity had an increased abundance of distinct genera which are predominant heterotrophic forms involved in remineralization and reduced levels of pathogens. Our findings highlight the profound influence of urbanization on the sediment mangrove bacterial communities and spotlight the resilience and adaptability of these microorganisms. This calls for immediate action and preventive measures to restore their functional potential in maintaining the health of these ecosystems amidst expanding urban landscapes.

This study first constructs an evaluation index system based on the pressure state response model, and assigns weights through entropy method and coefficient of variation method, providing theoretical and methodological support for comprehensive measurement and evaluation. Second, the least squares decision model is introduced and the PVAR model is used to analyze the development level of China's marine economy, ecology, and technological and financial innovation. The results indicated that from 2012 to 2022, the marine economic development level, marine ecological development level, and marine technology and financial innovation development level of 9 coastal provinces in China all showed a certain growth trend. However, in terms of the level of marine ecological development, various provinces had shown a downward trend, with Hebei performing the best, with an average of 0.230. Although various regions have achieved significant development in marine economy, ecology, and technological and financial innovation, the level of development varies among regions, and some regions have relatively low levels of technological innovation. The pressure and challenges between the marine economy and ecological environment protection caused by these real environments remain significant.