MS-222 is widely used for fish anesthesia, but data on its rapid induction effects and cardiac safety in goldfish (Carassius auratus) are limited. This study evaluated the behavioral and electrocardiographic responses of a total of 50 goldfish (body length: 6.8 +/- 0.6 cm; body weight: 9.8 +/- 1.9 g) exposed to five MS-222 concentrations of 0.8, 1.2, 1.6, 2.0, and 2.4 g/L. Induction time decreased and recovery time increased with rising concentration. Heart rate exhibited a significant dose-dependent decline (P < 0.05). Notably, R-wave amplitude was significantly reduced at 2.4 g/L (P < 0.05), indicating potential myocardial electrophysiological risk. The concentration range of 1.2-1.6 g/L effectively balanced rapid induction and cardiac safety, whereas 2.4 g/L was identified as a risk threshold. These results support the use of ECG as a sensitive tool for anesthesia safety assessment and provide a reference for the rapid anesthesia application of MS-222 in goldfish aquaculture and research.

Larimichthys crocea and Larimichthys polyactis, two commercially and ecologically important sciaenid species, are often morphologically confused (especially at the juvenile stage or for incomplete specimens), leading to limitations in traditional morphological taxonomic methods for accurate identification. Otoliths, as stable hard tissues with species-specific morphological characteristics, serve as an ideal tool for species discrimination. To investigate the efficacy of landmark-based methods in extracting morphological information from different surfaces of sagittal otoliths, this study analyzed six surfaces (medial, lateral, dorsal, ventral, anterior, and posterior) of left otoliths from two sciaenid species using geometric morphometrics. We collected 487 sagittal otolith samples from sciaenids in the Zhoushan Islands of the East China Sea (Larimichthys polyactis: 277 specimens; Larimichthys crocea: 210 specimens). Landmark coordinates were extracted using tps-series software, and morphological differences were quantified through principal component analysis (PCA), discriminant analysis, and thin-plate spline visualizations. Key results include: relative warp PCA showed cumulative contributions of PC1 + PC2 at 52.48% (medial), 52.87% (lateral), 71.29% (dorsal), 63.7% (ventral), 64.8% (anterior), and 67.85% (posterior), effectively discriminating species with Type I/III landmarks demonstrating highest contributions; centroid size analysis revealed significantly larger values in L. crocea across all surfaces (most pronounced on medial surface: F = 183.450, p < 0.05); discriminant analysis achieved peak cross-validated success on the medial surface (98.6% for L. polyactis, 95.2% for L. crocea), with other surfaces ranging from 79.6–83.6%. This confirms that multi-surface landmark analysis effectively captures morphological divergence, with the medial surface providing optimal species discrimination. The established method provides a reliable supplementary tool for the taxonomy of L. crocea and L. polyactis, and offers scientific support for fisheries resource survey, population dynamic monitoring, and conservation of these sciaenid species.

Coasts, including estuaries, wetlands, mangroves, etc., have long been recognizedfor their critical role in providing and maintaining the ecological services on which wedepend [...]

Large-scale marine resource development and utilization projects will disturb sediment, cause sediment resuspension, and furtherly cause the release of heavy metals, threatening the safety of ecosystems and biodiversity. This study described the sources of heavy metals in marine sediment, sorted out the simulation devices of heavy metal release caused by the external disturbance and sediment resuspension, detailed the influencing factors and rules of heavy metal release, summarized the kinetic models of heavy metal release, pointed out the current research progress and problems of heavy metal release from sediment, and put forward suggestions. It is found that the current researches on the release of heavy metals in sediment are limited to indoor simulation, and the simulation disturbance devices cannot accurately judge the quantitative relationship between the simulated disturbance intensity under experimental conditions and the one under natural conditions, such as wind wave and current. Among them, particle entrainment simulator (PES) device, EROMES device and Y-type resuspension device are more suitable for simulating the hydrodynamic sediment resuspension process in shallow water. The annular flume device can better simulate the marine environment. Studies on the factors influencing the release of heavy metals mainly focus on the physical and chemical properties of sediment and overlying water conditions, among which the physical and chemical properties of sediment, dissolved oxygen (DO), redox potential (Eh) and pH of overlying water are the main regulatory factors for the release of heavy metals from sediment resuspension. Elovich model and double constant model have a wide range of application in describing the release kinetics of heavy metals. It is pointed out that in the future, in-situ test experiments combined with indoor physical model tests and numerical simulation can be carried out to build a dynamic model of heavy metal release from sediment that is closer to the natural situation, which can provide references for the study of heavy metal release in marine sediment caused by ocean engineering and the formulation of relevant protection and restoration schemes.

The harmful effects of marine microplastic pollution on organisms have attracted widespread attention, but research on the toxic effects of combined pollution formed by microplastics adsorbing petroleum in intertidal sediments is relatively scarce. In this study, acute toxicity of the single and combined pollution of Polyethylene microplastics (PE MPs) and diesel on Tegillarca granosa after 96 h exposure was investigated in terms of oxidative stress related biochemical indicators, histopathology, DNA damage and gene expression, respectively. The results showed that microplastics-diesel combined exposure resulted in increased SOD activity in both the gills and the visceral mass of T. granosa, whereas GPx and GST activities were inhibited. However, no significant change in MDA content was observed under short-term exposure conditions. The Integrated Biological Responses version 2 (IBRv2) index revealed that the gills exhibited higher sensitivity to the combined pollutant. High-concentration combined exposure induced histopathological alterations (gill swelling, digestive tubule necrosis of the visceral mass) and DNA damage. Furthermore, high-concentration combined pollution upregulated the gene expression of cytochrome P450 Family 2 (CYP2 family), GST, CAT, GPX, and SOD1, while downregulating the KEAP1. It indicated that combined pollutants can regulate antioxidant genes by activating the cytochrome P450 (CYPs) enzyme system and the KEAP1-NRF2 signaling pathway, interfere with the antioxidant defense system of T. granosa, and produce an enhanced toxic effect. The research revealed the toxic effects and molecular mechanisms of microplastic-petroleum combined pollution on T. granosa, providing a scientific basis for assessing the ecological risks of combined pollution in marine environments.

The morphological indexes serve as a critical biological foundation for analyzing species dimorphism, play a pivotal role in population dynamics models and species assessments, and provide valuable, accurate, and costefficient biological information. Dimorphism identification holds significant importance for the conservation and sustainable development of Larimichthys crocea resources. Therefore, this study aims to validate the dimorphism effects of various morphological indexes using interpretable machine learning techniques and evaluate model performance and deviation in automatic identification. First, data visualization, significance analysis, correlation analysis, and principal component analysis (PCA) were applied to otolith morphology (OM) indexes and fish body morphology (FM) indexes. Then, the SHAP (SHapley Additive exPlanations) method of machine learning was used to analyze the importance of different morphological indexes and output the morphological indexes of importance. Finally, different machine learning models were used to analyze the identification performance and deviation of Larimichthys crocea dimorphism. The experimental results demonstrate that the SHAP method effectively prioritizes the importance of different morphological indexes, with the importance of OM indexes primarily concentrated in the sulcus. Within the machine learning models, OM indexes achieved a peak identification rate of 71 % (Random Forest), whereas FM indexes reached a maximum identification rate of 65 % (Random Forest and Support Vector Machine). The comparative analysis of the average effects of different models, including evaluation metrics and learning curves, demonstrates that OM indexes outperform FM indexes in terms of identification performance. The application of machine learning models not only enables a comprehensive analysis of the dimorphism in Larimichthys crocea but also offers effective strategies for the conservation of Larimichthys crocea resources and their associated biodiversity.

Carbon emissions from freshwater aquaculture can exacerbate the greenhouse effect, thereby impacting human life and health. Consequently, it is of great significance to explore the carbon peak process and the role of emission reduction data in China’s freshwater aquaculture industry. This study innovatively employs the Logarithmic Mean Divisia Index model (LMDI) and the Tapio decoupling model to conduct an in-depth analysis of the relationship between carbon emissions and output values in the freshwater aquaculture industry, accurately identifying the main driving factors. Meanwhile, the global and local Moran’s I indices are introduced to analyze its spatial correlation from a new perspective. The results indicate that from 2013 to 2023, carbon emissions from China’s freshwater aquaculture industry exhibited a quasi-“N”-shaped trend, reaching a peak of 38 million tons in 2015. East China was the primary contributor to carbon emissions, accounting for 46%, while South China, Central China, and Northeast China each had an average annual share of around 14%, with Southwest, North China, and Northwest China contributing relatively small proportions. The global Moran’s I index showed a decreasing trend, with a p-value ≤ 0.0010 and a z-score > 3.3, indicating a 99% significant spatial correlation. High-high clusters were concentrated in some provinces of East China, while low-low clusters were found in Northwest, North, and Southwest China. The level of fishery economic development positively drove carbon emissions, whereas freshwater aquaculture production efficiency, industrial structure, and the scale of the aquaculture population had negative effects on carbon emissions. During the study period, carbon emissions exhibited three states: weak decoupling, strong decoupling, and expansive negative decoupling, with alternating strong and weak decoupling occurring after 2015.

The marine environment is highly complex, characterized by substantial fluctuations in flow velocity. To enhance the adaptability of robotic large yellow croakers to such conditions, this study takes into account multiple factors, including shape, dimensions, and material properties, and evaluates their hydrodynamic resistance characteristics. A 2D model of large yellow croakers aged 1, 4, 7, 10, and 12 months was established as the bionic object. Based on computational fluid dynamics, the water resistance characteristics of this model were investigated in the same water environment. A 3D model of this species based on the 2D model and three skin materials, PE, PC, and ST, was added, and the effects of these materials on the water resistance of the 3D model were investigated. It was shown that in a water environment with a current speed of 0.1~1 m/s, the water resistance of large yellow croaker models at different ages ranged from 0.1006 to 6.8485 N; that of croakers with different body lengths ranged from 0.1067 to 28.5760 N; and that of croakers with different skin materials ranged from 0.0048 to 0.8672 N. The results showed that in the water environment with a current speed of 0.1–1 m/s, the 12-month-old large yellow croaker model had a lower water resistance range of 0.1006~3.6512 N in the watershed compared with other models of the same age; the large yellow croaker models with body lengths of 20, 30, and 40 cm had a smaller range of water resistance of 0.1125~12.5110 N in the watershed compared with other models of the same body length; and large yellow croaker models made of PE had a smaller range of resistance of 0.0048~0.7523 N in the watershed compared to those made of PC and ST materials. The results of this study are important for the design and fabrication of robotic fish capable of prolonged underwater operations.

Marine oil spills lead to intertidal sediment pollution, causing benthic bioaccumulation and toxicity. However, relatively few studies have been conducted on the effects of crude oil sediment pollution on benthos. In this study, Sinonovacula constricta was used as the research object in a sediment environment to study the accumulation and elimination effects of S. constricta on long-term exposure to crude oil pollution as well as the toxicity effects at the biochemical and tissue levels through laboratory exposure tests. The objective of this study was to provide theoretical support for monitoring the biological toxicity of intertidal crude oil pollution. The results showed that S. constricta accumulated petroleum hydrocarbons in the sediment, which were positively correlated with pollution concentration and time. The fitting results of the two-compartment kinetic model were good and could be applied to the accumulation and elimination of sediment crude oil pollution. The activity of antioxidant enzymes and the content of malondialdehyde in the gills were mainly induced, and there was a dose- and time-dependent relationship. Crude oil pollution can cause digestive tube ablation, lumen swelling, and blood cell infiltration in the viscera of S. constricta. S. constricta can be used as an indicator organism for oil pollution in the intertidal zone, and its gills and visceral mass can be used as target tissues.

In the context of the growing demand for the sustainable development and conservation of fish stocks, artificial intelligence (AI) technologies are essential for supporting scientific fish stock management. Artificial intelligence technology provides an effective solution for the intelligent recognition of fish information. This study used bibliometric analysis to review a sample of 719 scientific articles from the WoSCC (Web of Science Core Collection) database from 2014-2024. The results revealed a significant increase in the number of publications from 2014-2024, with publications mainly from China, the USA (the United States) and other developed countries. The top three impactful journals are Ecological Informatics, Computers and Electronics in Agriculture and the ICES Journal of Marine Science. The most frequent keyword co-occurrence analysis was deep learning, and the best keyword clustering effect was computer vision. The findings indicate that this bibliometric evaluation provides a holistic visualization of the research frontier of AI in fish information identification, and our findings underscore the growing global importance of AI in fish information identification research and highlight publication trends, hotspots, and future research directions in this area. In conclusion, our findings provide valuable insights into the emerging frontiers of AI-based fish information identification.

In this study, a comparison of the concentrations of eight heavy metals (including Fe, Mn, Cu, Zn, Cr, As, Cd, and Hg) was conducted between wild and cultured Oplegnathus fasciatus. Significant differences in the concentrations of Zn, Cd, As, and Hg were observed between wild and cultured Oplegnathus fasciatus. The results showed that the mean Zn concentration was significantly higher in cultured Oplegnathus fasciatus (3.051 ± 0.738 mg/kg) when compared to its wild counterpart (2.512 ± 0.407 mg/kg). In contrast, the mean Cd concentration was found to be lower in the cultured Oplegnathus fasciatus (0.001 ± 0.0007 mg/kg) than in the wild ones (0.003 ± 0.003 mg/kg). Likewise, the wild samples demonstrated a higher mean As concentration (1.494 ± 0.659 mg/kg) than the cultured samples (0.594 ± 0.215 mg/kg). Lastly, it was noted that the mean Hg concentration was considerably higher in the cultured Oplegnathus fasciatus (0.042 ± 0.016 mg/kg) than in the wild specimens (0.014 ± 0.011 mg/kg). Pollution levels and health risks were evaluated using the single-factor pollution index (SFI), metal pollution index (MPI), and health risk assessment methods. The results showed that, for Cu, Zn, Cr, and Cd, both wild and cultured Oplegnathus fasciatus had SFI values below 1 compared to the marine organism quality standards. The MPI values for wild and cultured Oplegnathus fasciatus were 0.188 ± 0.051 and 0.172 ± 0.054, respectively, both far below the safety limit of 2 for pollution-free aquatic products. The Hazard Index (HI) for wild and cultured Oplegnathus fasciatus were below 1, indicating no health risks from long-term consumption. A discriminant analysis, based on Zn, Cd, As, and Hg concentrations, distinguished wild from cultured Oplegnathus fasciatus with a 96.0% accuracy, remaining stable at over 94.9% upon cross-validation. These findings accurately evaluate that there is no risk to human health from consuming Oplegnathus fasciatus, which is significant in safeguarding public health.

This paper uses spatial interpolation to reconstruct the three-dimensional surface of midwater trawl, and the trawl surface is successfully reconstructed with a variety of different surface patch functions and weight functions. The entire internal space of the trawl is decomposed into a finite number of tetrahedral volume elements that are seamlessly connected in sequence. Two different methods (central radiation method and signed volume method) are proposed to calculate the trawl volume. Compared with the Delaunay triangulation, the layered free triangulation method proposed in the present study can obtain a smoother and more reasonable trawl surface. By combining the weight functions (5), (6), (7), and (9) with the two-order surface patch function (10), taking four coordinate points to fit the surface patch function for the cod-end of the trawl, and taking eight coordinate points to fit the surface patch function for the other parts, the better and smoother trawl surface can be obtained. However, the interpolation surface, obtained by combining the weight function (7) and the surface patch function (10), should be the best result, because the interpolation surface is naturally smooth, and the gradient is gentle and reasonable. The symbolic volume method has wider applicability.

Tuna are economically important fish species. The automated identification of tuna species is of importance in fishery production and resource assessment in that it would facilitate the informed monitoring of tuna fishing vessels and the establishment of electronic observer systems. As morphological characteristics are important for tuna identification, this study aims to verify the performance of the automated identification of three Thunnus species through morphological characteristics based on different machine learning algorithms. Firstly, morphological outlines were visually analyzed using EFT (elliptic Fourier transform) and CNN (convolutional neural network). Then, the EFT feature data and deep feature data of the tuna outline images were extracted, and principal component analysis of the two different morphological characteristics was performed. Finally, different machine learning algorithms were used to analyze the identification performance of tuna of the same genus and different species. The experimental results showed that EFT features had the highest identification accuracy in KNN (K-nearest neighbor), with 90% for T. obesus, 90% for T. albacores, and 85% for T. alalunga. Deep features had the best identification performance in SVM (support vector machine), with 80% for T. obesus, 90% for T. albacores, and 100% for T. alalunga. Deep features were better than EFT features in identification performance. The biodiversity and intergeneric differences among tuna species can be well analyzed using these two different morphological characteristics. Machine learning algorithms open up the way for rapid near-real-time electronic observer systems in these important international fisheries.

Numerical simulation is an important method for calculating the hydrodynamic performance of otter boards used in sea floor trawling. Although such simulations have been explored in prior studies, the effects of the proximity of the otter boards to the seafloor and the plume of upward-drawn sediment during bottom trawling have largely been ignored. In this study, we assessed these factors. The results show that within the angles of attack used during normal operations, the effect of the seafloor bottom boundary of the flow field on the hydrodynamic performance of an otter board is obvious. We found that when the ratio of the distance between the bottom of an otter board and the surface boundary of the flow field to the chord length of the board exceeds 0.4, the influence of the bottom boundary of the flow field on the hydrodynamic performance of the board is negligible. For values of less than 0.4, the seafloor bottom boundary has an increasingly obvious impact on the hydrodynamic performance as this ratio decreases. We also found that the turbid plume of ocean floor sediment raised during bottom trawling has an obvious effect on the lift and resistance coefficients of an otter board at high angles of attack. At low angles, this effect on the lift-to-drag ratio is reversed and less obvious. The simulation results show that the optimal lift-to-drag ratio decreases with an increase in the sediment concentration; however, beyond a certain threshold, an increasing concentration of sediments was not found to have an obvious impact on the lift-to-drag ratio.

为了进一步了解和促进我国休闲渔业的健康发展,选取了 2011-2020 年休闲渔业及其七大相关产业统计数据,对我国休闲渔业及相关产业进行灰色关联度分析.研究结果表明,休闲渔业与金融业灰色关联度位于所有指标的首位,说明金融业对于休闲渔业具有强大的影响力和带动作用;休闲渔业与房地产业、批发零售业、建筑业以及水产养殖业灰色关联度排名都比较靠前,联系较为紧密;与餐饮住宿、交通运输、仓储邮政业联系最少,这与我国休闲渔业发展相对较晚,在旅游经济中所占比重较少有关.为了促进我国休闲渔业的发展,建议加大政策和金融扶持力度,在科学调研的基础上建立信息数据库,坚持产学研结合和创新驱动,积极探索渔文化,因地制宜发展地方特色的休闲渔业文化品牌.

The spatial surface of the midwater trawl was reconstructed with combined interpolation methods of cubic spline, cubic Heimite and polar-coordinate periodic spline interpolation. The results show that the trawl surface obtained only by the ring section method or the vertical section method has a certain deviation, especially when cubic spline is used only in the X direction. When the ring section is combined with the vertical section, and the cubic spline is combined with the cubic Heimite in the X direction, the smoothest feasible trawl surface can be obtained. Two different trawl volume algorithms (volume element method and numerical integration method) were proposed. The finite volume element method can accurately calculate the volume inside the trawl, and the approximation calculation result of the numerical integration method is also very ideal. The numerical integration method is easier to calculate and suitable for the calculation of the trawl volume under any circumstances.

Tuna resources are an important part of China's pelagic fishery production. However, for China's tuna fishery, tuna species caught at sea are still manually classified, which is a time-consuming and inefficient process; so China's tuna fishery needs to develop toward automation. This study uses gray-level co-occurrence matrix (GLCM) and VGG16 to visualize phenotypic texture through local images of three Thunnus species. At the same time, texture feature index data (TFD), deep feature data (DFD), and their combined feature data (CFD) are obtained from texture images. Support vector machine (SVM) with different kernel functions is used to classify phenotypic texture of tuna automatically. The study shows that visualized texture images of different tuna using GLCM and VGG16 have biological characteristics. In the classification results without cross-validation, the average classification accuracy of TFD in polynomial was 83%, the average classification accuracy of DFD in RBF (Radial basis function) was 93%, and the average classification accuracy of CFD in RBF was 95%. It is concluded that tuna phenotype texture can be efficiently classified by using SVM with different kernel functions.

为研究暗适应条件下斑马鱼Danio rerio视网膜电图(ERG)试验中的最佳试验参数和光谱敏感性,选取体长为3.5～4.0 cm的6月龄斑马鱼,探究了斑马鱼视网膜电图试验中的最低暗适应时间和闪光刺激时间间隔,以ERG的b波振幅分量作为对光刺激的响应分析了斑马鱼的暗视光谱敏感性.结果表明:斑马鱼的ERG试验中暗适应时间至少为90 min(t检验,P>0.05),闪光刺激时间间隔至少为50 s(配对t检验,P>0.05);暗适应条件下,斑马鱼的光谱敏感性函数在可见光波段和紫外光波段均出现了敏感峰值,敏感峰值分别出现在500 nm和365 nm波长处,且紫外敏感峰值相较于可见光敏感峰值降低约0.28个lg单位.研究表明,暗适应的斑马鱼对可见光和紫外光均表现出敏感性,其视网膜中的U-视锥细胞和视杆细胞共同参与了暗视视觉,增加了暗视光谱敏感范围,从而提高了暗视视觉的灵敏度.

As a cephalopod with a short life cycle, the Dosidicus gigas (jumbo flying squid) is extremely sensitive to climate variability and marine environment changes in terms of individual growth and resource changes. Based on 7514 D. gigas samples collected off Peru from 2008 to 2020, the fishery biological characteristics such as size, sexual maturity, and size-at-maturity were analyzed to explore the impacts of climate variability on individual growth. The results showed that there were significant differences in the relationship between mantle length and body weight and in the composition of sexual maturity between male and female individuals in different years (P < .05). La Nina events were conducive to the individual growth of D. gigas and slowed down their sexual maturity, producing D. gigas groups in medium and large sizes; El Nino events inhibited the individual growth of D. gigas and accelerated their sexual maturity, producing D. gigas groups in a smaller size. From 2008 to 2020, the mantle length of the small-size group decreased by 46 mm, while that of the medium-size group increased by 28 mm. Size-at-maturity of female D. gigas decreased by 201.2 mm and that of male D. gigas decreased by 143 mm. The study concluded that the changes in the marine environment caused by climate variability from 2008 to 2020 have had a significant impact on the population structure, growth, and development of the D. gigas off Peru.

Under tidal scouring, residual petroleum in the intertidal sediment after oil spills could release again, causing secondary pollution in the marine ecosystem. The current study aimed to investigate the dynamic process and principles of crude oil release from silty intertidal sediment under different influencing factors and screened for the key factors. In this paper, the fitting equations and correlation between the release amount and various factors were explored through the single-factor and orthogonal experiments. Then, the key influencing factors were selected for multi-factor fitting of the release amount. The results showed that the oil release amount rose with the increase in oil concentration, oscillation frequency, and release time, but decreased with an increase in salinity. As the pH decreased, the oil release amount increased. The relationship between release amount and concentration/oscillation frequency can be equipped by the polynomial equation, and the average R2 was 0.95 and 0.84, respectively. The release amount can be fitted by the Lagergren pseudo-second-order kinetic equation with time, with the average R2 0.89. The pH was negatively correlated with the release amount in the fresh contaminated sediment but positively correlated with the weathered one. The correlation between each factor and oil release amount was ranked (from large to small) as oil concentration, oscillation frequency, salinity, time, and pH. At last, a polynomial equation can be fitted between the key influencing factors (oil concentration and oscillation frequency) and the release amount. The results can provide a theoretical basis for predicting the secondary pollution owing to the oil re-release from intertidal sediment.