A primary problem affecting the sustainable development of aquaculture is fish skin diseases. In order to prevent the outbreak of fish diseases and to provide prompt treatment to avoid mass mortality of fish, it is essential to detect and identify skin diseases immediately. Based on the YOLOv4 model, coupled with lightweight depthwise separable convolution and optimized feature extraction network and activation function, the detection and identification model of fish skin disease is constructed in this study. The developed model is tested for the diseases hemorrhagic septicemia, saprolegniasis, benedeniasis, and scuticociliatosis, and applied to monitor the health condition of fish skin in deep-sea cage culture. Results show that the MobileNet3-GELU-YOLOv4 model proposed in this study has an improved learning ability, and the number of model parameters is reduced. Compared to the original YOLOv4 model, its mAP and detection speed increased by 12.39% and 19.31 FPS, respectively. The advantages of the model are its intra-species classification capability, lightweight deployment, detection accuracy, and speed, making the model more applicable to the real-time monitoring of fish skin health in a deep-sea aquaculture environment.

The predominant form of aquaculture is the facility fishery, which is also subject to significant impacts from marine disasters. Conducting research on the extraction of facility fishery areas based on remote sensing technology is crucial to efficiently comprehending the configuration of coastal culture patterns and to establishing scientifically sound plans for managing and administering these areas. The extensive dispersion of facility fishery areas in coastal regions poses a challenge to the conduction of comprehensive field surveys. The utilization of satellite remote sensing images for information extraction has emerged as a significant area of research in the fields of coastal fishery and ecological environment. This study provides a systematic description of the current research status of coastal fishery area extraction methods using remote sensing technology from 2000 to 2022 reported in the literature. The methods discussed include the visual interpretation method, image element-based classification, object-based classification, supervised classification, unsupervised classification, and neural network classification. The extraction accuracy of each method in the coastal facility fishery area is evaluated, and the advantages and disadvantages of these methods, as well as their limitations and existing problems, are analyzed in detail, to construct a reference framework for the investigation of the high-precision extraction of facility fishery areas from satellite remote sensing images.

Knotless nets have been extensively used in sea cages and offshore fish farms; the explicit illustrations of local flow patterns and subjected hydrodynamic loads have practical implications for the safe operations of aquaculture pens in open oceans. However, the effects of inclination angles of knotless nets on local flow patterns have not yet been fully discussed. In this paper, the effects of inclination angles on local time-averaged and instantaneous flow fields, velocity reductions and force coefficients are investigated using a $k-\omega$ shear stress transport-improved delayed detached eddy simulation (SST-IDDES) high-fidelity turbulence model. It is demonstrated that the inclination angles have dominant effects on the time-averaged velocity magnitudes around the net meshes. Secondly, the considerable flow interactions amongst the transverse and longitudinal net meshes, as well as cross-flow effects, are observed but weakened with the inclination angles. Thirdly, the profiles of velocity decelerations behind the net panels for 0${}^{\circ }$–45${}^{\circ }$ are not as trivial as those for 45${}^{\circ }$–90${}^{\circ }$. The associations between the embedded mechanism of subjected loads and pressure fields are established to analyse the current loads on nets in small inclination angles. The inclination angles are finally elaborated into the area-averaged velocity reduction and screen force models, then the improved characteristics are validated against the experimental data.

Estuaries provide nursery habitats for a variety of fish species of different ecological guilds and have complicated environmental conditions. In this study, we applied ensemble species distribution models (SDMs) to four abundant and different ecological guild larval fish species (Hemiculter bleekeri (freshwater guild), Pseudolaubuca sinensis (freshwater guild), Coilia mystus (brackish water guild), and Engraulis japonicus (marine guild)) to explore their suitable habitats and the fish–habitat relationships in the Yangtze Estuary. The results showed that random forest (RF) demonstrated the best performance in all single algorithms and the surface range envelop (SRE) model was scarcely accurate. The ensemble SDMs demonstrated a superior predictive ability compared with any single algorithm, with the true skill statistic (TSS) and the area under the receiver operating characteristic curve (AUC) scores being above 0.899 and 0.641, respectively. Binary presence–absence maps showed the different spatial distribution patterns of the four species. We primarily found the freshwater species (P. sinensis and H. bleekeri) present in the South Branch (west of 122° E), whereas we found the marine species (E. japonicus) anywhere except inside the South Branch (west of 121.8° E). The area for P. sinensis (1615.93 km²) was relatively larger than that for H. bleekeri (1136.87 km²). We predicted that the brackish water species (C. mystus) would most likely be present inside the North Branch (west of 122° E), Eastern Chongming, and outside the South Branch (east of 121.8° E). Salinity, as a key environmental variable, contributed to the spatial variability. A low salinity (sea surface salinity (SSS) < 3) was beneficial for P. sinensis and H. bleekeri but was not suitable for E. japonicus. The SSS suitable range for C. mystus was 5–10 and 12–20. Multiple ecological guild species dwelled in the confluence of salt and fresh water. Our results will play an important role in the design of specific conservation strategies for fishery resources in this area.

An orthogonal experiment was conducted to study the effects of the aspect ratio, camber of the fore wing, and gap ratio of front and rear wing panels on the hydrodynamic performance of double-vane otter boards. The design of the orthogonal experiment comprised three factors (each having three levels), namely the aspect ratio (1.0, 1.5, and 2.0), camber (0.12, 0.14, and 0.16), and gap ratio (0.25, 0.30, and 0.35), the drag coefficient C_x and the lift coefficient C_y of nine otter board models obtained in a wind tunnel experiment, and the lift–drag ratio K obtained by calculation. The lift–drag ratio for a working angle of attack of 30° was selected as the inspection index, and the experimental data were analyzed in an orthogonal design-direct analysis. Analysis of each factor revealed that the optimal level combination of factors was A₃B₃C₃ and that the decreasing order of the effects of the factors was A (aspect ratio) > B (gap ratio) > C (camber). The orthogonal experiment thus obtained an optimal otter board in terms of the aspect ratio (2.0), fore wing camber (0.16), and gap ratio (0.35), with the aspect ratio having the greatest effect on performance. The hydrodynamic performances of the otter board with the optimized structure and another otter board model were compared in numerical simulation, which verified the correctness of the analysis results. The experimental results provide a reference for the optimal design of the double-vane otter board.

Estuaries, as important fish nursery habitats, usually include a variety of larval fishes of different ecological guilds and exhibit complicated changing environmental conditions. We carried out a survey to examine the spatiotemporal dynamics of different ecological guild larval fishes and their relationships with environmental factors in the springs and summers from 2018 to 2020 in the Yangtze Estuary (China). The aims of the study were to provide detailed information on the characteristics of the larval fish assemblage and to explore the spatiotemporal variation in different ecological guild species and the effects of environmental variables on assemblage structure. More than 140,000 fish larvae from 26 families and 99 species were gathered during the six cruises, with the spring being the most prolific. The assemblage was dominated by a few species and was divided into three ecological guilds. Engraulidae was the most abundant family, followed by Cyprinidae and Gobiidae. Hemiculter bleekeri (freshwater), Pseudolaubuca sinensis (freshwater), Coilia mystus (brackish water), and Engraulis japonicas (marine) were the predominant species. Seasonal variations in larval fish assemblage structure were closely influenced by temperature, and the fluctuation in salinity mainly determined the spatial distribution of the larval fish community. Freshwater flows also played an important role in shaping the larval fish assemblage structure and dynamics. The conclusions improve the understanding of the ecological dynamics of larval fish assemblages in environmentally heterogeneous areas and may be applicable to other estuary ecosystems.