Search Results (85)

Obtaining the echo of individual fish is an important prerequisite for fisheries acoustic applications, such as in situ measurement of fish target strength and assessment of fish abundance using the counting method. It is also the foundation for evaluating the growth status of farmed fish and managing aquaculture risks. The density of farmed fish populations is typically higher, and such high-density aquaculture further increases the difficulty of obtaining individual fish echoes in practical applications. Building upon previous research and considering the behavioral characteristics of fish in aquaculture settings, this study conducted performance simulations, live fish experiments in simulated aquaculture cages, and comparative evaluations of three individual fish broadband echo detection methods based on a broadband signal system: the amplitude pulse width method (APM) based on echo envelopes, the peak detection and time delay estimation method (PDM), and the peak time delay combined with instantaneous frequency method (PDIM). This study assumed a dorsolateral fish orientation, which limits its research scope and applicability. The results showed that the PDIM achieved a detection accuracy of 78.34% and a false recognition rate of 1.32%. The APM based on echo envelopes was insensitive to individual fish echoes and had lower recognition accuracy. The PDM exhibited better individual fish echo capture capabilities, while the PDIM demonstrated superior overlapping echo rejection capabilities. Full article

Generic and consistent formulations for measurement of the backscattering cross section $\left({\sigma }_{bs}\right)$ and the volume backscattering coefficient $\left(s_v\right)$ using broadband pulse compression and narrowband echo integration are derived, for small- and finite-amplitude sound propagation. The theory applies to backscattering operation of echosounders and sonars in general, with focus on fisheries acoustics. Formally consistent mathematical relationships for broadband and narrowband operation of such instruments are established that ensure consistency with the underlying power budget equations on average-power form, bridging a gap in prior literature. The formulations give full flexibility in choice of transmit signals and reference signals for pulse compression. Generic and general criteria for quantitative consistency between broadband and narrowband operation are derived, establishing new knowledge and analysis tools. These criteria become identical for small- and finite-amplitude sound propagation. In addition to general criteria, two special cases are considered, relevant for actual operation scenarios. The criteria serve to test and evaluate the extent to which the methods used in broadband pulse compression and narrowband echo integration operating modes are correct and consistent, and to identify and reduce experienced discrepancies between such methods. These are topics of major concern for quantitative acoustic stock assessment, underlying national and international fisheries quota regulations. Full article

This study addresses the challenges of manual measurement bias and low robustness in detecting small, occluded targets in complex marine environments during real-time onboard sorting of Portunus trituberculatus. We propose YOLO-DFAM, an enhanced YOLOv11n-based model that replaces the global average pooling in the Focal Modulation module with a spatial–channel dual-attention mechanism and incorporates the ASF-YOLO cross-scale fusion strategy to improve feature representation across varying target sizes. These enhancements significantly boost detection, achieving an mAP@50 of 98.0% and precision of 94.6%, outperforming RetinaNet-CSL and Rotated Faster R-CNN by up to 6.3% while maintaining real-time inference at 180.3 FPS with only 7.2 GFLOPs. Unlike prior static-scene approaches, our unified framework integrates attention-guided detection, scale-adaptive tracking, and lightweight weight estimation for dynamic marine conditions. A ByteTrack-based tracking module with dynamic scale calibration, EMA filtering, and optical flow compensation ensures stable multi-frame tracking. Additionally, a region-specific allometric weight estimation model (R² = 0.9856) reduces dimensional errors by 85.7% and maintains prediction errors below 4.7% using only 12 spline-interpolated calibration sets. YOLO-DFAM provides an accurate, efficient solution for intelligent onboard fishery monitoring. Full article

Accurate and rapid aquatic organism recognition is a core technology for fisheries automation and aquatic organism statistical research. However, due to absorption and scattering effects, images of aquatic organisms often suffer from poor contrast and color distortion. Additionally, the clustering behavior of aquatic organisms often leads to occlusion, further complicating the identification task. This study proposes a lightweight object detection model, Mobile-YOLO, for the recognition of four representative aquatic organisms, namely holothurian, echinus, scallop, and starfish. Our model first utilizes the Mobile-Nano backbone network we proposed, which enhances feature perception while maintaining a lightweight design. Then, we propose a lightweight detection head, LDtect, which achieves a balance between lightweight structure and high accuracy. Additionally, we introduce Dysample (dynamic sampling) and HWD (Haar wavelet downsampling) modules, aiming to optimize the feature fusion structure and achieve lightweight goals by improving the processes of upsampling and downsampling. These modules also help compensate for the accuracy loss caused by the lightweight design of LDtect. Compared to the baseline model, our model reduces Params (parameters) by 32.2%, FLOPs (floating point operations) by 28.4%, and weights (model storage size) by 30.8%, while improving FPS (frames per second) by 95.2%. The improvement in mAP (mean average precision) can also lead to better accuracy in practical applications, such as marine species monitoring, conservation efforts, and biodiversity assessment. Furthermore, the model’s accuracy is enhanced, with the mAP increased by 1.6%, demonstrating the advanced nature of our approach. Compared with YOLO (You Only Look Once) series (YOLOv5-12), SSD (Single Shot MultiBox Detector), EfficientDet (Efficient Detection), RetinaNet, and RT-DETR (Real-Time Detection Transformer), our model achieves leading comprehensive performance in terms of both accuracy and lightweight design. The results indicate that our research provides technological support for precise and rapid aquatic organism recognition. Full article

Depensation (or an Allee effect) has recently been detected in stock–recruitment relationships (SRRs) in four Atlantic herring stocks and one Atlantic cod stock using a Bayesian statistical approach. In the present study, we define the Allee effect threshold (B_AET) for these five stocks and propose B_AET as a candidate limit reference point (LRP). We compare B_AET to traditional LRPs based on proportions of equilibrium unfished biomass (B₀) and biomass at maximum sustainable yield (B_MSY) assuming a Beverton–Holt or Ricker SRR with and without depensation, and to the change point from a hockey stick SRR (B_CP). The B_AET for the case studies exceeded 0.2 B₀ and 0.4 B_MSY for three of the case study stocks and exceedances of 0.2 B₀ were more common when the Ricker form of the SRR was assumed. The B_AET estimates for all case studies were less than B_CP. When there is depensation in the SRR, multiple equilibrium states can exist when fishing at a fixed fishing mortality rate (F) because the equilibrium recruits-per-spawner line at a given F can intersect the SRR more than once. The equilibrium biomass is determined by whether there is excess recruitment at the initial projected stock biomass. Estimates of equilibrium F_MSY in the case studies were generally higher for SRRs that included the depensation parameter; however, the long-term F that would lead the stock to crash (F_crash) in the depensation SRRs was often about half the F_crash for SRRs without depensation. When warranted, this study recommends exploration of candidate LRPs from depensatory SRRs, especially if Allee effect thresholds exceed commonly used limits, and simulation testing of management strategies for robustness to depensatory effects. Full article

With the advent of the big data era in ocean remote sensing and fisheries, there is a growing demand for finer temporal scales to predict spatial distribution of the jumbo flying squid (Dosidicus gigas). This can help reduce fuel costs and provide higher quality and faster decision-making. Therefore, this study employed a deep neural network (DNN) model, using sea surface temperature, sea surface height, sea surface salinity, and photosynthetically active radiation as input factors, with catch per unit effort as the output factor. We construct five cases with temporal scales of 3, 6, 10, 15, and 30 days using data spanning 10 years (2012–2021). Additionally, the performance of DNN was compared with those of traditional methods such as generalized additive model (GAM), extreme gradient boosting (XGBoost), and artificial neural network (ANN). The results demonstrated that the DNN model had the best performance. As the temporal scale decreased, the mean squared error and the mean absolute error increased, whereas the area under the precision−recall curve decreased, indicating a decline in model performance. The interpretability analysis indicated that spatial and temporal factors significantly contributed to the model, with longitude exhibiting the highest contribution. To improve the accuracy of finer temporal scales, future research should focus on reducing noise in the data and address the presence-only nature of fishery data, particularly by cleaning the unsampled portions. Full article

Global warming has increasingly become a widespread concern of the international community, and one of the key approaches to achieving carbon neutrality goals lies in the carbon sequestration capacity of oceans. Therefore, scientifically and accurately measuring the carbon sink capacity of marine fisheries and studying its spatial effects are particularly crucial for mitigating global climate change. Marine fisheries encompass categories such as fish, shellfish, algae, and crustaceans. Given that marine fisheries-based carbon sinks are non-feed fisheries, with cultivated shellfish and algae being highly representative, this paper primarily focuses on the carbon sink capacity of shellfish and algae as the main assessment criteria for marine fisheries carbon sinks, aiming to apply this research to other countries worldwide to assist in addressing global warming. Thus, based on panel data of shellfish and algae cultivation in nine coastal provinces of China from 2007 to 2021, this paper employs the “removable carbon sink” model to calculate the carbon sink capacity of Chinese marine shellfish and algae aquaculture industry and utilizes the spatial Durbin model to analyze its spatial effects. The research findings are as follows: (1) The spatial distribution of carbon sink capacity in China’s marine shellfish and algae is uneven. (2) Moran’s Index indicates that the carbon sink capacity of marine shellfish and algae exhibits positive spatial correlation, but the degree of spatial agglomeration is unstable. Fujian Province has the highest average carbon sink capacity at 446,451.21 tons, while regions such as Hainan, Hebei, and Jiangsu have relatively lower average carbon sink capacities, with Hainan Province’s being only 3627.57 tons, sufficiently demonstrating the characteristic of uneven spatial distribution. (3) Through decomposition using the spatial Durbin model, it is found that the direct effects of marine shellfish and algae aquaculture production, technological input, technological promotion, and fishery disaster situations are positive, with the result for marine shellfish and algae aquaculture production being 1.617, significantly positive at the 1% level. The result for labor input is −0.847, with a negative direct effect. From the perspective of indirect effects, the indirect effects of marine shellfish and algae aquaculture production, technological input, and technological promotion are positive, with aquaculture production at 1.185, still significantly positive at the 1% level. The result for labor input is −2.140, with a negative indirect effect. These research conclusions provide important references for the formulation of global marine carbon sink-related policies, helping countries optimize resource allocation, strengthen regional collaboration, and increase investment in science and technology. Consequently, they can promote the sustainable development of marine shellfish and algae aquaculture industries, and contribute to enhancing marine carbon sink capacity and achieving global carbon neutrality goals. Full article

Due to its good adaptability, the pneumatic conveying feeder has been widely developed and applied in recirculating aquaculture systems (RASs). Its important performances include the integrity of feed pellets and the feeding accuracy. The aim of this study was to design and evaluate a feed distribution device for a small-scale pneumatic conveying feeder. A cylindrical hopper with a feed capacity of 4 kg and a feed distribution device were designed based on theoretical calculations. The motion and force of feed pellets during the distribution process were studied using the discrete element method (DEM) simulation to evaluate the integrity of feed pellets. Additionally, to evaluate feeding accuracy, the effect of discharge disk rotational speed on single feeding quantity was studied using DEM simulations and experimental validations, as well as the effect of the proportion of feed pellets in the hopper. Results showed that the maximum force on feed pellets was 1.25 N during the distribution process. It was inferred that the feed pellets can be distributed without breaking based on their shear strength. When the rotational speed of the discharge disk was set at a maximum of 28 rpm, the relative error of single feeding quantity between simulation and actual experiments was 4.43%, and the single feeding mass was 62.74 g, suggesting an optimal speed. In addition, the average single feeding quantity ranged from 262 to 301 feed pellets at the different proportions of feed pellets in the hopper, and its coefficient of variation was 12.46%, which generally meets the distribution requirements of the small-scale feeder. This study provides a feed distribution device for a small-scale pneumatic conveying feeder and offers references for the relevant analysis of DEM simulation. Full article

This study aims to clarify the influence of water flow on the behavior of the large yellow croaker (Larimichthys crocea). Although L. crocea is a key species in marine cage aquaculture, and the industry is increasingly adopting large-scale sea cages, the behavioral adaptations of this species under such conditions remain insufficiently characterized. To solve this problem, the study implemented an ultrasonic biotelemetry system to monitor the in situ swimming behavior of L. crocea across varying current velocities and tidal phases. The results indicated that the tagged fish predominantly occupied water depths of 1 to 2.6 m, with no observable circular swimming behavior along the cage periphery. Additionally, the spatial distribution of L. crocea within the large-scale cage seemed to correlate with the direction of the current. Furthermore, both the frequency of appearance and swimming speed of L. crocea were higher in the center of the cage compared to the peripheral regions during flood and ebb tides, whereas the opposite trend was observed during slack water. This study provides novel insights into the behavioral ecology of L. crocea in large-scale aquaculture systems. Full article

The extraction of aquaculture areas from high-resolution remote sensing images is crucial for effective coastal management and resource preservation. This study introduces SwinNet, a semantic segmentation model leveraging multi-scale feature fusion to enhance the extraction of aquaculture areas, particularly in the Maowei Sea of the Beibu Gulf, China. Utilizing the Swin Transformer backbone and a novel Parallel Pooling Attention Module (PPAM), SwinNet minimizes background noise and improves segmentation accuracy. SwinNet achieved a pixel accuracy of 96.53% and an intersection over the union of 93.07% on an aquaculture dataset, demonstrating superior performance in overcoming noise and accurately extracting aquaculture areas. SwinNet offers an effective solution for large-scale, high-precision monitoring of coastal aquaculture, with potential broader applicability in aquatic resource conservation and management. Full article

Hard-shell clams are highly valued for their nutritional and economic benefits, leading to an increase in their aquaculture scale. Harvesting these clams manually leads to low efficiency and high labor intensity; thus, a new type of hard-shell clam harvester has been designed to overcome this challenge. Based on biological characteristics and sediment properties of hard-shell clams, a 3D model of the harvester has been created utilizing SolidWorks software (version 2022), which has a working length of 980 mm, an excavation depth range from 0~12 mm, and an angle of entry of 22 degrees. To optimize the efficiency of the machine, a Discrete Element Method (DEM) simulation trial was conducted through a three-factor three-level experiment using EDEM software. Results indicated an optimal harvest efficiency of 91.17% with the machine achieving a running speed of 0.526 m/s, roller speed of 4.772 r/min, and excavation depth of 73.067 mm. Field experiments verified the feasibility of the harvester, demonstrating high accuracy when compared to simulation results. Full article

In order to address the challenges of a low detection accuracy, missed detections, and false detections in marine precious biological target detection within complex marine environments, this paper presents a novel residual attention module called R-AM. This module is integrated into the backbone network of the YOLOv10 model to improve the model’s focus on the detailed features of biological targets during feature extraction. Additionally, the introduction of a bidirectional feature pyramid with adaptive feature fusion in the neck network enhances the integration of semantic information from deep layers, and localization cues from shallow layers improve the model’s ability to distinguish targets from their environments. The experimental data showed that the improved YOLOv10 model achieved 92.89% at mAP@0.5, increasing by 1.31% compared to the original YOLOv10 model. Additionally, the mAP@0.5:0.95 was 77.13%, indicating a 3.71% improvement over the original YOLOv10 model. When compared to the Faster R-CNN, SSD, RetinaNet, YOLOv6, and YOLOv7 models, the enhanced model exhibited increases of 1.5%, 1.7%, 4.06%, 4.7%, and 1.42% in mAP@0.5, respectively. This demonstrates a high detection accuracy and robust stability in complex seabed environments, providing valuable technical support for the scientific management of marine resources in underwater ranches. Full article

We sought to develop and evaluate an escape vent designed for undersized swimming crabs (Portunus trituberculatus) to reduce bycatch, contributing to the preservation of marine resources. To this end, we conducted aquarium experiments and selectivity analysis to determine the appropriate size of the escape vent that would allow only undersized crabs with a carapace length of 64 mm or less to escape. The optimal dimensions for the escape vent were approximately 34.1 mm in height and 69.1 mm in width. During the sea trial, the average bycatch rates for undersized crabs per pot were 57.2%, 15.0%, and 22.3% for the control, basic, and door types, respectively. Regarding legal-sized crab catch per pot, averages of 1.40, 1.72, and 1.62 individuals were obtained for the three pot types. To our knowledge, this study is the first to assess the optimal size for an escape vent capable of reducing the bycatch of undersized crabs while maintaining legal-sized swimming crabs capture. Full article

The visual underwater monitoring of fish size, position, and swimming speed is experiencing increasing interest in aquaculture and marine research. Despite the long-standing use of video monitoring, there is no methodological consensus, but numerous researchers and developers advocate for 3D video capture techniques to facilitate biometric estimations. Most of the previous systems, however, use partially synchronized cameras (within one frame), which causes an inherent error if observing moving fish in relation to the camera. This study proposes the use of a completely synchronized 3D camera system for underwater video capture, which can be calibrated, and which allows analyses to be performed using open-source software(s). We present data on the maximum theoretical error in the size estimation of swimming fish. This article presents a guide on how to build and set up the camera hardware and run the system, including a formal study investigating pre-measured lengths, and an informal study investigating the lengths of Atlantic cod (Gadus morhua). Full article

Wild oyster reefs have been harvested for centuries and continue to face anthropogenic pressures, including climate change, pollution, and habitat reduction. Oyster aquaculture has grown to supplement depleted wild stocks and strengthen local economies, but development has not occurred at the same rate across all regions. Across the United States, states have a variety of political and cultural influences that impact oyster aquaculture policy, constraining the ability to make direct comparisons among locations that could enhance aquaculture expansion in slower-to-develop states and regions. This research developed a four-part index to compare regulatory, production, and economic attributes of oyster aquaculture among 23 coastal states. The final index score—a summation of the four individual index components—provides a broad integrated view of oyster aquaculture across the U.S. The results indicate that coastal states in the U.S. Mid-Atlantic and New England regions have the greatest number of resource and policy attributes in place to support oyster aquaculture, whereas coastal states in the Gulf of Mexico and Western Pacific region have relatively less in the way of aquaculture-supporting structures. As the oyster aquaculture industry continues to grow in the U.S., results from this study can help organizations involved in oyster aquaculture to make informed decisions to expand permitting, leasing, and production systems, following the model from states who have been active in oyster aquaculture for decades. Mindful and cautious improvements can facilitate sustainable sources of seafood and stable income generation for coastal communities while reducing pressures on wild stocks. Full article