Search Results (163)

Overfishing represents one of the most alarming threats to marine conservation in the Mediterranean Sea. In particular, deep-sea trawl fishing can severely damage marine habitats that may take decades to recover due to their slow growth rates. Hence, monitoring the health and subsistence of deep-sea ecosystems in fishing hotspots is vital to understand the impacts of deep-sea fishing. This paper presents a methodological study to prepare an expedition in Sardinian (Italy) deep waters. The methodology is composed of three sections: first, it offers a comparative analysis of the proper technological mix to identify fishing hotspots pre-expedition; second, it simulates an in situ expedition to monitor the state of deep-sea ecosystems in proximity of the fishing hotspots identified; and third, it offers recommendations for data analysis and management post-expedition. This study offers a replicable methodology for advancing knowledge on the state of deep-sea ecosystems affected by trawl fishing. Full article

Plastic debris is a pervasive and persistent threat to marine ecosystems. Microplastics (plastics < 5 mm) are increasing in a variety of marine habitats, including open water systems, shorelines, and benthic sediments. It remains unclear how microplastics distribute and accumulate in marine systems and the extent to which this pollutant is accessible to marine taxa. We examined subtidal benthic sediments and beach sediments in critical nearshore habitats for forage fish species—Pacific sand lance (Ammodytes personatus), Pacific herring (Clupea pallasi), and surf smelt (Hypomesus pretiosus)—to quantify microplastic concentrations in the spawning and deep-water habitats of these fish and better understand how microplastics accumulate and distribute in nearshore systems. In the San Juan Islands, we examined an offshore subtidal bedform in a high-flow channel and beach sites of protected and exposed shorelines. We also examined 12 beach sites proximate to urban areas in Puget Sound. Microplastics were found in all samples and at all sample sites. Microfibers were the most abundant, and flakes were present proximate to major shipyards and marinas. Microplastics were significantly elevated in Puget Sound compared to the San Juan Archipelago. Protected beaches had elevated concentrations relative to exposed beaches and subtidal sediments. Microplastics were in higher concentrations in sand and fine-grain sediments, poorly sorted sediments, and artificial sediments. Microplastics were also elevated at sites confirmed as spawning habitats for forage fish. The model results indicate that both current speed and proximate urban populations influence nearshore microplastic concentrations. Our research provides new insights into how microplastics are distributed, deposited, and retained in marine sediments and shorelines, as well as insight into potential exposure in benthic, demersal, and shoreline habitats. Further analyses are required to examine the relative influence of urban populations and shipping lanes and the effects of physical processes such as wave exposure, tidal currents, and shoreline geometry. Full article

Members of the genus Nemipterus are economically important fish species distributed in the tropical and subtropical Indo-West Pacific region. The majority of species in this genus inhabit waters with sandy–muddy substrates on the continental shelf, although different species are found at slightly varying water depths. In this study, we sequenced seven species within the genus Nemipterus after identifying the specimens using complementary morphological analysis and DNA barcoding. Each species yielded over 40,000,000 clean reads, totaling over 300,000,000 clean reads across the seven species. A total of 276,389 unigenes were obtained after de novo assembly and a total of 168,010 (60.79%) unigenes were annotated in the protein database. The comprehensive functional annotation based on the KOG, GO, and KEGG databases revealed that these unigenes are mainly associated with numerous physiological, metabolic, and molecular processes, and that the seven species exhibit similarity in these aspects. By constructing a phylogenetic tree and conducting divergence time analysis, we found that N. bathybius and N. virgatus diverged most recently, approximately during the Neogene Period (14.9 Mya). Compared with other species, N. bathybius and N. virgatus are distributed in deeper water layers. Therefore, we conducted selection pressure analysis using these two species as the foreground branches and identified several environmental-responsive genes. The results indicate that genes such as aqp1, arrdc3, ISP2, Hip, ndufa1, ndufa3, pcyt1a, ctsk, col6a2, casp2 exhibit faster evolutionary rates during long-term adaptation to deep-water environments. Specifically, these genes are considered to be associated with adaptation to aquatic osmoregulation, temperature fluctuations, and skeletal development. This comprehensive analysis provides valuable insights into the evolutionary biology and environmental adaptability of threadfin breams, contributing to the conservation and sustainable management of these species. Full article

Elasmobranch species are considered a global conservation priority due to their susceptibility to fishing pressure. In the Madeira Archipelago, Northeastern Atlantic, most elasmobranch species are caught as bycatch in artisanal drifting longline fishery targeting scabbardfishes. All commercial elasmobranch landings carried out in this archipelago over three decades (1990–2020) were analysed, aiming to provide a reliable overview of Madeira’s elasmobranch fisheries and their evolution. A total of 2316 tonnes of elasmobranchs were landed during the study period, corresponding to approximately EUR 2.1 million in first-sale value. The most representative period occurred from 2003 to 2013, corresponding to 75.21% of the total elasmobranch landings. A general pattern of supply and demand was evident, with mean price values typically showing an inverse trend to landed tonnage. At the species level, Centrophorus squamosus appears as the dominant species, representing about 89% of the total elasmobranch species landed, followed by Prionace glauca, with approximately 3%. The high dominance of C. squamosus in the scabbardfish fishery raises significant ecological and management concerns, as this deep-water shark species is known for its vulnerability to overexploitation. Management measures currently in place need to be updated and ought to be based on studies on the type and size of hooks for each fishery, to ultimately infer about species-specific survival rates, as well as the fishing gears’ soak time. Moreover, studies on the enhancement of food supply through fisheries discards are still missing, even though it is highly likely that this input may alter the dynamics of marine food webs. Full article

Investigating biodiversity in remote and harsh environments, particularly in the Southern Ocean, remains costly and challenging through traditional sampling methods such as trawling. Environmental DNA (eDNA) sampling, which refers to sampling genetic material shed by organisms from environmental samples (e.g., water), provides a more cost-effective and sustainable alternative to traditional sampling approaches. To study the biogeographic patterns of two typical mesopelagic fishes, Antarctic lanternfish (Electrona antarctica) and Antarctic deep-sea smelt (Bathylagus antarcticus), in the Cosmonaut Sea in the Indian Ocean sector of the Southern Ocean, we conducted both eDNA and trawling sampling at a total of 86 stations in the Cosmonaut Sea during two cruises in 2021–2022. Two sets of species-specific primers and probes were developed for a quantitative eDNA analysis of two fish species. Both the eDNA and trawl results indicated that the two fish species are widely distributed in the Cosmonaut Sea, with no significant difference in eDNA concentration, biomass, or abundance between stations. Spatially, E. antarctica tended to be distributed in shallow waters, while B. antarcticus tended to be distributed in deep waters. Vertically, E. antarctica was more abundant above 500 m, while B. antarcticus had a wider range of habitat depths. The distribution patterns of both species were affected by nutrients, with E. antarctica additionally affected by chlorophyll, indicating that their distribution is primarily influenced by food resources. Our study provides broader insight into the biogeographic patterns of the two mesopelagic fishes in the remote Cosmonaut Sea, demonstrates the potential of combining eDNA with traditional methods to study biodiversity and ecosystem dynamics in the Southern Ocean and even at high latitudes, and contributes to future ecosystem research and biodiversity conservation in the region. Full article

Deaths occur during the culture of sea bass, and if timely harvesting is not carried out, it will lead to water pollution and the continued spread of sea bass deaths. Therefore, it is necessary to promptly detect dead fish and take countermeasures. Existing object detection algorithms, when applied to the task of detecting dead sea bass, often suffer from excessive model complexity, high computational cost, and reduced accuracy in the presence of occlusion. To overcome these limitations, this study introduces YOLOv8n-Deadfish, a lightweight and high-precision detection model. First, the homemade sea bass death recognition dataset was expanded to enhance the generalization ability of the neural network. Second, the C2f-faster–EMA (efficient multi-scale attention) convolutional module was designed to replace the C2f module in the backbone network of YOLOv8n, reducing redundant calculations and memory access, thereby more effectively extracting spatial features. Then, a weighted bidirectional feature pyramid network (BiFPN) was introduced to achieve a more thorough integration of deep and shallow features. Finally, in order to compensate for the weak generalization and slow convergence of the CIoU loss function in detection tasks, the Inner-CIoU loss function was used to accelerate bounding box regression and further improve the detection performance of the model. The experimental results show that the YOLOv8n-Deadfish model has an accuracy, recall, and mean precision of 90.0%, 90.4%, and 93.6%, respectively, which is an improvement of 2.0, 1.4, and 1.3 percentage points, respectively, over the original base network YOLOv8n. The number of model parameters and GFLOPs were reduced by 23.3% and 18.5%, respectively, and the detection speed was improved from the original 304.5 FPS to 424.6 FPS. This method can provide a technical basis for the identification of dead sea bass in the process of intelligent aquaculture. Full article

Trachinotus ovatus is a euryhaline, warm-water pelagic fish species with strong adaptability, rapid growth, and a high survival rate, making it one of the most important marine aquaculture species in China. In recent years, extensive experience has been accumulated in the cage farming of T. ovatus, but whether it can adapt to deep-sea environments and grow normally remains a current research focus. This study used RNA-Seq sequencing technology to analyze the gene expression changes in the liver of T. ovatus under three conditions: rest (0 cm/s), medium flow velocity (54 cm/s), and high flow velocity (90 cm/s). Through differential expression analysis, Short Time-series Expression Miner (STEM) analysis and protein–protein interaction (PPI) network analysis, a total of 5107 differentially expressed genes (DEGs), three significantly expressed gene profiles (profile6, profile1, and profile5), and 15 hub genes were identified. The results showed that changes in flow speed significantly impacted key biological processes such as energy metabolism, protein homeostasis, and endoplasmic reticulum (ER) stress response. Under moderate and high flow conditions, glycolysis-related genes were upregulated to meet the energy demands of swimming, while the downregulation of the PPARγ-RXRG complex and its downstream genes in the lipid metabolism pathway suggested a limitation in its fatty acid β-oxidation capacity. At the same time, protein synthesis was enhanced, and the unfolded protein response (UPR) was activated to help cope with ER stress. Furthermore, when the flow speed reached 90 cm/s, the expression of UPR- related genes and the anti-apoptotic factor JNK significantly decreased, suggesting that the stress response was nearing its limit and could potentially trigger cell apoptosis. These findings provide new insights into the molecular adaptation mechanisms of T. ovatus to flow speed stress and offer theoretical support for its rational farming in deep-sea cages, suggesting that the water flow speed in farming should not exceed 90 cm/s. Full article

Understanding the coupled evolution mechanisms of stress, fracture, and seepage fields in overburden strata is critical for preventing water inrush disasters during fully mechanized mining in deep coal seams, particularly under complex hydrogeological conditions. To address this challenge, this study integrates laboratory experiments with FLAC3D numerical simulations to systematically investigate the multi-field coupling behavior in the Luotuoshan coal mine. Three types of coal rock samples—raw coal/rock (bending subsidence zone), fractured coal/rock (fracture zone), and broken rock (caved zone)—were subjected to triaxial permeability tests under varying stress conditions. The experimental results quantitatively revealed distinct permeability evolution patterns: the fractured samples exhibited a 23–48 × higher initial permeability (28.03 mD for coal, 13.54 mD for rock) than the intact samples (0.50 mD for coal, 0.21 mD for rock), while the broken rock showed exponential permeability decay (120.32 mD to 23.72 mD) under compaction. A dynamic permeability updating algorithm was developed using FISH scripting language, embedding stress-dependent permeability models (R² > 0.99) into FLAC3D to enable real-time coupling of stress–fracture–seepage fields during face advancement simulations. The key findings demonstrate four distinct evolutionary stages of pore water pressure: (1) static equilibrium (0–100 m advance), (2) fracture expansion (120–200 m, 484% permeability surge), (3) seepage channel formation (200–300 m, 81.67 mD peak permeability), and (4) high-risk water inrush (300–400 m, 23.72 mD stabilized permeability). The simulated fracture zone height reached 55 m, directly connecting with the overlying sandstone aquifer (9 m thick, 1 MPa pressure), validating field-observed water inrush thresholds. This methodology provides a quantitative framework for predicting water-conducting fracture zone development and optimizing real-time water hazard prevention strategies in similar deep mining conditions. Full article

With the rising global demand for aquatic products, aquaculture has become a cornerstone of food security and sustainability. This review comprehensively analyzes the application of deep learning in sustainable aquaculture, covering key areas such as fish detection and counting, growth prediction and health monitoring, intelligent feeding systems, water quality forecasting, and behavioral and stress analysis. The study discusses the suitability of deep learning architectures, including CNNs, RNNs, GANs, Transformers, and MobileNet, under complex aquatic environments characterized by poor image quality and severe occlusion. It highlights ongoing challenges related to data scarcity, real-time performance, model generalization, and cross-domain adaptability. Looking forward, the paper outlines future research directions including multimodal data fusion, edge computing, lightweight model design, synthetic data generation, and digital twin-based virtual farming platforms. Deep learning is poised to drive aquaculture toward greater intelligence, efficiency, and sustainability. Full article

Illegal, unreported, and unregulated (IUU) fishing significantly threatens marine ecosystems, disrupts the ecological balance of the oceans, and poses serious challenges to global fisheries management. This contribution presents the efficacy of China’s summer fishing moratorium using BeiDou vessel monitoring system (VMS) data from 2805 fishing vessels in the East China Sea and Yellow Sea, integrated with a deep learning framework for spatiotemporal analysis. A preprocessing protocol addressing multidimensional noise in raw VMS datasets was developed, incorporating velocity normalization and gap filling to ensure data reliability. The CNN-BiLSTM hybrid model emerged as optimal for fishing behavior classification, achieving 89.98% accuracy and an 87.72% F1 score through synergistic spatiotemporal feature extraction. Spatial analysis revealed significant policy-driven reductions in fishing intensity during the moratorium (May–August), with hotspot areas suppressed to sporadic coastal distributions. However, concentrated vessel activity in Zhejiang’s nearshore waters suggested potential illegal fishing. Post-moratorium, fishing hotspots expanded explosively, peaking in October and clustering in Yushan, Zhoushan, and Yangtze River estuary fishing grounds. Quarterly patterns identified autumn–winter 2021 as peak fishing seasons, with hotspots covering >80% of East China Sea grounds. The framework enables real-time fishing state detection and adaptive spatial management via dynamic closure policies. The findings underscore the need for strengthened surveillance during moratoriums and post-ban catch regulation to mitigate overfishing risks. Full article

Flow velocity is a critical factor in determining the suitability of fish habitats. Understanding the preference patterns of the four major Chinese carps (FMCCs) for different flow velocities is crucial for their habitat conservation and restoration. In this study, the preference of individual fish species, approximately 15 cm in length, for flow velocity was investigated at flow velocity gradients of 0.0, 0.4, 0.8, 1.2, 1.6, and 2.0 times their body length. Additionally, a deep learning algorithm based on convolutional neural networks (CNNs) was employed for fish target detection. The results showed that, at this length, black carp (Mylopharyngodon piceus) preferred fast currents when the inlet flow velocity was between 0.4 and 1.6 times their body length, while grass carp (Ctenopharyngodon idella), silver carp (Hypophthalmichthys molitrix), and bighead carp (Hypophthalmichthys nobilis) preferred fast currents when the inlet flow velocity of the test flume was between 0.4 and 2.0 times their body length. However, this preference for fast currents decreased as the overall flow velocity increased to a specific threshold, eventually leading to their avoidance. The highest preference for fast currents among the four species was observed at inlet flow velocities of 1.2, 0.4, 0.8, and 0.8 times their body length, respectively. The findings of this study provide important insights into habitat conservation and restoration for the FMCCs in projects focused on the construction of navigation channels and water conservancy. Full article

Understanding spatiotemporal patterns of fish density and their environmental drivers is critical for managing river–lake ecosystems, yet dynamic interactions in heterogeneous habitats remain poorly quantified. This study combined hydroacoustic surveys, spatial autocorrelation analysis (Moran’s I), and generalized additive models (GAMs) to investigate seasonal and spatial fish distribution, aggregation characteristics, and regulatory mechanisms in China’s Zhelin Reservoir. The results reveal pronounced seasonal fluctuations, with summer fish density peaking at 13.70 ± 0.91 ind./1000 m³ and declining to 1.95 ± 0.13 ind./1000 m³ in winter. Spatial heterogeneity was evident, with the Xiuhe region sustaining the highest density (15.69 ± 1.09 ind./1000 m³) and persistent hotspots in upstream bays. Transient high-density clusters (90–99% confidence) near the Zhelin Dam during summer suggested thermal or hydrodynamic disturbances. GAM analysis (R²adj = 0.712, 78.5% deviance explained) identified seasonal transitions (12.26% variance), water depth (16.54%), conductivity (13.75%), and dissolved oxygen (13.29%) as dominant drivers, with nonlinear responses to depth and bimodal patterns for conductivity/oxygen. These findings demonstrate that hydrological seasonality and habitat heterogeneity jointly govern fish aggregation, underscoring the ecological priority of Xiuhe and upstream bays as core habitats. This study provides a mechanistic framework for guiding reservoir management, including targeted conservation, dam operation adjustments to mitigate hydrodynamic impacts, and integrated strategies for balancing hydrological and ecological needs in similar ecosystems. Full article

Otoliths are common in the fossil record and can provide important insight into the evolution and spatial and stratigraphic distribution of fishes, but have remained understudied in many areas of the world. Here, we describe the first marine otolith assemblage from East Africa. The material is from Tanzania Drilling Project cores of late Eocene to early Oligocene age, spanning the Eocene-Oligocene transition (EOT). The assemblage consists of 10 identifiable species of which 5 are new, and 4 remain in open nomenclature. The new species are as follows: Protanago africanus, Bregmaceros tanzaniensis, Ortugobius pandeanus, “Serranus” plasmaticus, and Acanthocepola signanoae. The association of shallow and deep-water taxa along with the dominance of the family Cepolidae, which has not been observed in either the extant or fossil record, makes the faunal composition unusual. However, when taxon occurrences are correlated with stable isotope records from the same cores and compared with previous studies, it is clear the otoliths reflect the sea-level fall known to occur during the EOT, with deeper dwelling taxa in the late Eocene and taxa preferring shallower, which are more shelf-like environments in the early Oligocene. Full article

In this study, samples were collected from different types of artificial fish reefs and prevention and control areas in the sea areas of the northern part of Da Changshan Island and the northeastern part of Xiao Changshan Island in the North Yellow Sea. The purpose is to compare the differences in the bacterial communities among different regions, determine the impacts of environmental factors on the bacterial communities, and evaluate the ecological effects of artificial fish reefs on the marine bacterial communities. We obtained a total of 2,128,186 effective sequences and 4321 bacterial operational taxonomic units (OTUs), which were classified into 14 phyla and 76 genera. Proteobacteria were the most abundant phylum across the 32 samples, followed by Bacteroidetes. We found that all samples from the deep-sea control area exhibited the highest bacterial richness. In addition, all samples from the shallow-water concrete reef exhibited high community richness. The distribution of bacterial communities showed differences among different regions. In two specific sea areas, the bacteria in the sediment samples exhibited particularly remarkable characteristics of high diversity. Importantly, environmental factors significantly influence bacterial communities. In seawater samples, salinity (Sal) and dissolved oxygen (DO) were the primary factors affecting bacterial communities. Furthermore, grain size (GS) emerged as the most critical physicochemical factor influencing bacterial communities in sediment. This study compared the characteristics of bacterial communities in different types of artificial reefs and control areas in two marine ranches and revealed the main environmental factors affecting the bacterial communities. This is of great significance for protecting biodiversity and evaluating the ecological effects of artificial reef placement. Full article

Marine life exploration is constrained by factors such as limited scuba diving time, depth restrictions for divers, costly expeditions, safety risks to divers’ health, and minimizing harm to marine ecosystems, where traditional diving often risks disturbing marine life. This paper introduces Nu (named after an ancient Egyptian deity), a 3D-printed Remotely Operated Underwater Vehicle (ROUV) designed in an attempt to address these challenges. Nu employs Long Range (LoRa), a low-power and long-range communication technology, enabling wireless operation via a manual controller. The vehicle features an onboard live-feed camera with a separate communication system that transmits video to an external real-time machine learning (ML) pipeline for fish species classification, reducing human error by taxonomists. It uses Brushless Direct Current (BLDC) motors for long-distance movement and water pump motors for precise navigation, minimizing disturbance, and reducing damage to surrounding species. Nu’s functionality was evaluated in a controlled 2.5-m-deep body of water, focusing on connectivity, maneuverability, and fish identification accuracy. The fish detection algorithm achieved an average precision of 60% in identifying fish presence, while the classification model achieved 97% precision in assigning species labels, with unknown species flagged correctly. The testing of Nu in a controlled environment has met the system design expectations. Full article