Search Results (237)

Skipjack tuna constitutes a crucial fishery resource in the Western and Central Pacific Ocean (WCPO) purse seine fishery, with high economic value and exploitation potential. It also serves as an essential subject for studying the interaction between fishery resource dynamics and marine ecosystems, as its resource abundance is significantly influenced by marine environmental factors. Skipjack tuna can be categorized into unassociated schools and associated schools, with the latter being predominant. Overfishing of the associated schools can adversely affect population health and the ecological environment. In-depth exploration of the spatial distribution responses of these two fish schools to environmental variables is significant for the rational development and utilization of tuna resources and for enhancing the sustainability of fishery resources. In sparsely sampled and complex marine environments, geographic similarity methods effectively predict tuna resources by quantifying local fishing ground environmental similarities. This study introduces geographical similarity theory. This study focused on 1° × 1° fishery data (2004–2021) released by the Western and Central Pacific Fisheries Commission (WCPFC) combined with relevant marine environmental data. We employed Geographical Convergent Cross Mapping (GCCM) to explore significant environmental factors influencing catch and variations in causal intensity and employed a Geographically Optimal Similarity (GOS) model to predict the spatial distribution of catch for the two types of tuna schools. The research findings indicate that the following: (1) Sea surface temperature (SST), sea surface salinity (SSS), and net primary productivity (NPP) are key factors in GCCM model analysis, significantly influencing the catch of two fish schools. (2) The GOS model exhibits higher prediction accuracy and stability compared to the Generalized Additive Model (GAM) and the Basic Configuration Similarity (BCS) model. R² values reaching 0.656 and 0.649 for the two types of schools, respectively, suggest that the geographical similarity method has certain applicability and application potential in the spatial prediction of fishery resources. (3) Uncertainty analysis revealed more stable predictions for unassociated schools, with 72.65% of the results falling within the low-uncertainty range (0.00–0.25), compared to 52.65% for associated schools. This study, based on geographical similarity theory, elucidates differential spatial responses of distinct schools to environmental factors and provides a novel approach for fishing ground prediction. It also provides a scientific basis for the dynamic assessment and rational exploitation and utilization of skipjack tuna resources in the Pacific Ocean. Full article

In recent decades, there has been a marked surge in the development of marine-by-product-derived ingredients for cosmetic applications, driven by the increasing demand for natural, sustainable, and high-performance formulations. Marine animal by-products, particularly those from fish, crustaceans, and mollusks, represent an abundant yet underutilized source of bioactive compounds with notable potential in cosmeceutical innovation. Generated as waste from the fishery and seafood-processing industries, these materials are rich in valuable bioactives, such as chitosan, collagen, peptides, amino acids, fatty acids, polar lipids, lipid-soluble vitamins, carotenoids, pigments, phenolics, and mineral-based substrates like hydroxyapatite. Marine by-product bioactives can be isolated via several extraction methods, and most importantly, green ones. These compounds exhibit a broad spectrum of skin-health-promoting effects, including antioxidant, anti-aging, anti-inflammatory, antitumor, anti-wrinkle, anti-hyperpigmentation, and wound-healing properties. Moreover, applications extend beyond skincare to include hair, nail, and oral care. The present review provides a comprehensive analysis of bioactives obtained from marine mollusks, crustaceans, and fish by-products, emphasizing modern extraction technologies with a focus on green and sustainable approaches. It further explores their mechanisms of action and documented efficacy in cosmetic formulations. Finally, the review outlines current limitations and offers future perspectives for the industrial valorization of marine by-products in functional and environmentally-conscious cosmetic development. Full article

In response to the ongoing depletion of fishery resources, many countries now prioritize sustainable fish stock use and ecosystem protection, balancing ecological, economic, and social goals. Fishery subsidies are key in this shift, with their impact depending on design and implementation. In 2020, China introduced marine fishery resource conservation subsidies and simultaneously phased out a 15-year policy of harmful fuel subsidies. This study uses evolutionary game theory to analyze the strategic interactions between government authorities and fishermen across four institutional scenarios, each combining different forms of subsidies and penalties. The findings suggest that a dynamic approach, incorporating both subsidies and penalties, is most effective in promoting legal fishing practices and protecting marine resources. Additionally, the study emphasizes that the effectiveness of subsidies and penalties does not necessarily increase with their scale; instead, both must be carefully calibrated to sustainable and reasonable limits. Full article

Various activities, whether economic, social, or environmental, exert pressure on a coastal area. The extent of economic activities taking place in coastal regions is continuously increasing, particularly in tourism, maritime transport, port operations, and fisheries and aquaculture. Therefore, the decision to establish activities in a coastal area is complex and requires careful consideration by all stakeholders who use this space, which is potentially one of the most important natural resources for the development of any coastal country. This research is focused on assessing the justification for establishing economic activities in a coastal area, taking into account the interconnection of spatial, safety, environmental, and social factors. Therefore, three possible scenarios have been proposed: the location of the communal port, the location of the nautical port-marina, and the location of the marine entertainment and recreation centre. The goal was to develop a model that would enable the objective assessment and selection of the most suitable activity that would simultaneously benefit society and have the least harmful impact on the environment. Therefore, a multi-criteria analysis was conducted using the AHP (Analytic Hierarchy Process) method. The decision-making process was based on the expert validation of criteria, sub-criteria, and alternatives. An analytical tool called Expert Choice was used to synthesise the results and select the optimal activity. The sensitivity analysis confirmed the stability and reliability of the obtained results, with the AHP method proving to be an effective tool in structuring the decision-making process regarding the establishment of activities in the coastal area. Based on the results of the multi-criteria assessment, planning the establishment of activities is an important precondition for the long-term and sustainable development of coastal activities in an area. Full article

Dietary marine lipids enriched in ω-3 polyunsaturated fatty acids (PUFAs) are spotlighted for favorable effects in neurodegenerative conditions and tumor cell proliferation. Commercial marine oils, with high EPA and DHA content, consist of non-polar lipids constituted by triacylglycerols or polar oils composed of phospholipids. Both classes have shown different activities to significantly inhibit proliferation and migration, and induce apoptosis in cancer cells. This work was aimed at testing marine oils’ associated effects on neuroblastoma (NB) and glioblastoma (GB). Commercial non-polar and polar marine oils were studied in 3D spheroid models developed with human neuroblastoma, GB, and non-nervous embryonic kidney cell lines. This study also included results provided by a new sustainable polar marine oils source: fishery side-streams. Cell viability and mitochondrial activity assessments demonstrated that both marine oils dramatically reduced NB cells’ metabolism, proliferation, and viability. Effects on GB and epithelial cells were different, including a metabolic increase. Marine oils also induce cell differentiation and selectively modulate the activity of neurons and glia, depending on the oils’ chemical form. Sustainable polar oil showed bioactive characteristics similar to commercial krill oil. We propose that marine oils rich in triacylglycerols and phospholipids with high EPA and DHA levels may be a useful tool in NB antiproliferative therapies. Full article

Overexploitation is the main anthropogenic threat to groupers (Epinephelidae) that aggregate to spawn. Fishing negatively affects their reproductive success and indirectly harms fishery economic yield. In the southern Gulf of Mexico, grouper catches, which include thirteen species, are in decline. A lack of biological information on each exploited species prevents optimising fishery management. Using histological examination of the gonads, the reproductive traits of red hind Epinephelus guttatus and yellowfin grouper Mycteroperca venenosa were studied from January 2008 to October 2009. Collections were made at two reef systems (Alacranes Reef and Bajos del Norte) on the continental shelf of the Yucatan Peninsula, Mexico, where these species form transient spawning aggregations. The results confirmed that previously identified spawning aggregation sites at both reefs constitute productive seasonal and perennial “hotspots” for both groupers; they spawn annually between January and April. Females of these protogynous hermaphroditic species exhibit a reproductive strategy characterised by asynchronous ovarian development organisation and ovulation. Sex ratios and maximum sizes at each reef suggest that populations of both groupers had a good conservation status as of the late 2000s. Both reefs are now marine protected areas, and a discussion is made of the consequent possible benefits to grouper population conservation and sustainability in the southern Gulf of Mexico. Full article

Marine heatwaves (MHWs) have recently become more frequent, intense, and prolonged, posing significant threats to marine life and fisheries. In this study, transcriptomic analysis was employed to investigate the genes and pathways in Seriola dumerili that respond to MHW-induced stress at 28 °C (T28) and 32 °C (T32), using 24 °C (T24) as the control. Transcriptome sequencing revealed that 17 differentially expressed genes (DEGs) belonging to the heat shock protein (HSP) families—HSP30, HSP40, HSP70, and HSP90—were significantly upregulated under short-lasting MHW stress in the T24-4d vs. T32-4d comparison. Additionally, genes related to oxidative stress (e.g., protein disulfide isomerase family A member 6 [pdia6]), immune responses (e.g., interferon regulatory factor 5 [irf5]), and energy metabolism (e.g., hexokinase-1 [hk1]) were also identified. Enrichment analysis of DEGs in the T24-4d vs. T32-4d group revealed that S. dumerili exhibited adaptive responses to MHWs through the upregulation of HSPs and the activation of antioxidant, energy metabolism, and immune response pathways. However, in the T24-13d vs. T32-13d group, DEGs associated with these pathways were either not significantly expressed or were downregulated. These findings indicate that S. dumerili is unable to sustain its adaptive responses under repeated, intense MHW exposure, resulting in the disorder of its antioxidant defense system, immune suppression, and metabolic dysfunction. This study provides valuable insights into the molecular responses of S. dumerili to MHWs and supports the selection for thermal resistance in this species. Full article

Marine ranching, an emerging paradigm in sustainable fisheries, integrates technological, social, and ecological dimensions through a social–technical–ecological systems (STESs) framework to enhance ecosystem resilience and resource governance. This study proposes a comprehensive STESs-based framework and applies it to 15 demonstration sites in Guangdong Province, China, to explore the dynamic interplay among technological innovation, stakeholder engagement, fisheries governance, ecosystem health, biodiversity, and community participation. Through regression analyses and descriptive statistics, we quantified these multi-layered interactions. The study’s findings reveal significant correlations that underscore the importance of integrated approaches to marine ranching sustainability. Notably, stakeholder engagement is strongly linked to technological adoption (r = 0.58), suggesting that inclusive decision-making processes can drive the uptake of innovative, sustainable technologies. Furthermore, technological adoption is positively correlated with ecosystem health (r = 0.62), highlighting the potential for sustainable technologies to enhance marine ecosystem well-being. Community participation emerges as a critical factor in biodiversity conservation (r = 0.71), emphasizing the value of collaborative conservation efforts. Additionally, the strong predictive relationship between marine biodiversity and water quality (β = 0.85, p = 0.001) underscores the importance of preserving biodiversity for maintaining good water quality, which is fundamental to the health and sustainability of marine ranching systems. These insights collectively support the development of holistic management strategies that integrate social, technological, and ecological dimensions to promote the resilience and sustainability of marine ranching. These results underscore the crucial roles of participatory governance, sustainable fishery practices, and biodiversity protection in strengthening the ecological resilience of marine ranching systems. Full article

Microplastic pollution presents a significant and rising risk to both ecological integrity and the long-term viability of economic activities reliant on marine ecosystems. The Black Sea, a region sustaining economic sectors such as fisheries, tourism, and maritime transport, is increasingly vulnerable to this form of contamination. Mytilus galloprovincialis, a well-established bioindicator, accumulates microplastics, providing a direct measure of environmental pollution and indicating potential economic consequences deriving from degraded ecosystem services. While previous studies have documented microplastic pollution in the Black Sea, our paper specifically quantified microplastic contamination in M. galloprovincialis collected from four sites along the western Black Sea coast, each characterised by distinct levels of anthropogenic influence: Midia Port, Constanta Port, Mangalia Port, and 2 Mai. We used statistical analysis to quantify site-specific microplastic contamination in M. galloprovincialis and employed machine learning to develop models predicting accumulation patterns based on environmental variables. Our findings demonstrate the efficacy of mussels as bioindicators of marine plastic pollution and highlight the utility of machine learning in developing effective predictive tools for monitoring and managing marine litter contamination in marine environments, thereby contributing to sustainable economic practices. Full article

Nuclear accident-derived radionuclide dispersion poses critical challenges to marine ecological sustainability and human–ocean interdependence. While existing studies focus on hydrodynamic modeling of pollutant transport, the link between nuclear safety and sustainable ocean governance remains underexplored. This study investigates radionuclide diffusion patterns in semi-enclosed bays using a high-resolution coupled hydrodynamic particle-tracking model, explicitly addressing threats to marine ecosystem stability and coastal socioeconomic resilience. Simulations revealed that tidal oscillations and topographic constraints prolong pollutant retention by 40% compared to open seas, elevating local concentration peaks by 2–3× and intensifying bioaccumulation risks in benthic organisms. These findings directly inform sustainable marine resource management: the identified high-risk zones enable targeted monitoring of fishery resources, while diffusion pathways guide coastal zoning policies to decouple economic activities from contamination hotspots. Compared to Fukushima’s open-ocean dispersion models, our framework uniquely quantifies how semi-enclosed geomorphology exacerbates localized ecological degradation, providing actionable metrics for balancing nuclear energy development with UN Sustainable Development Goals (SDGs) 14 and 3. By integrating hydrodynamic specificity with ecosystem vulnerability thresholds, this work advances science-based protocols for sustainable nuclear facility siting and marine spatial planning. Full article

Accurate fish species identification is crucial for marine biodiversity conservation, environmental monitoring, and sustainable fishery management, particularly as marine ecosystems face increasing pressures from human activities and climate change. Traditional morphological identification methods are inherently labor-intensive and resource-demanding, while contemporary automated approaches, particularly deep learning models, often suffer from significant computational overhead and struggle with the pervasive issue of class imbalance inherent in ecological datasets. Addressing these limitations, this research introduces a novel computationally parsimonious fish classification framework leveraging the hybrid Mobile–Former neural network architecture. This architecture strategically combines the local feature extraction strengths of convolutional layers with the global context modeling capabilities of transformers, optimized for efficiency. To specifically mitigate the detrimental effects of the skewed data distributions frequently observed in real-world fish surveys, the framework incorporates a sophisticated robust asymmetric loss function designed to enhance model focus on under-represented categories and improve resilience against noisy labels. The proposed system was rigorously evaluated using the comprehensive FishNet dataset, comprising 74,935 images distributed across a detailed taxonomic hierarchy including eight classes, seventy-two orders, and three-hundred-forty-eight families, reflecting realistic ecological diversity. Our model demonstrates superior classification accuracy, achieving 93.97 percent at the class level, 88.28 percent at the order level, and 84.02 percent at the family level. Crucially, these high accuracies are attained with remarkable computational efficiency, requiring merely 508 million floating-point operations, significantly outperforming comparable state-of-the-art models in balancing performance and resource utilization. This advancement provides a streamlined, effective, and resource-conscious methodology for automated fish species identification, thereby strengthening ecological monitoring capabilities and contributing significantly to the informed conservation and management of vital marine ecosystems. 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

Understanding the dynamics of phytoplankton size classes (PSCs), highly sensitive to environmental conditions in marine ecosystems, is crucial for comprehending variations in primary production and biogeochemical processes. Over the past decades, the littoral seas of Korea have undergone significant environmental shifts, yet long-term studies on PSC distribution remain limited. Employing a regionally developed deep neural network model and 20 years (2003–2022) of satellite ocean color data, we assessed spatiotemporal variability in dominant PSCs in the Yellow Sea (YS), South Sea of Korea (SS), and East/Japan Sea (EJS). Micro-size phytoplankton dominated turbid nearshore waters of the YS and western SS year-round, while nano-size phytoplankton were seasonally prevalent in the central YS and EJS. Pico-size phytoplankton exhibited strong summer dominance under warm, stratified, nutrient-depleted conditions, showing a sustained long-term expansion across all regions, particularly in the southwestern EJS. This expansion was closely linked to rising sea surface temperatures and changes in nutrient stoichiometry. The increasing dominance of smaller phytoplankton may reduce primary production, alter food web structure, and ultimately diminish fishery productivity. These findings provide new insight into climate-driven ecological shifts in marginal seas and underscore the need for integrated long-term monitoring to anticipate future ecosystem responses in a rapidly warming ocean. Full article

Pakistan’s marine fishing industry is crucial to the country’s economy, generating employment opportunities and foreign revenue. It produces 80% of the country’s total fish production. Otolithes ruber is a commercially important fish on the Makran coast of Pakistan, contributing significantly to the region’s croaker fisheries. This study is the first to apply three length-based approaches for assessing the stock status of O. ruber in the Makran coast: (1) TropFishR to estimate the mortality, growth parameters, and current exploitation status, reference points based on the yield per recruitment model, (2) the length-based Bayesian biomass method (LBB) to calculate stock biomass, and (3) the length-based spawning potential ratio (LBSPR) to estimate the spawning potential ratio. The length–weight relationship of Otolithes ruber was a positive allometric pattern (b = 3.28; R² = 0.94). Growth parameters for Otolithes ruber were L_∞ = 55.47 cm, K = 0.50 year⁻¹. The calculated total mortality rate (Z), natural mortality (M), and fishing mortality (F) were 2.27 year⁻¹, 0.67 year⁻¹, and 1.6 year⁻¹, respectively. The exploitation rate (E) was 0.70, indicating severe overexploitation. The current length at first capture (Lc₅₀) = 27.37 cm was lower than that at first maturity (Lm₅₀) = 30.75 cm, indicating growth overfishing. The current spawning potential ratio (8%) was lower than the optimal value (40%), indicating recruitment overfishing. The current biomass, concerning virgin biomass B/B_o, was also 8%, resulting in a 92% stock decline. We recommend reducing the exploitation pressure by limiting the commercial catch to an optimum length range of 34.5–42.2 cm and reducing fishing pressure by 40% to ensure sustainable fishery management. Full article

The escalating conflict between cetaceans and fisheries underscores the need for efficient mitigation strategies that balance conservation priorities with economic viability. This study presents a TinyML-driven approach deploying an optimized Convolutional Neural Network (CNN) on a Raspberry Pi Zero 2 W for real-time detection of bottlenose dolphin whistles, leveraging spectrogram analysis to address acoustic monitoring challenges. Specifically, a CNN model previously developed for classifying dolphins’ vocalizations and originally implemented with TensorFlow was converted to TensorFlow Lite (TFLite) with architectural optimizations, reducing the model size by 76%. Both TensorFlow and TFLite models were trained on 22 h of underwater recordings taken in controlled environments and processed into 0.8 s spectrogram segments (300 × 150 pixels). Despite reducing model size, TFLite models maintained the same accuracy as the original TensorFlow model (87.8% vs. 87.0%). Throughput and latency were evaluated by varying the thread allocation (1–8 threads), revealing the best performance at 4 threads (quad-core alignment), achieving an inference latency of 120 ms and sustained throughput of 8 spectrograms/second. The system demonstrated robustness in 120 h of continuous stress tests without failure, underscoring its reliability in marine environments. This work achieved a critical balance between computational efficiency and detection fidelity (F1-score: 86.9%) by leveraging quantized, multithreaded inference. These advancements enable low-cost devices for real-time cetacean presence detection, offering transformative potential for bycatch reduction and adaptive deterrence systems. This study bridges artificial intelligence innovation with ecological stewardship, providing a scalable framework for deploying machine learning in resource-constrained settings while addressing urgent conservation challenges. Full article