Pub Date : 2026-03-16DOI: 10.3389/fmars.2026.1783157
Zongquan Ying, Wengeng Shen, Xuegang Wang, Yiming Zhao, Meihong Lin
To improve the accuracy and robustness of significant wave height prediction under complex marine conditions, a multi-strategy Snow Ablation Optimization (GVSAO) model based on the Good Point Set Initialization Strategy (G), Cyclic Oscillation Mutation Strategy (V), and Snow Ablation Optimizer (SAO) is proposed to enhance parameter optimization. The GVSAO model combines Convolutional Neural Networks (CNN), Bidirectional Gated Recurrent Units (BiGRU), and a Self-Attention Mechanism (SA) to construct the GVSAO-CNN-BiGRU-SA framework, which fully exploits the nonlinear characteristics of wave height time series. The study utilizes observed data from two observation points along the U.S. East Coast to the Gulf of Mexico (Stations 41013 and 42002) as well as from the Arabian Sea (Station 23020) and the Pacific Ocean (Station 46044). Comparative experiments on input feature combinations reveal that Intrinsic Mode Function (IMF) components derived from Variational Mode Decomposition (VMD) contribute more significantly to prediction accuracy than single physical features by effectively capturing dynamic time-frequency characteristics. The results demonstrate that the GVSAO model outperforms SAO, GSAO, and VSAO in terms of global exploration and stability, as validated by performance comparisons on the CEC2005 benchmark functions. Compared with the BiGRU model, the GVSAO-CNN-BiGRU-SA model exhibited superior performance, with RMSE reduced by 44.01% at Station 41013 and 15.12% at Station 42002. Similarly, it outperformed the CNN-BiGRU and CNN-BiGRU-SA models across all key metrics. The model achieved high-accuracy predictions in diverse marine environments, with relative mean errors within 0.5472%, RMSE within 0.1064 m, and correlation coefficients (R2) exceeding 0.99. Furthermore, in multi-step forecasting (3 to 48 hours), the model maintained high reliability with R2 values remaining above 0.84 across diverse geographic environments. The GVSAO-CNN-BiGRU-SA model provides a reliable solution for wave height prediction, contributing to marine engineering early warnings and energy utilization.
为了提高复杂海洋条件下显著波高预测的精度和鲁棒性，提出了基于Good Point Set Initialization Strategy (G)、Cyclic Oscillation Mutation Strategy (V)和Snow Ablation Optimizer （SAO）的多策略雪蚀优化（GVSAO）模型，以加强参数优化。GVSAO模型结合卷积神经网络（CNN）、双向门控循环单元（BiGRU）和自注意机制（SA）构建了GVSAO-CNN-BiGRU-SA框架，充分利用了波高时间序列的非线性特性。该研究利用了沿美国东海岸到墨西哥湾的两个观测点（41013和42002站）以及阿拉伯海（23020站）和太平洋（46044站）的观测数据。输入特征组合的对比实验表明，由变分模态分解（VMD）得到的内禀模态函数（IMF）分量比单一物理特征更能有效捕获动态时频特征，对预测精度的贡献更显著。结果表明，GVSAO模型在全局探索性和稳定性方面优于SAO、GSAO和VSAO，并在CEC2005基准函数上进行了性能比较。与BiGRU模型相比，GVSAO-CNN-BiGRU-SA模型在41013站和42002站的RMSE分别降低了44.01%和15.12%。同样，它在所有关键指标上都优于CNN-BiGRU和CNN-BiGRU- sa模型。模型对不同海洋环境的预测精度较高，相对平均误差在0.5472%以内，RMSE在0.1064 m以内，相关系数（R2）超过0.99。此外，在多步预测（3 ~ 48 h）中，模型在不同地理环境下均保持较高的可靠性，R2值均保持在0.84以上。GVSAO-CNN-BiGRU-SA模型为波高预测提供了可靠的解决方案，有助于海洋工程预警和能源利用。
{"title":"A significant wave height prediction method combining VMD decomposition and the GVSAO-CNN-BiGRU-SA model","authors":"Zongquan Ying, Wengeng Shen, Xuegang Wang, Yiming Zhao, Meihong Lin","doi":"10.3389/fmars.2026.1783157","DOIUrl":"https://doi.org/10.3389/fmars.2026.1783157","url":null,"abstract":"To improve the accuracy and robustness of significant wave height prediction under complex marine conditions, a multi-strategy Snow Ablation Optimization (GVSAO) model based on the Good Point Set Initialization Strategy (G), Cyclic Oscillation Mutation Strategy (V), and Snow Ablation Optimizer (SAO) is proposed to enhance parameter optimization. The GVSAO model combines Convolutional Neural Networks (CNN), Bidirectional Gated Recurrent Units (BiGRU), and a Self-Attention Mechanism (SA) to construct the GVSAO-CNN-BiGRU-SA framework, which fully exploits the nonlinear characteristics of wave height time series. The study utilizes observed data from two observation points along the U.S. East Coast to the Gulf of Mexico (Stations 41013 and 42002) as well as from the Arabian Sea (Station 23020) and the Pacific Ocean (Station 46044). Comparative experiments on input feature combinations reveal that Intrinsic Mode Function (IMF) components derived from Variational Mode Decomposition (VMD) contribute more significantly to prediction accuracy than single physical features by effectively capturing dynamic time-frequency characteristics. The results demonstrate that the GVSAO model outperforms SAO, GSAO, and VSAO in terms of global exploration and stability, as validated by performance comparisons on the CEC2005 benchmark functions. Compared with the BiGRU model, the GVSAO-CNN-BiGRU-SA model exhibited superior performance, with RMSE reduced by 44.01% at Station 41013 and 15.12% at Station 42002. Similarly, it outperformed the CNN-BiGRU and CNN-BiGRU-SA models across all key metrics. The model achieved high-accuracy predictions in diverse marine environments, with relative mean errors within 0.5472%, RMSE within 0.1064 m, and correlation coefficients (R2) exceeding 0.99. Furthermore, in multi-step forecasting (3 to 48 hours), the model maintained high reliability with R2 values remaining above 0.84 across diverse geographic environments. The GVSAO-CNN-BiGRU-SA model provides a reliable solution for wave height prediction, contributing to marine engineering early warnings and energy utilization.","PeriodicalId":12479,"journal":{"name":"Frontiers in Marine Science","volume":"24 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2026-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147470905","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-13DOI: 10.3389/fmars.2026.1774634
Jian Hou, Diankai Wang, Zhiyi Huang, Huan Nong
This paper addresses mismatched equipment combinations, lack of end-to-end carbon emission accounting, and difficulty in quantifying uncertainty in intermodal transport. We propose a comprehensive framework integrating integer programming and Monte Carlo simulation. The framework builds an end-to-end carbon emission model covering loading/unloading as well as land and water transport, optimizing equipment combinations to minimize carbon emissions across multiple scenarios. A two-step approach using variance analysis and Monte Carlo simulation enhances quantification efficiency and accuracy. The results show that the optimized mixed equipment configuration reduces carbon emissions by 7.6% to 20.5%, especially in medium-high weight goods and medium-short distance transport. Monte Carlo simulation quantifies emission fluctuations, helping decision-makers develop strategies based on risk tolerance. This research provides technical support for emission optimization and effective risk management tools for decision-making, aligning with green logistics and low-carbon transportation goals.
{"title":"Carbon emission optimization and uncertainty quantification in multi-scenario water–land transport","authors":"Jian Hou, Diankai Wang, Zhiyi Huang, Huan Nong","doi":"10.3389/fmars.2026.1774634","DOIUrl":"https://doi.org/10.3389/fmars.2026.1774634","url":null,"abstract":"This paper addresses mismatched equipment combinations, lack of end-to-end carbon emission accounting, and difficulty in quantifying uncertainty in intermodal transport. We propose a comprehensive framework integrating integer programming and Monte Carlo simulation. The framework builds an end-to-end carbon emission model covering loading/unloading as well as land and water transport, optimizing equipment combinations to minimize carbon emissions across multiple scenarios. A two-step approach using variance analysis and Monte Carlo simulation enhances quantification efficiency and accuracy. The results show that the optimized mixed equipment configuration reduces carbon emissions by 7.6% to 20.5%, especially in medium-high weight goods and medium-short distance transport. Monte Carlo simulation quantifies emission fluctuations, helping decision-makers develop strategies based on risk tolerance. This research provides technical support for emission optimization and effective risk management tools for decision-making, aligning with green logistics and low-carbon transportation goals.","PeriodicalId":12479,"journal":{"name":"Frontiers in Marine Science","volume":"20 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2026-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147440462","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-13DOI: 10.3389/fmars.2026.1764145
Costanza Cappelli, Hjálmar Hátún, Jan Arge Jacobsen, André W. Visser, Flemming Thorbjørn Hansen, Jonas B. Mortensen, Sara Accornero, Francisca Rodrigues, Brian R. MacKenzie
Environmental drivers of early life-stage survival are critical to understanding recruitment variability and improving ecosystem-based fisheries management. We investigate how regional ocean circulation influences blue whiting ( Micromesistius poutassou ) recruitment in the Northeast Atlantic by combining multi-decadal transport analyses with Lagrangian particle simulations. Using ocean reanalysis, we compute 28-year (1993-2020) volume transport indices across the Ellett Line, a hydrographic section through the main spawning grounds, and we relate them to interannual variation in recruit per spawner. We also simulate larval dispersal from main spawning areas (Porcupine Bank, Rockall Trough, Rockall Plateau, Hebrides) during the six highest and lowest recruit-per-spawner years using an agent-based particle-tracking model. Statistical models show that higher recruit per spawners are produced in years with stronger northward flow along the Hebrides-Rockall Trough (upper 0–100 m), whereas transport over Rockall Plateau is weaker and exhibits no consistent relationship with recruit per spawner. Complementary particle-tracking simulations reveal that high-recruit-per-spawner years are characterized by larger northward advection of eggs and larvae from the Hebrides, as well as increased local retention over Porcupine Bank. In contrast, low-recruit-per-spawner years exhibit more meandering drift in the Rockall region and a modest southward dispersal from Porcupine Bank. These results suggest that both effective transport to known northern nursery areas and retention in productive spawning regions can enhance early survival, depending on spawning location. We propose that large-scale ocean-climate variability (e.g., changes in subpolar gyre circulation driven by wind stress curl) modulates these transport mechanisms, thereby influencing whether early life stages are delivered to favorable habitats or lost to suboptimal areas. Our findings provide a mechanistic link between climate-driven circulation changes and fish recruitment variability, underscoring a potential benefit of incorporating oceanographic processes into ecosystem-based fisheries management strategies.
{"title":"Circulation-driven dispersal and retention affect blue whiting recruitment dynamics in the Northeast Atlantic Ocean","authors":"Costanza Cappelli, Hjálmar Hátún, Jan Arge Jacobsen, André W. Visser, Flemming Thorbjørn Hansen, Jonas B. Mortensen, Sara Accornero, Francisca Rodrigues, Brian R. MacKenzie","doi":"10.3389/fmars.2026.1764145","DOIUrl":"https://doi.org/10.3389/fmars.2026.1764145","url":null,"abstract":"Environmental drivers of early life-stage survival are critical to understanding recruitment variability and improving ecosystem-based fisheries management. We investigate how regional ocean circulation influences blue whiting ( <jats:italic>Micromesistius poutassou</jats:italic> ) recruitment in the Northeast Atlantic by combining multi-decadal transport analyses with Lagrangian particle simulations. Using ocean reanalysis, we compute 28-year (1993-2020) volume transport indices across the Ellett Line, a hydrographic section through the main spawning grounds, and we relate them to interannual variation in recruit per spawner. We also simulate larval dispersal from main spawning areas (Porcupine Bank, Rockall Trough, Rockall Plateau, Hebrides) during the six highest and lowest recruit-per-spawner years using an agent-based particle-tracking model. Statistical models show that higher recruit per spawners are produced in years with stronger northward flow along the Hebrides-Rockall Trough (upper 0–100 m), whereas transport over Rockall Plateau is weaker and exhibits no consistent relationship with recruit per spawner. Complementary particle-tracking simulations reveal that high-recruit-per-spawner years are characterized by larger northward advection of eggs and larvae from the Hebrides, as well as increased local retention over Porcupine Bank. In contrast, low-recruit-per-spawner years exhibit more meandering drift in the Rockall region and a modest southward dispersal from Porcupine Bank. These results suggest that both effective transport to known northern nursery areas and retention in productive spawning regions can enhance early survival, depending on spawning location. We propose that large-scale ocean-climate variability (e.g., changes in subpolar gyre circulation driven by wind stress curl) modulates these transport mechanisms, thereby influencing whether early life stages are delivered to favorable habitats or lost to suboptimal areas. Our findings provide a mechanistic link between climate-driven circulation changes and fish recruitment variability, underscoring a potential benefit of incorporating oceanographic processes into ecosystem-based fisheries management strategies.","PeriodicalId":12479,"journal":{"name":"Frontiers in Marine Science","volume":"8 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2026-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147440465","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Fishery resources are among the most economically valuable assets from aquatic ecosystems, underpinning global food security, nutrition, and livelihoods. However, their sustainable management is increasingly challenged by anthropogenic pressures, including overexploitation, and pollution, which not only deplete stocks, but also compromise the health of human and aquatic organism. In this context, the One Health framework, an integrated approach recognizing the interdependence of human, aquatic organism, and environmental health, provides a critical lens for fisheries governance to ensure long-term resource sustainability. It calls for coordinated surveillance of biological and environmental indicators across trophic levels to anticipate and mitigate risks such as pathogen emergence, biodiversity loss, and fishery resource depletion. Environmental DNA (eDNA) has emerged as a promising exploratory tool in fisheries science and aquatic ecology, offering a non-invasive and system-wide monitoring mean to detect presence and composition of cross-domain organisms (from microbes to aquatic animals) and even inferring relative or absolute abundance. Its ability to simultaneously interrogate multiple components of the aquatic biosphere aligns uniquely with the multisectoral objectives of One Health. As such, eDNA functions not as a standalone solution, but as a synergistic component within integrated assessment frameworks that link ecosystem status, fishery productivity, and public health outcomes. Nonetheless, methodological challenges remain, particularly in designing primers, expanding and curating reference databases, standardizing sampling and bioinformatic protocols, and developing robust quantitative models translating eDNA signals into actionable stock or risk assessments. This review critically examines the applications, limitations, and future trajectories of eDNA technology in fisheries science through the lens of One Health, with emphasis on its potential to inform cross-scale, interdisciplinary strategies for sustainable fishery management.
{"title":"Harnessing environmental DNA: revolutionizing holistic monitoring of aquatic biodiversity for fishery management under the One Health framework","authors":"Mingyang Zhang, Xinyi Guo, Zhiyong Zheng, Shanglin Yang, Jingyi Li, Jun Lv, Wenyan Xu, Pengsheng Dong","doi":"10.3389/fmars.2026.1747671","DOIUrl":"https://doi.org/10.3389/fmars.2026.1747671","url":null,"abstract":"Fishery resources are among the most economically valuable assets from aquatic ecosystems, underpinning global food security, nutrition, and livelihoods. However, their sustainable management is increasingly challenged by anthropogenic pressures, including overexploitation, and pollution, which not only deplete stocks, but also compromise the health of human and aquatic organism. In this context, the One Health framework, an integrated approach recognizing the interdependence of human, aquatic organism, and environmental health, provides a critical lens for fisheries governance to ensure long-term resource sustainability. It calls for coordinated surveillance of biological and environmental indicators across trophic levels to anticipate and mitigate risks such as pathogen emergence, biodiversity loss, and fishery resource depletion. Environmental DNA (eDNA) has emerged as a promising exploratory tool in fisheries science and aquatic ecology, offering a non-invasive and system-wide monitoring mean to detect presence and composition of cross-domain organisms (from microbes to aquatic animals) and even inferring relative or absolute abundance. Its ability to simultaneously interrogate multiple components of the aquatic biosphere aligns uniquely with the multisectoral objectives of One Health. As such, eDNA functions not as a standalone solution, but as a synergistic component within integrated assessment frameworks that link ecosystem status, fishery productivity, and public health outcomes. Nonetheless, methodological challenges remain, particularly in designing primers, expanding and curating reference databases, standardizing sampling and bioinformatic protocols, and developing robust quantitative models translating eDNA signals into actionable stock or risk assessments. This review critically examines the applications, limitations, and future trajectories of eDNA technology in fisheries science through the lens of One Health, with emphasis on its potential to inform cross-scale, interdisciplinary strategies for sustainable fishery management.","PeriodicalId":12479,"journal":{"name":"Frontiers in Marine Science","volume":"33 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2026-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147440466","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-13DOI: 10.3389/fmars.2026.1796684
Mirko Rupani, Ana J. Abascal, Rodrigo Manzanas, Javier García-Alba, Andrés García
High-resolution hydrodynamic data are essential for coastal and estuarine management. However, traditional downscaling methods based on numerical modeling remain computationally expensive, limiting their applicability for long-term hindcasts and operational forecasting systems. This study evaluates the use of machine learning for the reconstruction of sea surface height and surface currents in a semi-enclosed estuary, using Santander Bay as a case study. Three techniques spanning increasing model complexity are analyzed: K-nearest neighbors, Adaptive Boosting, and long short-term memory networks. The models are trained to emulate high-resolution hydrodynamic-model outputs using a comprehensive set of tidal, meteorological, and fluvial forcings. Performance is assessed through spatial validation, cluster-based analysis, representative-point time series, and independent comparison against in-situ observations. Results show that all techniques successfully reproduce the main hydrodynamic patterns, with accuracy increasing with model complexity. Long short-term memory networks achieve the highest skill in tidally energetic regions, while Adaptive Boosting provides more stable performance in low-energy and shoreline areas. Computational cost analysis demonstrates that all machine-learning approaches achieve speedups of several orders of magnitude relative to numerical modelling, with inference costs that are negligible at both point and domain scales. These findings demonstrate the potential of machine learning as a computationally efficient approach for high-resolution modelling of coastal hydrodynamics, with important implications for operational forecasting and coastal management applications.
{"title":"High-resolution modeling of local-scale currents using machine learning and artificial intelligence: application to Santander Bay","authors":"Mirko Rupani, Ana J. Abascal, Rodrigo Manzanas, Javier García-Alba, Andrés García","doi":"10.3389/fmars.2026.1796684","DOIUrl":"https://doi.org/10.3389/fmars.2026.1796684","url":null,"abstract":"High-resolution hydrodynamic data are essential for coastal and estuarine management. However, traditional downscaling methods based on numerical modeling remain computationally expensive, limiting their applicability for long-term hindcasts and operational forecasting systems. This study evaluates the use of machine learning for the reconstruction of sea surface height and surface currents in a semi-enclosed estuary, using Santander Bay as a case study. Three techniques spanning increasing model complexity are analyzed: K-nearest neighbors, Adaptive Boosting, and long short-term memory networks. The models are trained to emulate high-resolution hydrodynamic-model outputs using a comprehensive set of tidal, meteorological, and fluvial forcings. Performance is assessed through spatial validation, cluster-based analysis, representative-point time series, and independent comparison against <jats:italic>in-situ</jats:italic> observations. Results show that all techniques successfully reproduce the main hydrodynamic patterns, with accuracy increasing with model complexity. Long short-term memory networks achieve the highest skill in tidally energetic regions, while Adaptive Boosting provides more stable performance in low-energy and shoreline areas. Computational cost analysis demonstrates that all machine-learning approaches achieve speedups of several orders of magnitude relative to numerical modelling, with inference costs that are negligible at both point and domain scales. These findings demonstrate the potential of machine learning as a computationally efficient approach for high-resolution modelling of coastal hydrodynamics, with important implications for operational forecasting and coastal management applications.","PeriodicalId":12479,"journal":{"name":"Frontiers in Marine Science","volume":"9 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2026-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147440469","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-13DOI: 10.3389/fmars.2026.1740130
Shan Zheng, Chao Sun, Lianghong Yu
Government subsidies serve as a crucial catalyst for the value realization of ocean carbon sinks. However, the existing literature does not address what subsidy strategy the government should adopt. So, this study constructs a model for the value realization of ecological products associated with ocean carbon sinks, involving the government, production firms, trading platforms and demand firms. It further develops a four-party evolutionary game model to analyze and simulate government subsidy strategies. The findings are as follows. (1) Government subsidies not only foster the value realization of ocean carbon sinks, but also influence the behaviors of trading platforms, production and demand firms. (2) The optimal subsidy strategy varies depending on the distinct cost-benefit considerations of the four parties involved. (3) While government subsidies is essential, there is a finite limit to their allocation for ocean carbon sinks. (4) Comparatively, subsidizing production firms proves to be more effective in promoting the value realization of ocean carbon sinks than subsidizing trading platforms and demand firms. Therefore, the government should moderately enhance the probability of direct subsidies for ocean carbon sinks, reasonably determine the subsidy amount, optimize the structure of direct subsidy recipients. This study can provide reference for optimizing government subsidy strategies and the value realization of ocean carbon sinks.
{"title":"How government subsidy promote the value realization of ocean carbon sinks in China?","authors":"Shan Zheng, Chao Sun, Lianghong Yu","doi":"10.3389/fmars.2026.1740130","DOIUrl":"https://doi.org/10.3389/fmars.2026.1740130","url":null,"abstract":"Government subsidies serve as a crucial catalyst for the value realization of ocean carbon sinks. However, the existing literature does not address what subsidy strategy the government should adopt. So, this study constructs a model for the value realization of ecological products associated with ocean carbon sinks, involving the government, production firms, trading platforms and demand firms. It further develops a four-party evolutionary game model to analyze and simulate government subsidy strategies. The findings are as follows. (1) Government subsidies not only foster the value realization of ocean carbon sinks, but also influence the behaviors of trading platforms, production and demand firms. (2) The optimal subsidy strategy varies depending on the distinct cost-benefit considerations of the four parties involved. (3) While government subsidies is essential, there is a finite limit to their allocation for ocean carbon sinks. (4) Comparatively, subsidizing production firms proves to be more effective in promoting the value realization of ocean carbon sinks than subsidizing trading platforms and demand firms. Therefore, the government should moderately enhance the probability of direct subsidies for ocean carbon sinks, reasonably determine the subsidy amount, optimize the structure of direct subsidy recipients. This study can provide reference for optimizing government subsidy strategies and the value realization of ocean carbon sinks.","PeriodicalId":12479,"journal":{"name":"Frontiers in Marine Science","volume":"54 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2026-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147440470","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
High-energy, short-lived typhoon deposition can disrupt particle–water interactions, raising the question of whether rare earth elements (REEs) in event deposits still reflect equilibrium-controlled partitioning or instead capture transient, non-equilibrium geochemical states. We sampled a ~0.5–1 cm surface storm layer and underlying background sediments at 11 stations in the northeastern Beibu Gulf on 29–30 September 2024 (20–21 days after Typhoon Yagi), and quantified major/trace elements and REEs by ICP-OES and ICP-MS, integrating grain size/TOC and statistical correlations. Storm deposits show systematically lower ∑REE and LREE concentrations and slightly lower LREE/HREE ratios than background sediments, accompanied by weaker negative Eu anomalies and a shift toward slightly negative Ce anomalies relative to the mild positive Ce anomaly in background deposits. Despite finer textures and elevated TOC in the storm deposits, the canonical grain-size/adsorption control collapses, with ∑REE exhibiting little to no correlation with grain-size under storm conditions. Critically, storm deposits display pronounced LREE–HREE decoupling: LREE behave quasi-conservatively with “event-scale inertia”, whereas HREE respond more sensitively to non-equilibrium carrier reorganization and rapid settling. This selective decoupling provides a diagnostic geochemical fingerprint for identifying event-driven sedimentation and highlights the need to incorporate kinetic/time-scale effects when interpreting REE-based proxies in dynamic environments.
{"title":"Nonequilibrium fractionation of rare earth elements during typhoon-induced event sedimentation","authors":"Yanbin Fan, Yunhai Li, Yunpeng Lin, Haidong Li, Hengbo Wang, Haibo Fan, Hannv Zhang, Guicai Zhong, Feng Jiang","doi":"10.3389/fmars.2026.1786074","DOIUrl":"https://doi.org/10.3389/fmars.2026.1786074","url":null,"abstract":"High-energy, short-lived typhoon deposition can disrupt particle–water interactions, raising the question of whether rare earth elements (REEs) in event deposits still reflect equilibrium-controlled partitioning or instead capture transient, non-equilibrium geochemical states. We sampled a ~0.5–1 cm surface storm layer and underlying background sediments at 11 stations in the northeastern Beibu Gulf on 29–30 September 2024 (20–21 days after Typhoon Yagi), and quantified major/trace elements and REEs by ICP-OES and ICP-MS, integrating grain size/TOC and statistical correlations. Storm deposits show systematically lower ∑REE and LREE concentrations and slightly lower LREE/HREE ratios than background sediments, accompanied by weaker negative Eu anomalies and a shift toward slightly negative Ce anomalies relative to the mild positive Ce anomaly in background deposits. Despite finer textures and elevated TOC in the storm deposits, the canonical grain-size/adsorption control collapses, with ∑REE exhibiting little to no correlation with grain-size under storm conditions. Critically, storm deposits display pronounced LREE–HREE decoupling: LREE behave quasi-conservatively with “event-scale inertia”, whereas HREE respond more sensitively to non-equilibrium carrier reorganization and rapid settling. This selective decoupling provides a diagnostic geochemical fingerprint for identifying event-driven sedimentation and highlights the need to incorporate kinetic/time-scale effects when interpreting REE-based proxies in dynamic environments.","PeriodicalId":12479,"journal":{"name":"Frontiers in Marine Science","volume":"7 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2026-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147440468","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-13DOI: 10.3389/fmars.2026.1775985
M. A. Pradeep, Saima Rehman, Irine Maria Jose, T. V. Arun Kumar, Vinaya Kumar Katneni, Adnan Hussain Gora, N. R. Dhanutha, Ashok Kumar Jangam, T. S. Azhar Shahansha, K. K. Vijayan
Climate-driven shifts in salinity regimes pose significant challenges to aquatic organisms, particularly those inhabiting dynamic coastal ecosystems. Etroplus suratensis (Pearl spot), a euryhaline cichlid capable of thriving across fresh, brackish, and marine environments, offers an excellent model for understanding molecular strategies underpinning salinity acclimation. This study investigated the transcriptomic reprogramming in the gills of fish acclimated for 21 days to freshwater (0‰), brackish water (18‰), and marine water (36‰) conditions. Freshwater exposure elicited a coordinated metabolic response characterized by activation of mitochondrial energy pathways, including oxidative phosphorylation and electron transport, to support ATP-intensive ion uptake, alongside enhanced ion transport functions and epithelial remodeling. In contrast, marine water exposure triggered a more pronounced osmoregulatory shift, with activation of calcium-dependent exocytosis and vesicular trafficking pathways central to maintaining ion balance under high salinity. However, prolonged marine water exposure also led to suppression of key antioxidant and immune pathways, revealing a potential trade-off whereby resources are redirected toward ion regulation at the expense of physiological defense mechanisms. Concurrent enrichment of cortisol synthesis, autophagy, apoptosis, and other stress-responsive pathways further reflects cellular remodeling and adaptive stress management under salinity stress. Collectively, these results demonstrate the remarkable metabolic plasticity and molecular resilience of E. suratensis , highlighting its capacity to deploy distinct, context-dependent mechanisms to maintain homeostasis across fluctuating salinity environments.
{"title":"Molecular adaptations of the estuarine fish Etroplus suratensis in response to salinity fluctuations","authors":"M. A. Pradeep, Saima Rehman, Irine Maria Jose, T. V. Arun Kumar, Vinaya Kumar Katneni, Adnan Hussain Gora, N. R. Dhanutha, Ashok Kumar Jangam, T. S. Azhar Shahansha, K. K. Vijayan","doi":"10.3389/fmars.2026.1775985","DOIUrl":"https://doi.org/10.3389/fmars.2026.1775985","url":null,"abstract":"Climate-driven shifts in salinity regimes pose significant challenges to aquatic organisms, particularly those inhabiting dynamic coastal ecosystems. <jats:italic>Etroplus suratensis</jats:italic> (Pearl spot), a euryhaline cichlid capable of thriving across fresh, brackish, and marine environments, offers an excellent model for understanding molecular strategies underpinning salinity acclimation. This study investigated the transcriptomic reprogramming in the gills of fish acclimated for 21 days to freshwater (0‰), brackish water (18‰), and marine water (36‰) conditions. Freshwater exposure elicited a coordinated metabolic response characterized by activation of mitochondrial energy pathways, including oxidative phosphorylation and electron transport, to support ATP-intensive ion uptake, alongside enhanced ion transport functions and epithelial remodeling. In contrast, marine water exposure triggered a more pronounced osmoregulatory shift, with activation of calcium-dependent exocytosis and vesicular trafficking pathways central to maintaining ion balance under high salinity. However, prolonged marine water exposure also led to suppression of key antioxidant and immune pathways, revealing a potential trade-off whereby resources are redirected toward ion regulation at the expense of physiological defense mechanisms. Concurrent enrichment of cortisol synthesis, autophagy, apoptosis, and other stress-responsive pathways further reflects cellular remodeling and adaptive stress management under salinity stress. Collectively, these results demonstrate the remarkable metabolic plasticity and molecular resilience of <jats:italic>E. suratensis</jats:italic> , highlighting its capacity to deploy distinct, context-dependent mechanisms to maintain homeostasis across fluctuating salinity environments.","PeriodicalId":12479,"journal":{"name":"Frontiers in Marine Science","volume":"9 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2026-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147440467","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-13DOI: 10.3389/fmars.2026.1758382
Yi Zhang, Xiaomin Zhang, Jie Yang
Introduction Underwater acoustic direction-of-arrival (DOA) estimation is fundamental to submarine detection, offshore exploration, and autonomous underwater vehicle navigation, where accurate source localization under severe multipath propagation and low signal-to-noise ratios remains challenging. Existing methods face critical limitations: traditional uniform arrays require extensive physical sensors to achieve sufficient spatial resolution, resulting in high hardware costs; vector sensor arrays typically neglect sparse array geometries that enable virtual aperture expansion; and conventional matrix-based processing discards multidimensional structural information through vectorization, leading to suboptimal performance. Methods To address these challenges, this paper presents a novel tensor-based DOA estimation framework that integrates hybrid scalar-vector sensor arrays (HSVSAs), fourth-order tensor modeling, and higher-order singular value decomposition (HOSVD). The HSVSA architecture combines vector and scalar sensors in a hybrid configuration to create virtual sensors, improving degrees of freedom while reducing hardware complexity. The tensor model preserves spatial–polarization coupling, enabling robust subspace estimation without iterative optimization. Results Simulations demonstrate that the proposed method outperforms conventional approaches. Discussion The proposed framework offers a practical solution for resource-constrained underwater acoustic applications, with potential for further optimization in real-world scenarios.
{"title":"Tensor-based DOA estimation for hybrid scalar–vector sensor arrays","authors":"Yi Zhang, Xiaomin Zhang, Jie Yang","doi":"10.3389/fmars.2026.1758382","DOIUrl":"https://doi.org/10.3389/fmars.2026.1758382","url":null,"abstract":"Introduction Underwater acoustic direction-of-arrival (DOA) estimation is fundamental to submarine detection, offshore exploration, and autonomous underwater vehicle navigation, where accurate source localization under severe multipath propagation and low signal-to-noise ratios remains challenging. Existing methods face critical limitations: traditional uniform arrays require extensive physical sensors to achieve sufficient spatial resolution, resulting in high hardware costs; vector sensor arrays typically neglect sparse array geometries that enable virtual aperture expansion; and conventional matrix-based processing discards multidimensional structural information through vectorization, leading to suboptimal performance. Methods To address these challenges, this paper presents a novel tensor-based DOA estimation framework that integrates hybrid scalar-vector sensor arrays (HSVSAs), fourth-order tensor modeling, and higher-order singular value decomposition (HOSVD). The HSVSA architecture combines vector and scalar sensors in a hybrid configuration to create virtual sensors, improving degrees of freedom while reducing hardware complexity. The tensor model preserves spatial–polarization coupling, enabling robust subspace estimation without iterative optimization. Results Simulations demonstrate that the proposed method outperforms conventional approaches. Discussion The proposed framework offers a practical solution for resource-constrained underwater acoustic applications, with potential for further optimization in real-world scenarios.","PeriodicalId":12479,"journal":{"name":"Frontiers in Marine Science","volume":"92 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2026-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147454719","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Objective This study aimed to identify, characterize, and determine the origin of semi-persistent gamma radiation anomalies in the Adriatic Sea along the Trieste-Panarea transect, establishing a high resolution radiometric baseline and assessing the influence of environmental parameters. Methods In situ gamma-ray spectrometry was conducted using an RS-250 NaI(Tl) detector aboard the R/V Laura Bassi during four research cruises, covering a total distance of over 2500 nautical miles. The spectrometer was configured with 1024 energy channels with range 3 keV and provided a resolution of 6-7% at the 662 keV photopeak of 137 Cs. More than 4000 recordings of the total gamma-ray count rate and full-spectrum data were collected. These radiological data were precisely synchronized and correlated with contemporaneous bathymetric, wind speed, air temperature, and humidity data. Results Three persistent anomaly regions were identified in the Central Adriatic, Southern Adriatic, and Strait of Otranto, with peak total counts per 10-minute sample of 34,659, 76,854, and 32,415, respectively. Spectral analysis revealed these are primarily sourced from natural Uranium ( 214 Bi, 214 Pb), Potassium ( 40 K), and Thorium ( 208 Tl, 212 Bi) decay series radionuclides, with a negligible anthropogenic 137 Cs contribution. Correlation analyses showed weak relationships with environmental variables (R² < 0.25 for wind, temperature, humidity, depth), confirming the anomalies are not artifacts of atmospheric or surface conditions but are linked to seabed processes. Conclusion The identified anomalies are natural features resulting from the oceanographic focusing of clay-rich, radiogenic sediments in specific depositional zones. This work provides a validated methodological inspection framework and a critical baseline for future geophysical mapping, environmental monitoring, and radiological assessment in the research cruises.
{"title":"Identification and characterization of gamma radiation anomalies along the Trieste–Panarea routes aboard R/V Laura Bassi","authors":"Behzad Salmassian, Massimiliano Iurcev, Alessio Trebbi, Franco Coren","doi":"10.3389/fmars.2026.1750403","DOIUrl":"https://doi.org/10.3389/fmars.2026.1750403","url":null,"abstract":"Objective This study aimed to identify, characterize, and determine the origin of semi-persistent gamma radiation anomalies in the Adriatic Sea along the Trieste-Panarea transect, establishing a high resolution radiometric baseline and assessing the influence of environmental parameters. Methods <jats:italic>In situ</jats:italic> gamma-ray spectrometry was conducted using an RS-250 NaI(Tl) detector aboard the R/V Laura Bassi during four research cruises, covering a total distance of over 2500 nautical miles. The spectrometer was configured with 1024 energy channels with range 3 keV and provided a resolution of 6-7% at the 662 keV photopeak of <jats:sup>137</jats:sup> Cs. More than 4000 recordings of the total gamma-ray count rate and full-spectrum data were collected. These radiological data were precisely synchronized and correlated with contemporaneous bathymetric, wind speed, air temperature, and humidity data. Results Three persistent anomaly regions were identified in the Central Adriatic, Southern Adriatic, and Strait of Otranto, with peak total counts per 10-minute sample of 34,659, 76,854, and 32,415, respectively. Spectral analysis revealed these are primarily sourced from natural Uranium ( <jats:sup>214</jats:sup> Bi, <jats:sup>214</jats:sup> Pb), Potassium ( <jats:sup>40</jats:sup> K), and Thorium ( <jats:sup>208</jats:sup> Tl, <jats:sup>212</jats:sup> Bi) decay series radionuclides, with a negligible anthropogenic <jats:sup>137</jats:sup> Cs contribution. Correlation analyses showed weak relationships with environmental variables (R² &lt; 0.25 for wind, temperature, humidity, depth), confirming the anomalies are not artifacts of atmospheric or surface conditions but are linked to seabed processes. Conclusion The identified anomalies are natural features resulting from the oceanographic focusing of clay-rich, radiogenic sediments in specific depositional zones. This work provides a validated methodological inspection framework and a critical baseline for future geophysical mapping, environmental monitoring, and radiological assessment in the research cruises.","PeriodicalId":12479,"journal":{"name":"Frontiers in Marine Science","volume":"52 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2026-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147440473","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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