Search Results (676)

As economically important sympatric species in the Northwest Pacific, the Japanese sardine (Sardinops melanostictus) and Chub mackerel (Scomber japonicus) exhibit significant biological interactions. Understanding the impact of interspecies competition on their habitat dynamics can provide crucial insights for the sustainable development and management of these interconnected species resources. This study utilizes fisheries data of S. melanostictus and S. japonicus from the Northwest Pacific, collected from June to November between 2017 and 2020. We integrated various environmental parameters, including temperature at different depths (0, 50, 100, 150, and 200 m), eddy kinetic energy (EKE), sea surface height (SSH), chlorophyll-a concentration (Chl-a), and the oceanic Niño index (ONI), to construct interspecific competition species distribution model (icSDM) for both species. We validated these models by overlaying the predicted habitats with fisheries data from 2021 and performing cross-validation to assess the models’ reliability. Furthermore, we conducted correlation analyses of the habitats of these two species to evaluate the impact of interspecies relationships on their habitat dynamics. The results indicate that, compared to single-species habitat models, the interspecific competition species distribution model (icSDM) for these two species exhibit a significantly higher explanatory power, with R² values increasing by up to 0.29; interspecific competition significantly influences the habitat dynamics of S. melanostictus and S. japonicus, strengthening the correlation between their habitat changes. This relationship exhibits a positive correlation at specific stages, with the highest correlations observed in June, July, and October, at 0.81, 0.80, and 0.88, respectively; interspecific competition also demonstrates stage-specific differences in its impact on the habitat dynamics of S. melanostictus and S. japonicus, with the most pronounced differences occurring in August and November. Compared to S. melanostictus, interspecific competition is more beneficial for the expansion of the optimal habitat (HIS ≥ 0.6) for S. japonicus and, to some extent, inhibits the habitat expansion of S. melanostictus. The variation in migratory routes and predatory interactions (with larger individuals of S. japonicus preying on smaller individuals of S. melanostictus) likely constitutes the primary factors contributing to these observed differences. Full article

Carbon emissions from freshwater aquaculture can exacerbate the greenhouse effect, thereby impacting human life and health. Consequently, it is of great significance to explore the carbon peak process and the role of emission reduction data in China’s freshwater aquaculture industry. This study innovatively employs the Logarithmic Mean Divisia Index model (LMDI) and the Tapio decoupling model to conduct an in-depth analysis of the relationship between carbon emissions and output values in the freshwater aquaculture industry, accurately identifying the main driving factors. Meanwhile, the global and local Moran’s I indices are introduced to analyze its spatial correlation from a new perspective. The results indicate that from 2013 to 2023, carbon emissions from China’s freshwater aquaculture industry exhibited a quasi-“N”-shaped trend, reaching a peak of 38 million tons in 2015. East China was the primary contributor to carbon emissions, accounting for 46%, while South China, Central China, and Northeast China each had an average annual share of around 14%, with Southwest, North China, and Northwest China contributing relatively small proportions. The global Moran’s I index showed a decreasing trend, with a p-value ≤ 0.0010 and a z-score > 3.3, indicating a 99% significant spatial correlation. High-high clusters were concentrated in some provinces of East China, while low-low clusters were found in Northwest, North, and Southwest China. The level of fishery economic development positively drove carbon emissions, whereas freshwater aquaculture production efficiency, industrial structure, and the scale of the aquaculture population had negative effects on carbon emissions. During the study period, carbon emissions exhibited three states: weak decoupling, strong decoupling, and expansive negative decoupling, with alternating strong and weak decoupling occurring after 2015. Full article

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 the past two decades, little information has been updated to understand the resource status of the crab species Ovalipes punctatus in the East China Sea Region. In this study, we conducted surveys in 2018 and 2019 to identify the seasonal spatial distribution patterns of the economically important sand crab Ovalipes punctatus (De Haan 1833) in the southern Yellow and East China Seas. In the study area, the largest biomass of crabs was observed in the fishing grounds of Dasha and the Yangtze River mouth, and the second largest biomass was detected in the Jiangwai-Zhouwai area. Seasonally, the total biomass order in these areas was summer > autumn & winter > spring, and the mean average individual weight order was spring & summer > winter > autumn. These findings provided maps of the seasonal spatial distribution pattern of the species across seasons, which were then used in climate-change scenario models. Model predictions suggested that O. punctatus might migrate northward and offshore under climate warming conditions, and that the climate scenario SSP585-2100 might be the most negative case, respectively, for the habitat area of gain% minus loss%. These data can be used to develop robust and systematic regional fisheries resource management policies that consider adaptation measures to address the impact of environmental and climate change along China’s coasts and other areas in the world. Full article

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

The effects of changes in China’s final demand structure on its forestry sector and associated supply chains have not been thoroughly examined. This study aims to provide a detailed analysis of the quantitative relationships and underlying mechanisms between these interactive changes. Using China’s 153-sector input–output tables from the National Bureau of Statistics and applying a Leontief-based input–output model, we conducted scenario simulations through three distinct schemes, generating both quantitative and qualitative results. Our findings indicate that (1) For China’s forestry sector and its entire value chain to thrive, policymakers should boost consumer demand. This can better stimulate the development of forestry and the “agriculture-forestry-animal husbandry-fishery services” sector and related service industries; (2) Increased investment demand effectively stimulates the development of tertiary industries and secondary industries within the forestry supply chain and boosts the demand and production of intermediate products; (3) Changes in net exports have a significant impact on forestry and the forestry industry chain. To reduce dependence on foreign timber resources, China should strategically expand commercial plantation development; (4) Regarding intermediate product production, investment has a more pronounced effect on increasing total volume compared to consumption. Additionally, the Sino–US tariff disputes negatively impact the forestry industries of both countries. China needs to accelerate import substitution strategies for timber products, adjust international trade markets, and expand domestic consumption and investment to ensure the healthy and stable development of its forestry sector. Full article

Background: Fish escape events from aquaculture facilities are increasing and pose significant ecological, economic, and traceability concerns. Accurate methods to differentiate between wild, cultured, and escaped fish are essential for fishery management and seafood authentication. Methods: This study analyzed muscle tissue from Sparus aurata, Dicentrarchus labrax, and Argyrosomus regius using a multiomics approach. Heavy metals were quantified by ICP-MS, fatty acid profiles were assessed via GC-MS, and metabolomic and lipidomic signatures were identified using 1H NMR spectroscopy. Multivariate statistical models (MDS and PLS-LDA) were applied to classify fish origins. Results: Wild seabream showed significantly higher levels of arsenic (9.5-fold), selenium (3.5-fold), and DHA and ARA fatty acids (3.2-fold), while cultured fish exhibited increased linoleic and linolenic acids (6.5-fold). TMAO concentrations were up to 5.3-fold higher in wild fish, serving as a robust metabolic biomarker. Escaped fish displayed intermediate biochemical profiles. Multivariate models achieved a 100% classification accuracy across species and analytical techniques. Conclusions: The integration of heavy metal analysis, fatty acid profiling, and NMR-based metabolomics enables the accurate differentiation of fish origin. While muscle tissue provides reliable biomarkers relevant to human exposure, future studies should explore additional tissues such as liver and gills to improve the resolution of traceability. These methods support seafood authentication, enhance aquaculture traceability, and aid in managing the ecological impacts of escape events. Full article

With the advantages of industrial integration, China’s recreational fishery sector represents a new trajectory in the transformation of the fishery industry. Coastal regions possess abundant fishery resources and have favorable geographical conditions, offering natural advantages for developing recreational fishing. However, substantial variations can be observed among regions regarding their resource endowments and economic conditions, leading to diversity in the driving forces and paths of recreational fishery development. This study employs panel data for 11 coastal provinces, municipalities, and autonomous regions in the Chinese mainland from 2005 to 2023 to explore the driving forces and regional heterogeneity of recreational fishery development. This paper employs fixed-effects estimation and further incorporates a mediating-effect model to explore the role of market demand in shaping the development path of recreational fisheries. The results are as follows: (1) Natural resource endowments and market demand are key driving forces that promote growth in the output value of recreational fisheries. (2) There is heterogeneity in the driving forces across regions. In areas with richer resource endowments or lower economic development levels, recreational fishery growth relies more on natural resource-driven mechanisms, whereas in regions with weaker resource endowments or higher economic development levels, market demand plays a more dominant role. (3) Market demand drives recreational fishery growth through the expansion of the tertiary sector. This paper offers a valuable reference for policymakers seeking to allocate resources more efficiently, support balanced regional development, and formulate tailored development strategies in accordance with local conditions, thereby facilitating the sustainable and high-quality development of the recreational fishery industry in the Chinese mainland. Full article

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

Recreational fisheries increasingly intersect with the habitats of flagship species, i.e., species that attract public attention and drive conservation efforts, raising potential ecological conflicts. This study investigated the spatial coupling between recreational fisheries and three flagship species in the Yangtze River Basin: the Chinese alligator (Alligator sinensis), the Yangtze finless porpoise (Neophocaena phocaenoides), and the scaly-sided merganser (Mergus squamatus). Drawing on over 10,000 fishing Points of Interest recorded between 2015 and 2024 and over 300 verified species occurrences, this study applied a Random Forest model with spatial integration and a Maximum Entropy model to examine estimated current distributions and forecast interactions from 2025 to 2035. Flagship species habitat suitability was modeled and projected at a spatial resolution of 1 km, while recreational fishing density was resolved on a coarser grid of 1.875° × 1.25° in latitude–longitude dimensions. Results reveal a substantial increase in high-risk overlap zones. For example, high-density fishing areas within high-suitability habitats for the scaly-sided merganser expanded from 0 km² in 2015 to 85,359 km² in 2024. Projections indicate continued intensification of such overlaps, particularly in regions including Ma’anshan–Wuhu, the Taihu–Chaohu–Poyang lake system, and Yibin. These findings offer robust, model-driven evidence of growing spatial conflicts and offer actionable insights for ecosystem-based governance. The methodological framework is transferable and supports broader applications in other regions and species under ecological sustainability goals. Full article

Gray snapper (Lutjanus griseus; Family: Lutjanidae) local habitat preferences have been assessed, but the biotic and abiotic factors influencing age and growth rates in Mosquito Lagoon, Florida, have not been quantified. To address this knowledge gap, the goal of this study was to estimate mean age and growth rate of gray snapper, and use generalized linear mixed models to investigate if prey and/or other environmental factors (e.g., abiotic/biotic conditions, time, location, or habitat restoration status) impact size at both the lagoon- and habitat-specific scales. Age data were extracted via otolith microstructural analyses, and incorporated with size into a lagoon-scale linear growth model. Based on microstructural analyses, mean age of gray snapper at the lagoon scale was 175 ± 66 days (range = 56–350 days). The results indicate the most common life stage of gray snapper in Mosquito Lagoon is juveniles, with living shoreline habitats having a greater proportion of relatively young juveniles (111 ± 36 days) and oyster reef habitats having a greater proportion of relatively older juveniles (198 ± 58 days). The estimated growth rate was 0.43 mm/day. Body mass and body length were correlated positively with habitat quality and lagged salinity levels. Hence future studies should strive to characterize benthic habitat characteristics, and investigate biotic and abiotic factors that potentially influence gray snapper growth. Collectively, this study increases our understanding of environmental drivers affecting juvenile gray snapper development and shows that the restoration of benthic habitats can produce conditions conducive to gray snapper growth. The age-, size-, and habitat-specific growth rates of juveniles from this study can be incorporated into stock assessments, and thereby be used to refine and develop more effective ecosystem-based management strategies for gray snapper fisheries. Full article

Growth is the most influential aspect in demographic species analysis. Collecting data on ages and sizes (such as length and weight) is a fundamental step in growth modeling, particularly in fishery science. Residual analysis plays a crucial role in parameterizing the mathematical models chosen to describe the growth patterns of the species under investigation. Using optimal residual criteria is essential to improving model performance and accuracy. In the present study, the length-at-age data of the Gulf corvina (Cynoscion othonopterus) were evaluated with the Schnute model to obtain the best error type and to establish the most accurate growth pattern. Later, the observed, constant, depensatory, and compensatory variance approaches were tested using the logistic model. The Bayesian information criterion (BIC) was used as the goodness-of-fit test to obtain the best variance approach parametrizing the growth model. The BIC values selected the observed variance as the best approach to parametrize the logistic growth model. The conclusion is that the observed variance approach produces robust results—that is, the observed variance produced the most plausible fits. It is suggested that the observed error structure should be used to estimate individual growth. Full article

Mapping marine habitats is fundamental for biodiversity conservation and ecosystem-based management in oceanic regions under increasing anthropogenic and climatic pressures. In the context of global initiatives—such as marine protected area expansion and international agreements—habitat mapping has become mandatory for regional and global conservation policies. It provides spatial data to delineate essential habitats, support connectivity analyses, and assess pressures, enabling ecosystem-based marine spatial planning aligned with EU directives (2008/56/EC; 2014/89/EU). Beyond biodiversity, macrophytes, rhodolith beds, and coral reefs deliver key ecosystem services—carbon sequestration, coastal protection, nursery functions, and fisheries support—essential to local socioeconomies. This systematic review (PRISMA guidelines) examined 69 peer-reviewed studies across Central-Eastern Atlantic archipelagos (Macaronesia: the Azores, Madeira, the Canaries, and Cabo Verde) and the Mid-Atlantic Ridge. We identified knowledge gaps, methodological trends, and key challenges, emphasizing the integration of cartographic, ecological, and technological approaches. Although methodologies diversified over time, the lack of survey standardization, limited ground truthing, and heterogeneous datasets constrained the production of high-resolution bionomic maps. Regional disparities persist in technology access and habitat coverage. The Azores showed the highest species richness (393), dominated by acoustic mapping in corals. Madeira was most advanced in the remote mapping of rhodoliths; the Canaries focused on shallow macrophytes with direct mapping; and Cabo Verde remains underrepresented. Harmonized protocols and regional cooperation are needed to improve data interoperability and predictive modeling. 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

Harmful Algal Blooms (HABs) are a growing environmental concern due to their adverse impacts on aquatic ecosystems, human health, and economic activities. These blooms are driven by a combination of factors, including nutrient enrichment, environmental factors, and hydrological conditions, leading to the excessive growth of algae. HABs produce toxins that threaten aquatic biodiversity, contaminate drinking water, and cause economic losses in fisheries and tourism. The causes of HABs are multifaceted, involving interactions between environmental factors such as temperature, light availability, and nutrient levels. Agricultural runoff, wastewater discharge, and industrial pollution introduce excessive nitrogen and phosphorus into water bodies, fueling bloom formation. Climate change further exacerbates the problem by altering precipitation patterns, increasing water temperatures, and intensifying coastal upwelling events, all of which create favorable conditions for HAB proliferation. This review explores the causes, ecological consequences, and potential mitigation strategies for HABs. Effective monitoring and detection methods, including satellite remote sensing, molecular biotechnology, and artificial intelligence-driven predictive models, offer promising avenues for early intervention. Sustainable management strategies such as nutrient load reductions, bioremediation, and regulatory policies can help mitigate the adverse effects of HABs. Public awareness and community involvement also play a crucial role in preventing and managing HAB events by promoting responsible agricultural practices, reducing waste discharge, and supporting conservation efforts. By examining existing literature and case studies, this study underscores the urgent need for comprehensive and interdisciplinary approaches to regulate HABs. Full article