Distribution and potential drivers of methane emissions from deep-sea environments in Haima cold seep areas - Li Tang; Jing-Chun Feng; Can-Rong Li; Xiao Chen; Hui Zhang; Si Zhang (Frontiers in Marine Science, 2025)
Introduction Tracing methane originating from deep-sea environments is essential for understanding the global methane budget. However, knowledge regarding the mechanisms governing methane transfer from deep-sea sediments to the water column in cold seep environments remains limited. This study aims to quantitatively investigate the distribution of methane and identify its controlling factors within the Haima cold seep areas. Methods A comprehensive analysis was conducted to investigate the distribution characteristics of methane and its potential drivers in both the water column and sediment porewaters within the Haima cold seep areas. Results The key findings are: (1) Haima cold seeps serve as a methane source to the atmosphere, with pronounced spatial heterogeneity in emission strength across the monitored regions. (2) The vertical distribution of methane is influenced by multiple environmental factors. Key factors in sediment porewaters include sediment depth, porosity, inorganic carbon (IC), chloride (Cl – ), and sulfate (SO 4 2– ), whereas silicate (SiO 3 2– ) and dissolved oxygen (DO) are primary regulators in the water column. (3) Sediments represent a significant methane source for bottom seawater, with methane consumption being more pronounced in seepage areas than in non-seepage areas. Discussion This study demonstrates that methane dynamics in the Haima cold seep are complex and driven by a combination of physical, chemical, and biological processes across the sediment–water interface. The identified key drivers underscore the importance of porewater geochemistry and water column biogeochemistry in controlling methane release. These findings significantly advance our understanding of methane transport in deep-sea seep systems and provide crucial insights for refining global methane flux estimates.

Preliminary Investigation on Marine Radar Oil Spill Monitoring Method Using YOLO Model - Bo Li; Jin Xu; Xinxiang Pan; Rong Chen; Long Ma; Jianchuan Yin; Zhiqiang Liao; Lilin Chu; Zhiqiang Zhao; Jingjing Lian; Haixia Wang (Journal of Marine Science and Engineering, 2023)
Due to the recent rapid growth of ocean oil development and transportation, the offshore oil spill risk accident probability has increased unevenly. The marine oil spill poses a great threat to the development of coastal cities. Therefore, effective and reliable technologies must be used to monitor oil spills to minimize disaster losses. Based on YOLO deep learning network, an automatic oil spill detection method was proposed. The experimental data preprocessing operations include noise reduction, gray adjustment, and local contrast enhancement. Then, real and synthetically generated marine radar oil spill images were used to make slice samples for training the model in the YOLOv5 network. The detection model can identify the effective oil spill monitoring region. Finally, an adaptive threshold was applied to extract the oil slicks in the effective oil spill monitoring regions. The YOLOv5 detection model generated had the advantage of high efficiency compared with existing methods. The offshore oil spill detection method proposed can support real-time and effective data for routine patrol inspection and accident emergency response.

Combined effect of Cu- and ZnO- NPs on antibiotic resistance genes in an estuarine water - Yu-ru Chen; Rong-rong Sha; Xiao-li Sun; Xing-pan Guo; Yi Yang (Frontiers in Marine Science, 2023)
Most studies of whether and how nanoparticles (NPs) affect antibiotic resistance genes (ARGs) focus on testing single NPs type. In this study, we determined the combined effect of Cu- and ZnO- NPs in the water samples collected from the Yangtze River Estuary and found the effect differs greatly from that produced by individual NPs. The results showed that the Cu- and ZnO- NPs co-exposure resulted in an enrichment of ARGs, whereas individual Cu- and ZnO- NPs exposure decreased the abundance of ARGs. Furthermore, the co-exposure of Cu- and ZnO- NPs induced obvious changes in the microbial communities compared to the control communities. Redundancy analysis suggested that the microbial community contributed the most (43.5%) to the ARG profiles, followed by dissolved metal ions (25.7%), MRGs, (19.4%), and MGEs (4.4%). Network analysis found several potential hosts (such as Mycobacterium and Escherichia coli ) and implied the extent of the risk of ARG transmission into various environmental niches by these common microbes.

Marine Radar Oil Spill Extraction Based on Texture Features and BP Neural Network - Rong Chen; Baozhu Jia; Long Ma; Jin Xu; Bo Li; Haixia Wang (Journal of Marine Science and Engineering, 2022)
Marine oil spills are one of the major threats to marine ecological safety, and the rapid identification of oil films is of great significance to the emergency response. Marine radar can provide data for marine oil spill detection; however, to date, it has not been commonly reported. Traditional marine radar oil spill research is mostly based on grayscale segmentation, and its accuracy depends entirely on the selection of the threshold. With the development of algorithm technology, marine radar oil spill extraction has gradually come to focus on artificial intelligence, and the study of oil spills based on machine learning has begun to develop. Based on X-band marine radar images collected from the Dalian 716 incident, this study used image texture features, the BP neural network classifier, and threshold segmentation for oil spill extraction. Firstly, the original image was pre-processed, to eliminate co-channel interference noise. Secondly, texture features were extracted and analyzed by the gray-level co-occurrence matrix (GLCM) and principal component analysis (PCA); then, the BP neural work was used to obtain the effective wave region. Finally, threshold segmentation was performed, to extract the marine oil slicks. The constructed BP neural network could achieve 93.75% classification accuracy, with the oil film remaining intact and the segmentation range being small; the extraction results were almost free of false positive targets, and the actual area of the oil film was calculated to be 42,629.12 m2. The method proposed in this paper can provide a reference for real-time monitoring of oil spill incidents.

Changes in amino acid and fatty acid composition during early development in cobia (Rachycentron canadum) - Jian-sheng Huang; Rong-xin Li; Rui-tao Xie; You-ming Chen; Jian-dong Zhang; Eric Amenyogbe; Gang Chen (Frontiers in Marine Science, 2022)
An estimation of the utilization of endogenous nutrients from the yolk sac that occurs during embryonic and early larval development can be a valuable approach to studying the nutritional requirements of fish larvae. In this study, fertilized eggs, embryos (before the membrane, 24 hours after fertilization), newly-hatched larvae (0-d-old), and open-mouthed larvae (3-day-old, unfed rotifers) samples of cobia ( Rachycentron canadum ) were collected to determine the amino acid and fatty acid profiles. Crude protein composition varies significantly for cobia during the different stages of development. The total amino acids, except for lysine(Lys), histidine (His), methionine(Met), serine(Ser), and glycine(Gly), had no significant change in the early development stage ( P > 0.05); the content of other six essential amino acids (EAA) and six non-essential amino acids (NEAA) was consistent with the changing trend of total essential amino acid. From hatching newly hatched larvae to open-mouthed larvae, except for Leu, Phe and Ser, decreased significantly ( P <0.05). From the utilization rate of FAA, the utilization rate of Lys and Leu was the highest (60.26%) and (52.21%) in the embryonic and endogenous nutritional stages, respectively. The water content of the open-mouthed larvae of cobia was significantly higher than that of the fertilized eggs, embryos, and newly hatched larvae ( P < 0.05). Three kinds of saturated fatty acids (SFA), five kinds of monounsaturated fatty acids (MUFA), and eight kinds of polyunsaturated fatty acids (PUFA) were detected in the dry samples of each developmental stage. Based on these results, juvenile cobia can thrive with a wide range of crude protein concentrations. Further refinement of commercial cobia production feeds would have beneficial consequences for economic and environmental concerns due to the positive impacts of optimizing the protein component as well as the ability to maintain the rapid growth rates. The results show that the larval development of cobia needs to consume large amounts of n3PUFA (especially DHA and EPA) to improve the larvae’s survival rate. Research methods will always have limitations when evaluating the relationship between early life nutrition interventions and well-being outcomes later in life. This study provides essential information regarding cobia larvae’s fatty acid requirements.

Sediment Resuspension as a Major Contributor to Sinking Particles in the Northwestern South China Sea: Evidence From Observations and Modeling - Lihua Ran; Wentao Ma; Martin G. Wiesner; Yuntao Wang; Jianfang Chen; Lanlan Zhang; Zhi Yang; Jingjing Zhang; Hongliang Li; Jian Ren; Rong Xiang; Erick Fredj (Frontiers in Marine Science, 2022)
The lateral advection of sinking particles is a well-known phenomenon in the South China Sea (SCS) and has a significant impact on the estimation of the efficiency of the biological carbon pump. However, little is known about the sources and pathways of sinking particles. Here, we present benthic and freshwater diatom fluxes and relative abundances collected by a sediment trap deployed at a water depth of 1,000 m and more than 500 m above the seafloor in the northwestern SCS, indicating that laterally transported resuspended sediment accounts for a significant part of the particle flux to the deep sea. A Lagrangian particle tracking model (LPTM) revealed that the resuspended particles likely originated from the neighboring continental slope, approximately 12–145 km to the west of the study site. Sediment trap observations and the LPTM together indicated that the impact of resuspended sediment occurred mainly in the deep water, and especially strong sediment resuspension was related to summer monsoon-induced coastal upwelling. The results suggest that particle resuspension has an important impact on the biological pump as well as on paleoenvironmental reconstructions of the SCS.