All vertebrates have a definitive thyroid gland, or thyroid for short. As a critical organ for growth, development and metabolism, its origin and evolution have long received attention. On the basis of anatomical position, endodermal origination and histological features, the endostyle of amphioxus has been proposed as a homologue to the thyroid of vertebrates. This homology is further supported by the findings that the amphioxus endostyle abounds in thyroid hormones, possesses several thyroid-specific proteins such as thyroperoxidase, nicotinamide adenine dinucleotide phosphate (NADPH) oxidase and thyroglobulin, and expresses the thyroid-related transcription factors involved in the regulation of development of the vertebrate thyroid, including Nkx2.1, FoxE4 and Pax2/5/8. Importantly, our study on functionality, together with others, indicates significant similarities between the amphioxus endostyle and the vertebrate thyroid gland. Moreover, we show that the production of thyroid hormones by the amphioxus endostyle is mediated in a fashion similar to that of the vertebrate thyroid. These provide solid evidences that the amphioxus endostyle is the homologue of the vertebrate thyroid. From a phylogenetic viewpoint, we propose that the hypobranchial ridge, or endostyle-like structure, of hemichordates is the most primitive forerunner of the thyroid, from which the vertebrate thyroid is formed through the transformation of non-follicular endostyle of amphioxus to follicular endocrine organ of vertebrates. We also raise a couple of questions that demand further study.

Microsatellite markers with polymorphic advantages are widely used in the exploration and utilization of marine fishery resources. In this study, 16 polymorphic microsatellite markers were used to evaluate the diversity and population structure of Setipinna tenuifilis, a nearshore fish of economic and ecological value in the western Pacific Ocean and Indian Ocean. The genetic diversity of S. tenuifilis showed a high level [mean N _a (number of alleles) is 23.25, mean H _o (observed heterozygosity) is 0.639, mean R _a (allelic richness) is 11.625, and the polymorphic information content (PIC) is 0.844] similar to other Clupeiformes fish species. The nine wild S. tenuifilis populations showed significant differentiation (F _ST ranging from 0.00384 to 0.19346) and were generally divided into southern and northern populations based on genetic structure, except for the Zhoushan population, which exhibited genetic mixture. Our results provide fundamental but significant genetic insights for the management and conservation of S. tenuifilis fishery resources.

Scientific and precise evaluations of the megafaunal and landform characteristics of seamounts are important guides for their protection and study. A series of manned and unmanned submersibles have provided invaluable observational imaging data for the ecological study of seamounts. However, traditional methods of artificial observation of seamount imaging data cannot accurately and efficiently determine the characteristics of megafauna and landforms. This research harnesses data-driven technology to systematically investigate the distributional traits and morphological features of megafaunal organisms, as well as the topographical characteristics, in the Caiwei Guyot region of the western Pacific’s Magellan Seamounts. To construct the landform and megafauna dataset of the Caiwei Guyot region, we used a data preprocessing technology based on image enhancement to provide high-quality imaging data for data-driven technologies. A megafaunal identification and counting algorithm based on YOLOv5 (You Only Look Once Version 5) was developed to efficiently assess the abundance, variety, and dominant species of megafauna. Simultaneously, a landform three-dimensional (3D) reconstruction algorithm based on PatchmatchNet was developed to reconstruct the 3D form of the terrain accurately. This study pioneers the application of data-driven technology to deep-sea imaging within the Caiwei Guyot region, offering an innovative approach to accurately and efficiently characterize the region’s unique megafauna and landforms.

We introduce a new method, the piecewise Reynolds mean (PREM), for decomposing the flow velocity into the mean-flow and eddy-flow parts in the time domain for subsequent calculation of the mean flow kinetic energy (MKE) and eddy kinetic energy (EKE). Compared with conventional methods like the Reynolds mean and running mean (RUM), PREM has the advantage of exact balance between the MKE and EKE, without the additional residual kinetic energy (RKE), while retaining time-dependent mean-flow. It is mathematically simple and computationally lightweight, depending on a pre-defined separation scale for the mean-flow and eddies. Based on satellite observations and the separation scale of 1 year, we compare PREM with RUM, as well as another newly proposed method, the eddy detection and extraction (EDEX). The latter is based on objective identification of mesoscale eddies and eddy anomaly extraction algorithms, and is therefore only suitable for mesoscale eddy energetics, but independent of separation scales. It is shown that compared with RUM, PREM gives larger mean EKE and stronger interannual variability. In strong-current and eddy-rich regions, the two methods differ the most (max: Kuroshio Extension, root-mean-sqaure-difference = 60.3 J/m³); but in areas with weak current and eddy, the difference accounts for the largest fraction of total EKE (max: south of the Aleutian Islands, 208%). EKE estimated by the two methods is out of phase (min correlation coefficient = 0.38). The mean EKE and standard deviation from the EDEX method resemble the PREM with 1-year separation scale, but is generally smaller in magnitude.

Accurate significant wave height (SWH) prediction is essential for the development and utilization of wave energy. Deep learning methods such as recurrent and convolutional neural networks have achieved good results in SWH forecasting. However, these methods do not adapt well to dynamic seasonal variations in wave data. In this study, we propose a novel method—the spatiotemporal dynamic graph (STDG) neural network. This method predicts the SWH of multiple nodes based on dynamic graph modeling and multi-characteristic fusion. First, considering the dynamic seasonal variations in the wave direction over time, the network models wave dynamic spatial dependencies from long- and short-term pattern perspectives. Second, to correlate multiple characteristics with SWH, the network introduces a cross-characteristic transformer to effectively fuse multiple characteristics. Finally, we conducted experiments on two datasets from the South China Sea and East China Sea to validate the proposed method and compared it with five prediction methods in the three categories. The experimental results show that the proposed method achieves the best performance at all predictive scales and has greater advantages for extreme value prediction. Furthermore, an analysis of the dynamic graph shows that the proposed method captures the seasonal variation mechanism of the waves.

Over the past two decades, numerous countries have actively participated in the International Argo Program, working toward the global “OneArgo” goal. China’s Argo program has deployed over 500 autonomous profiling floats in the Indo-Pacific, with 55 Beidou (BD) floats, equipped with the Beidou satellite communication system, currently operational. During the operation of the BD float network, we found that in addition to the limitation of floats battery, the loss may also be caused by communication loss due to the floats escaping from the Beidou-2’s short message coverage. In this study, float trajectories are simulated using velocity fields from an eddy-resolved resolution Estimating the Circulation and Climate of the Ocean, Phase Ⅱ (ECCO2) model and a Lagrangian particle tracking model programmed to represent the vertical motions of profiling floats. The simulations can help to explore both the representativeness and the predictability of profiling float displacements. By deploying a large number of synthetic floats in the Lagrangian particle tracking system, we construct probability density functions (PDFs) of the simulated-float trajectory among key oceans, for example, a joint region of East Indian−South China Sea−Northwest Pacific Ocean (5°–40°N, 70°–140°E), which is generally similar to the location of the present BD float network. These statistics can help to estimate the chance of floats drifting into shallow seas (such as the East China Sea) and out of the coverage of the Beidou satellite communication. With this knowledge changes to the future China’s Argo observing system could be made.

We investigated dissolved iodine species in seawater from the northern South China Sea Shelf. Iodide concentrations were determined by cathodic stripping square wave voltammetry, and iodate was measured by spectrophotometry. Dissolved organic iodine (DOI) was measured with reference to reduced iodide. R-TDI (R-X or rationalized-X is the concentration of X normalized to a salinity of 35, TDI represents total dissolved iodine) was in the range of 0.43–0.46 µmol/L, showing a relatively conservative behavior, while iodate, iodide, and DOI showed non-conservative behaviors. Distribution characteristics in the surface waters showed R-iodate values in the 0.28–0.32 µmol/L range and an offshore>inshore trend, while R-iodide was in the 0.11–0.19 µmol/L range and R-DOI in the 0–0.07 µmol/L range, reflecting an inshore>offshore trend for both. The vertical distribution showed the highest R-iodide concentrations in the surface waters and decreased values with depth, reaching less than 0.01 µmol/L at depths>200 m. R-iodate increased with depth with a measured peak value of 0.43 µmol/L. Seawater with high iodate/iodide ratio (up to 2.9) was found in the central upwelling region and gradually decreased to 2.0 far from this center. The relationship between R-iodide and R-iodate among all samples followed the 1:1 relationship with a slope slightly less than 1, indicating that the conversion between iodate and iodide species could not account for the observed changes. This finding also suggests that DOI may be an important participant in the mass balance. A box model was applied to calculate the input and output of iodine species, and the result showed that approximately 8% of iodate (1.50 × 10⁸ mol/a) imported to the shelf sea was reduced. Concomitantly, the amount of iodide and DOI produced in the shelf amounted to 1.07 × 10⁸ mol/a, roughly 14% higher than the input iodide.

Aquaculture, as the fastest-growing food production sector in the world, is becoming an increasingly nonnegligible source of greenhouse gas emissions. Despite this, there has been limited research on nitrous oxide (N₂O) emission from marine aquaculture in China, where more marine aquaculture occurs than anywhere else, globally. We estimated N₂O emissions (E) from marine mariculture of 10 fish and 6 crustacean species in China from 2003 to 2022 using production data from the China Fishery Statistical Yearbook (2004–2023), and data for feed conversion rates and types from the literature. From 2003, marine aquaculture production, the annual N₂O emissions (E_A), and the annual N₂O emissions per unit of aquaculture area (EI_A) trend upward. The E_A of fish culture was lower than that of crustaceans, but the EI_A of fish culture was generally higher. Sea bass (0.308 Tg/a, in terms of N) and white shrimp (0.945 Tg/a, in terms of N) had the highest average E_A among fish and crustacean cultures, respectively. The highest average E_A from fish and crustacean were both Guangdong Province (fish: 0.248 Tg, crustacean: 0.547 Tg), and the highest sea area were both the South China Sea (fish: 0.316 Tg, crustacean: 1.082 Tg); the highest average EI_A for fish and crustacean were Tianjin City [35.40 t/(hm²·a)] and Guangxi Zhuang Autonomous Region [19.83 t/(hm²·a)], respectively, and the highest sea areas were both the South China Sea (fish: 0.316 Tg, crustacean: 1.082 Tg). These analyses provide baseline data for a greenhouse gas emissions inventory for China, based on an interpretation of them, we provide recommendations for reducing N₂O emissions in marine fish and crustacean culture.

Particle size is an important characteristic of suspended matter, and it contains crucial information about the deposition process. Suspended particle samples in the water mixing zone of the Changjiang River Estuary were collected in December 2016. Untreated original grain size and the decentralized grain size of the suspended particles were measured via a laser particle size analyzer. Morphological characteristics and the chemical composition of the suspended particles were also studied systematically using a scanning electron microscope (SEM) with an energy dispersive X-ray spectrometer (EDS). Then, the flocculation and sedimentation of suspended matter in the water mixing zone were explored by combining them with the water mixing processes in the estuary. The average particle size of suspended matter in the mixing zone of the Changjiang River Estuary ranges from Ф5.73 to Ф7.98. The particle size distribution pattern is an abnormal model with a mainly unimodal pattern. In the freshwater area that was dominated by runoff, the suspended matter is mainly composed of fine particles, the settling velocity is slow, and the flocculation is weak. Floc particles were often seen in the mixing zone, with the flocs having a relatively large particle size, a low density and a loose structure appearing at the weak mixing zone; the flocs had a compacted structure in most areas of the mixing zone. The changes of suspended particle size in the estuarine mixing zone promote the settling and deposition of suspended matter, which has an important influence on the bed geomorphology and preservation of the fine suspended particles in the estuary.

The lanternfishes are mesopelagic fish that are highly productive as common bycatch of deep-sea shrimp trawlers, but they are often neglected or discarded. Despite being one of the dominant lanternfish species in the Arabian Sea, little is known about the life history of Diaphus thiollierei and its role in marine ecosystems. In this study, 103 D. thiollierei were collected in the Arabian Sea during October-November 2020 to study population growth based on sagittal otolith daily ages; and 10 fish collected during April–May 2021 were subjected to otolith microchemistry analysis to reconstruct the vertical migration in their life history using LA-ICP-MS technique. The standard length–dry weight (SL-DW) relationships for D. thiollierei revealed both negative allometric growth and a significant difference between the sexes. Using daily growth annuli counts on the sagittal section of otoliths, the von Bertalanffy growth equation for D. thiollierei was determined. The pattern of four elemental ratios (Sr to Ca, Mg to Ca, Li to Ca, and Ba to Ca) in sagittal otolith suggested that, in general, D. thiollierei descended continually after hatching until the post-larval (PL) stage when they reached a depth of approximately 200 m. Subsequently, from the PL stage to the post-metamorphosis Ⅱ (PM Ⅱ) stage, D. thiollierei likely further sank from 200 m to a depth of approximately 300 m, and then in the daytime they were at a depth of approximately 300–800 m to take refuge from predators. This pilot study explored to unravel the vertical migration during life history in D. thiollierei from sagittal otoliths, whereas further investigation on otolith is needed to better delineate the population ecology in detail, and thus to provide basic information for the exploitation of the lanternfish resource and the understanding of their ecological roles.