Sea surface cooling (SSC) is a direct manifestation of the upper-ocean response to tropical cyclones (TCs) and provides an important negative feedback on storm intensity. Therefore, understanding the mechanisms governing SSC is essential for advancing our understanding of TC–ocean interactions and improving the prediction of TC intensity. Super Typhoon Bolaven (2023), one of the strongest typhoons of that year, remained over the open ocean throughout its life cycle. Satellite observations show that only moderate cooling of about 2 °C occurred beneath the storm core despite extremely strong winds, relatively slow translation, and a sharp track turn. In contrast, cooling approaching 6 °C developed later in the midlatitude sector after Bolaven had entered its decay phase, indicating that the along-track cooling contrast cannot be explained by storm intensity, translation speed, or track geometry alone. High-resolution numerical simulations reproduce the observed cooling pattern and are used to diagnose the controlling mechanisms. The results show that SSC was primarily driven by vertical mixing, but its magnitude was strongly regulated by preexisting upper-ocean stratification and the vertical redistribution of wind-forced near-inertial energy. The pronounced midlatitude cooling was caused almost entirely by an extratropical cyclone that preceded Bolaven. Strong stratification in this region favored the projection of wind-forced energy onto higher baroclinic modes, trapping near-inertial energy in the upper ocean and sustaining enhanced mixing and delayed sea surface temperature (SST) recovery. By contrast, weaker stratification and a deeper mixed layer in the turning region favored downward radiation of near-inertial energy, reducing energy available for local upper-ocean mixing and limiting Bolaven-induced cooling. These results highlight the importance of along-track stratification variability in controlling open-ocean TC cooling and associated ocean feedbacks.
The Jianjiang River Estuary Sharp-pointed Clam National Aquatic Germplasm Resources Reserve, situated at the mouth of the Jianjiang River, features diverse estuarine habitats that may support a variety of aquatic organisms. To investigate the potential role of the estuary as a spawning and nursery ground for fish, this study provides the first assessment of ichthyoplankton species composition, abundance, and niche breadth in the area. Based on ecological surveys conducted in spring (April) and autumn (September) 2023, cluster analysis and redundancy analysis (RDA) were employed to explore community structure and its relationship with key environmental factors. A total of 504,930 fish eggs and 2878 larvae were collected during the spring and autumn 2023 surveys in the Jianjiang River Estuary (JRE). Using a combination of DNA barcoding and morphological identification, 30 ichthyoplankton taxa were identified, belonging to 24 genera, 20 families, and seven orders. Mean ichthyoplankton abundance was 4352.47 ind./100 m3 in spring, increasing to 44,126.59 ind./100 m3 in autumn. The autumn abundance was markedly higher than in spring. Across both seasons, ichthyoplankton abundance in the study area exceeded values reported for several other estuarine or coastal regions, suggesting that the protected area and adjacent waters may support important spawning and nursery functions during the survey periods. The dominant species in spring were Ambassis gymnocephalus, Stolephorus commersonnii, and Escualosa thoracata, whereas in autumn, A. gymnocephalus, Nibea soldado, Paraplagusia blochii, Nibea albiflora, and Sillago asiatica were dominant. Niche breadth analysis indicated that among the dominant spring species, A. gymnocephalus exhibited a narrow niche breadth (0.19), while S. commersonnii (0.51) and E. thoracata (0.47) had moderate niches. All dominant autumn species showed narrow niches (0.19–0.26). Cluster analysis grouped ichthyoplankton assemblages into three clusters in each season, with significant differences detected for some pairwise group comparisons (P < 0.05). Redundancy analysis identified sea surface temperature (SST) as a significant environmental variable associated with variation in ichthyoplankton community structure (P < 0.05). These findings provide a comprehensive assessment of ichthyoplankton species composition, abundance, and ecological niche breadth in the JRE, establishing an initial quantitative baseline for future ichthyoplankton monitoring, fisheries management, and conservation of potential spawning and nursery habitats within the protected area.
Patagonian grenadier (Macruronus magellanicus) is widely distributed around the austral zone of South America. Contrary to the South Atlantic, a large number of eggs and larvae have been observed in the Chilean Patagonia. The spatial and temporal stability of these spawning areas, however, has not been confirmed, nor have their environmental features been detailed. To characterize the spawning and nursery areas of M. magellanicus, we analyzed zooplankton samples and hydrographic data collected during winter and spring in the inner sea (inshore) and its adjacent continental shelf (offshore) of the Chilean Patagonia between 1995 and 2019. The results indicate that northern Chilean Patagonia is a key spawning and nursery area for this species. Peak spawning occurs in winter, most eggs are found offshore, and secondarily inshore, between 44°-46°S, whereas toward southern Patagonia, the limited spawning observed appears to occur within the inshore zone areas. A fraction of the spawn located offshore in the northern Patagonia enters the inshore areas and, as their larvae grow, they return to the offshore zone. A linear relationship was found between salinity and egg abundance, coinciding with a deeper vertical distribution, whereas a non-linear (dome-shaped) effect of temperature on larval abundance indicated a wider spatial distribution. Overall, both egg and larval abundances declined over the 25-year study period.
Small pelagic bonga shad (Ethmalosa. fimbriata) and demersal fish lesser African threadfin (Galeoides. decadactylus) are the major groups of commercial fisheries targeted by artisanal and industrial fleets in the Central Gulf of Guinea (CGG). These species account for 60–80% of the total marine fisheries landings in the CGG, and over 10 million people are dependent on the fisheries for sustainable livelihoods. However, accurate stock assessments for these species remain constrained by limited and inconsistent datasets. This study provides the first reliable stock assessment of bonga shad and lesser African threadfin (LATF) in the CGG using the surplus production model JABBA-Select. Catch (1990–2023) and CPUE (1990–2016) time-series data obtained from Fishery Committee for the Eastern Central Atlantic (CECAF) were analysed using Markov chain Monte Carlo (MCMC) estimation, convergence diagnostics, and sensitivity scenarios to evaluate parameter uncertainty and model robustness. JABBA-Select produced well-behaved posterior distributions and consistent retrospective patterns, indicating adequate model fit. For bonga shad, the current biomass rate (SB2023/SBMSY) was 1.60 (CI:0.6, 2.3) and exploitation rate (H2023/HMSY) was 0.40 (CI:0.5–1.77) suggesting the stock is healthy, with a 92.7% probability of the stock being underfished (in the green quadrant of the Kobe plot). In contrast, LATF is overfished, SB2023/SBMSY was 0.70 (CI:0.30, 1.7); H2023/HMSY = was 1.60 (CI:0.5, 4.7), with 66.5% probability of the stock being overfished (in the red quadrant of the Kobe plot) Stock trajectories indicate declining trends, with LATF exhibiting greater vulnerability in fishing pressure. Future projections (10-years) indicate that bonga shad yields should remain below 180,000 t, whereas LATF catches should remain below 7000 t to reduce depletion risk. These findings highlight the need for reduced fishing pressure, strengthened monitoring, and seasonal closures, particularly for LATF. This study demonstrates the effectiveness of JABBA-Select for data-poor tropical fisheries and provides scientific reference points for sustainable management in the CGG.
Stable isotopes, particularly δ13C and δ15N, are widely used in ecological research to infer trophic interactions, energy flow, and resource use. However, preservation methods can introduce biases in isotopic measurements that complicate interpretation. The study quantifies the effects of freezing, oven-drying, repeated freezing and thawing cycles and ethanol preservation on δ13C and δ15N values of six marine taxa spanning Osteichthyes, Elasmobranchia, Cephalopoda, and Crustacea, over a 24-month period. The isotopic changes exhibited variability in accordance with the preservation method, duration, and taxon. Short-term freezing (5 days) and repeated freeze–thaw cycles caused minimal isotopic changes. In contrast, ethanol preservation (12 months) and long-term freezing (24 months) generated consistent and significant changes in both isotopic values across taxa. Δ values were computed relative to pooled control samples to isolate treatment effects from interspecific baseline differences. The application of these methods resulted in an increase in the δ13C and δ15N values by approximately 0.2–1.9‰ and up to 2.3‰, respectively. δ13C responses were more variable across taxa, highlighting challenges in interpreting carbon-based metrics in samples stored for extended periods or preserved in ethanol. Overall, the results show that preservation-induced isotopic shifts are strongly method-dependent and can be large enough to influence ecological interpretation. Careful selection of preservation protocols, and explicit consideration of their potential biases, is therefore essential for generating reliable stable isotope data in marine ecological research.
A thorough understanding of the planktonic food-web functioning is crucial for determining the origin of organic matter that sustains the broader ecosystem, particularly in environments exposed to intense anthropogenic and environmental pressures. This study builds on highly resolved data, enabling an exceptionally detailed representation of the planktonic food web by integrating both the taxonomic and functional diversity of plankton. Using Linear Inverse Modeling coupled with a Markov Chain Monte Carlo approach (LIM–MCMC), we reconstructed the food-web structure during spring and fall in three stations in the Gulf of Gabès, each subjected to varying levels of anthropogenic pressure. Ecological network analysis (ENA) indices were used to describe the emerging properties of each food web, and were compared between stations. Based on the phytoplankton size and diversity, three planktonic food webs (PFW) with different functional ENA indices were determined, hence indicating differently functioning systems. In spring, multivorous and herbivorous pathways were dominant and mainly relied on primary production of large phytoplankton (mainly >10 μm micro-sized diatoms). In fall, the microbial food-web dominated at one station characterized by an intense proliferation of picoprokaryotes (i.e. < 2 μm Synechococcus), providing very high primary production, while herbivorous pathways, supported by large phytoplankton production, prevailed in the others stations. The trophic models, revealed that dinoflagellates were very active with high herbivory and microbivory in the different food webs, suggesting their important role in supplying carbon to higher consumers. Trophic transfer was high in all food webs (22–46% of primary production), particularly via the herbivorous pathway that was characterized by high production of large phytoplankton, intense proliferation of dinoflagellates and high herbivory of mesozooplankton, indicating the efficiency of large phytoplankton-dinoflagellates-mesozooplankton interaction in terms of biogenic carbon transfer. ENA indices revealed that the microbial food web, which had the highest total system throughput and the highest capacity of carbon cycling and retention, was the most active and stable system and relied partly on detrital energy. In opposite, the herbivorous food webs, present at the stations that were exposed to higher chemical pollution, showed the lowest total system flux and cycling, low relative ascendancy and average mutual information features that collectively point to limited activity, weak organization, and low stability. This study showed that trait-based models are suitable to describe detailed processes within carbon transfer pathways. These models combined with ecological indices are effective tools for management and assessment of disturbed marine ecosystems.
Marine primary-production equations can be analysed as physical input–output functions using production-theory measures, without assuming phytoplankton optimization. From canonical bio-optical and mixed-layer terms we derive marginal products, elasticities, isoquant slopes, a self-shading correction, and a light–nutrient compensation threshold. The threshold is the nutrient gain per metre of deepening required to offset the light-related loss in average production; temperature and micronutrients enter the general differential as separate controls. A matched Bermuda Atlantic Time-series Study (BATS) profile panel illustrates the calculations. Profile-date fixed effects imply a net apparent depth coefficient of −0.0263m−1; 2037 adjacent-depth intervals give an observed log-production gradient of −0.0264m−1. On 239 nitrate＋nitrite-matched intervals, ΔϕN/Δz=+0.00419m−1; its local Monod conversion at N=Nk=0.5μmol kg-1 is ΔlogϕN/Δz≈+0.0084m−1. These are profile diagnostics, not a physiological calibration or a dynamic threshold test.
After the first two explorations in 2007 and 2009, the Carlsberg Ridge was revisited in 2021 to re-explore the previously identified hydrothermal plumes and to ascertain active vent sources around that area. During the present survey, at site 1 (3.69°N, 63.83°E; depth: 2900–3200 m) and site 2 (3.70°N, 63.66°E; depth: 3100–3300 m), prominent optical anomalies and enrichments of dissolved and particulate metals (Mn, Co, Cu, Cd) in water columns were traced and confirmed the existence of a chronic non-buoyant plume in that area. The intense plume signatures at stations CTD09 (of site 1) and CTD05 (of site 2) suggest that both sampling locations lie in the vicinity of active hydrothermal vent field(s). However, the spatial variability of dissolved Mn (12 to 20 times of ambient seawater) and dissolved Co (3.2 to 8.0 times of seawater) with distance indicated significant plume dilution across that area. It was noticed that most of the analysed metals were partitioned more towards particulate phases, but interestingly, the relative fractionation of different metals between dissolved and particulate phases differed significantly. Within the plumes, Mn, due to its quasi-conservative nature, was mainly present in the dissolved phase, Ni did not fractionate much, while Co, Cu, and Cd were mostly in the particulate fraction, which, with increasing dilution and lack of scavenging/ precipitating conditions, showed dominance in the dissolved phase. Such studies are important to understand the metal behaviour in a dispersing hydrothermal plume environment.
For many large estuary systems, timely and accurate projection of water quality is urgently needed; yet it is challenging due to the complex conditions and limited observation capabilities. The Pearl River Estuary (PRE) is a typical example, which is degraded by excessive inorganic nitrogen (IN) and reactive phosphate (RP). Existing methods (numerical model and data-driven machine learning) struggle to simultaneously achieve accuracy, efficiency, and interpretability. Therefore, this study establishes an explainable machine learning framework to obtain the spatiotemporal variation of water quality and the coverage rate of good water quality (Aq, defined by the portion of water quality classes I and II area, from the national standard of China). A model interpretation method (SHapley Additive exPlanations, SHAP) is applied to identify the key variables and provide a deeper understanding of the estuarine water quality dynamics. The framework uses a multi-layer perceptron as the core model and sea surface salinity as a key proxy of the estuarine dynamics from a previously developed machine learning model, with riverine pollutant fluxes from a random forest model, pollutant loads from empirical estimations, and invariant variables (water depth and geographic information). Due to limited in-situ observations, a transfer learning strategy is applied: the framework is pre-trained with numerical simulation data and then fine-tuned with observations. Validation shows good performance of the model prediction (86.8%/80.76% accuracy for IN/RP prediction). Using downscaled climate projections, the framework predicts an improvement in PRE water quality from 2023 to 2029 (with annual averaged Aq rising from 62.52% to 74.24%), followed by a decline in 2030 (64.50%). SHAP analysis demonstrates that prediction results can be explained by estuarine dynamics and pollution scene, providing a useful tool for local estuarine science-based environmental management. All the variables represent characteristics common to estuaries, so the developed framework has the potential for application across other estuarine systems, thereby supporting their utilization and management.
The continuous and increasing anthropogenic activity creates a multitude of waste and discharges, much of which ends up in the sea. Among the most important pollutants there are heavy metals (Pb, Cr, Cd, Hg, etc.), which can cause great degradation of the environment. In order to get an overview of the pollution present in the marine environment, bioindicators such as mussels are used. In this work, the effect of individual size and transplantation between three ports in Asturias (Spain) with different heavy metals average concentrations was evaluated using Mytilus galloprovincialis as a bioindicator. Results show the effect of size in tissue metal concentrations, among other potential factors such as reproductive season or condition. In addition, pre-conditioning of the local population to average concentration was also significant, stressing the importance of using local populations to measure responses.
We developed a habitat suitability index (HSI) model for predicting the fishery potential and future climate-change-related habitat shifts for dolphinfish (Coryphaena hippurus) in the Western Pacific Ocean. We collected data on oceanographic variables, including sea surface temperature (SST), sea surface salinity (SSS), sea surface height (SSH), mixed layer depth (MLD), sea surface chlorophyll-a concentration (SSC), sea surface dissolved oxygen (OXG), and eddy kinetic energy (EKE), and fishery data from Taiwanese dolphinfish longline vessels for the 2017–2020 period. With satellite-derived remotely sensed oceanographic data becoming increasingly available, HSI models may prove useful for evaluating potential changes in habitat suitability caused by oceanographic phenomena and for providing scientific advice for management. We initially constructed arithmetic mean model (AMM)- and geometric mean model (GMM)-based HSI models and assessed them according to the lowest Akaike information criterion (AIC). We eventually selected the AMM-based model (AIC value: −15.12 for AMM vs. −13.93 for GMM). The suitable SST, SSS, SSH, MLD, SSC, OXG, and EKE ranges for dolphinfish habitats were 26 °C–29.5 °C, 34–34.4 PSU, 0.43–0.84 m, 6–26 m, 0.08–0.32 mgm−3, 200–212 mmolm−3, and 0.09–0.7 m2s−2, respectively. Temporal habitat persistence analysis revealed consistently high suitability zones closely aligned with observed standardized catch per unit effort (SCPUE) trends, confirming the model's utility as a proxy for fishing opportunity. Mid-century (2050) projections revealed that suitable dolphinfish habitats shifted southward under future climate scenarios, with the most pronounced shift occurring under the lower-emission Representative Concentration Pathway (RCP) 2.6 scenario. However, late-century (2100) projections indicated a northward shift in suitable habitats, particularly under the higher-emission RCP 8.5 scenario. These shifts highlight the need for climate-resilient, adaptive fishery management strategies that can inform future conservation efforts and facilitate habitat management for enhanced ecological monitoring.
Tropical cyclones (TCs) are one of the most extreme weather events, and the Bay of Bengal (BoB) in the North Indian Ocean experiences multiple intense TCs every year. Although a decreasing trend of yearly TC frequency was previously observed over the BoB, the mean intensification tendency has enhanced. The current study investigated the spatiotemporal variability of cyclogenesis locations and the evolution of five TC-influencing geophysical parameters in the basin during the period 1983–2023. Three distinct clusters could be identified in the BoB using K-means clustering while evaluating the spatial evolution of cyclogenesis locations. Further, a shift in dominant cyclogenesis locations towards the northern BoB was observed since 2005. Temporal analysis of geophysical variability, as investigated by Empirical Orthogonal Function (EOF) and random forest regression techniques, revealed vertical wind shear to influence the northward shift in cyclogenesis over the basin. Moreover, analysis of the environmental steering flow revealed a weakening of mid-tropospheric westerly circulation during the 2005–2023 period, compared to the 1983–2004 period. This would mean lesser north-east recurvature of storm tracks and more TC translation towards Indian coastline in the northwest of BoB. Consequently, landfall events were observed to have increased over coastal cities north of Visakhapatnam in India since 2005, as estimated from analysing landfall events over the eastern coastal regions of India. Additionally, the number of high-intensity TC landfalls was also found to have increased over the northern part of the eastern coastline, rendering the coastal population in the region more vulnerable to TC-related hazards.
Summer filamentous cyanobacterial blooms strongly influence the biogeochemistry of the Baltic Sea. In surface water, they sustain organic matter (OM) production via N2 fixation despite the depletion of dissolved inorganic nitrogen (DIN). In deeper water, remineralization of this OM contributes to O2 depletion and H2S formation, thereby promoting Baltic Sea hypoxia/anoxia. Primary production by cyanobacteria also drives a characteristic summer drawdown of total dissolved CO2 (CT). While this biogeochemical signal is thought to reflect N2 fixation, direct observational evidence supporting this link remains limited. In addition, key questions remain regarding the factors regulating bloom initiation and intensity.This study applied a multi-method approach, combining continuous high-resolution surface water measurements of biogeochemical and biological variables made from the ship of opportunity Finnmaid traveling between Travemünde (Germany) and Helsinki (Finland), with modeled physical parameters, to investigate a cyanobacterial hotspot identified in summer 2023. During the 2.5-week CT drawdown (∼1500 to ∼1325 μmol/kg) in June, at the entrance to the Gulf of Finland, 70% of the decrease occurred in the final five days and coincided with a sharp increase in filamentous cyanobacterial biomass and pronounced N2 undersaturation. Our observations indicate that once the cyanobacterial biomass has been accumulated during favorable environmental conditions, their impacts can be drastic to the carbon system. Our results link N2 fixation with the CT decline in surface water, while also demonstrating that ecosystem productivity is enhanced by co-occurring phytoplankton species, which likely benefit from the nitrogen released by cyanobacterial N2 fixation.
The Western Antarctic Peninsula is a key area in the Southern Ocean ecosystem. Dense microalgal communities not only support diverse wildlife, but can also exert a climatic influence through CO2-uptake and the emission of climate-active gases like dimethylsulfide. The build-up of biomass is driven by high rates of primary production. In this paper, data are presented on primary production in Ryder Bay, a biologically-rich coastal area. Primary production was measured by means of 13C-uptake, in spring and summertime between 2012 and 2022. Production rates were linked to algal community composition and oceanographic data collected at the site of the Rothera Time Series. To get more detailed information on species-specific production rates, specific algal growth rates were obtained from laboratory studies and historical data. In Ryder Bay, primary production rates were 0.025 (± 0.024) mg C l−1 h−1 on average across all studies, and highest in February 2017. In spring, production was dominated by haptophyte algae with a low temperature optimum. Diatoms with higher growth rates and a higher temperature optimum thrive later in summer. For the near future, our data support the predictions that the warming of surface waters will stimulate algal growth rates, which will result in increased primary production. On longer timescales, ongoing ocean warming is expected to have strong negative effects on the occurrence of haptophytes like Phaeocystis antarctica. For polar diatoms, a temperature growth optimum may be passed. A potential shift in species composition is predicted, with ensuing consequences for primary production and biogeochemical cycles.
Submesoscale eddies (SMEs) are critical for oceanic energy dynamics and nutrient transport. This study explores the potential generation mechanisms, temporal and spatial variability of SMEs, over a period of 11 years (2012 to 2022), in a wide continental shelf with a gentle slope and bathymetric terraces in the Southwestern Atlantic Ocean, the Argentine Continental Shelf. The analysis revealed space and time patterns of SMEs, with a notable increase in activity during colder months (autumn and winter) and a predominance of cyclonic structures over anticyclonic ones. Regions with high tidal energy dissipation, upwelling mechanisms, and frontal systems were identified as hotspots of SMEs occurrences. Moreover, cyclonic eddies were found to follow a tidal front’s seasonal migration pattern. Satellite-detected eddies exhibit predominantly elliptical shapes, suggesting the influence of horizontal shear and interactions with topographic interactions. Furthermore, over 96 % of the detected cyclonic and anticyclonic eddies have radii below the baroclinic Rossby radius of deformation, highlighting their small-scale nature (mostly under 12 km equivalent radius). This research provides a framework for future studies on SMEs in marine ecosystems, improving our understanding of their role in ocean dynamics and fisheries productivity.
Effective marine ecosystem management requires a thorough understanding of ecological energy and material dynamics across multiple regions and timescales, as well as identifying factors that contribute to phytoplankton biomass variation in each region. This study used coupled physical-biogeochemical ocean model simulation results to identify the three-dimensional ecological regions and to understand spatiotemporal variations of driving factors for region-specific phytoplankton biomass in the Yellow Sea. The most pronounced spatial gradient of chlorophyll-a concentration was identified across both the tidal front and the thermocline. Five distinct ecological regions were identified, each separated by typical oceanographic boundaries: the surface layer (0–15 m), the subsurface chlorophyll maximum layer (15–30 m), the deep layer of offshore waters (> 30 m), the eastern coastal region, and the western coastal region. The key findings of this study include: (1) defining three-dimensional ecological regions in the Yellow Sea, delimited by invisible oceanographic boundaries such as tidal mixing fronts and the thermocline, and (2) identifying specific physical, chemical, and biological driving factors contributing to region-specific seasonal variations in chlorophyll-a concentration.
The Arctic gastropod fauna is dominated by species with broad Atlantic, Pacific, or circum-Arctic distributions, and endemics restricted to local regions are considered rare. Recent sampling at methane seeps in the Laptev Sea at 70–72 m depth revealed a new rissoid gastropod, Frigidoalvania krylovae sp. nov., the first confirmed seep-specialized member of the family Rissoidae in the Arctic. We describe this species based on shell, radular, and reproductive morphology, and assess its phylogenetic position using newly generated 16S and 28S rRNA sequences. F. krylovae is morphologically distinct from all described congeners and occurs exclusively within bacterial mat habitats at the single seep site, with stable isotope signatures indicating partial reliance on chemosynthetically derived organic matter. Phylogenetic analyses place Frigidoalvania krylovae in a clade distinct from Frigidoalvania cruenta, which affiliates with a Pacific-derived lineage. These results indicate that Arctic Frigidoalvania are polyphyletic, reflecting multiple independent colonizations from the Atlantic and Pacific. Our findings highlight methane seeps as potential hotspots of Arctic endemism and underscore the need for broader taxon sampling to resolve rissoid systematics in high-latitude seas.
