A comparison study on structure-function relationship of polysaccharides obtained from sea buckthorn berries using different methods:antioxidant and bile acid-binding capacity

In this study,the structural characters,antioxidant activities and bile acid-binding ability of sea buckthorn polysaccharides(HRPs)obtained by the commonly used hot water(HRP-W),pressurized hot water(HRP-H),ultrasonic(HRP-U),acid(HRP-C)and alkali(HRP-A)assisted extraction methods were investigated.The results demonstrated that extraction methods had significant effects on extraction yield,monosaccharide composition,molecular weight,particle size,triple-helical structure,and surface morphology of HRPs except for the major linkage bands.Thermogravimetric analysis showed that HRP-U with filamentous reticular microstructure exhibited better thermal stability.The HRP-A with the lowest molecular weight and highest arabinose content possessed the best antioxidant activities.Moreover,the rheological analysis indicated that HRPs with higher galacturonic acid content and molecular weight showed higher viscosity and stronger crosslinking network(HRP-C,HRP-W and HRP-U),which exhibited stronger bile acid binding capacity.The present findings provide scientific evidence in the preparation technology of sea buckthorn polysaccharides with good antioxidant and bile acid binding capacity which are related to the structure affected by the extraction methods.

Influence of Irregular Coastlines on a Tornadic Mesovortex in the Pearl River Delta during the Monsoon Season. Part Ⅰ:Pre-storm Environment and Storm Evolution

The Pearl River Delta(PRD),a tornado hotspot,forms a distinct trumpet-shaped coastline that concaves toward the South China Sea.During the summer monsoon season,low-level southwesterlies over the PRD’s sea surface tend to be turned toward the west coast,constituting a convergent wind field along with the landward-side southwesterlies,which influences regional convective weather.This two-part study explores the roles of this unique land–sea contrast of the trumpet-shaped coastline in the formation of a tornadic mesovortex within monsoonal flows in this region.Part I primarily presents observational analyses of pre-storm environments and storm evolutions.The rotating storm developed in a lowshear environment(not ideal for a supercell)under the interactions of three air masses under the influence of the land–sea contrast,monsoon,and storm cold outflows.This intersection zone(or“triple point”)is typically characterized by local enhancements of ambient vertical vorticity and convergence.Based on a rapid-scan X-band phased-array radar,finger-like echoes were recognized shortly after the gust front intruded on the triple point.Developed over the triple point,they rapidly wrapped up with a well-defined low-level mesovortex.It is thus presumed that the triple point may have played roles in the mesovortex genesis,which will be demonstrated in Part II with multiple sensitivity numerical simulations.The findings also suggest that when storms pass over the boundary intersection zone in the PRD,the expected possibility of a rotating storm occurring is relatively high,even in a low-shear environment.Improved knowledge of such environments provides additional guidance to assess the regional tornado risk.

Assessments of Data-Driven Deep Learning Models on One-Month Predictions of Pan-Arctic Sea Ice Thickness

In recent years,deep learning methods have gradually been applied to prediction tasks related to Arctic sea ice concentration,but relatively little research has been conducted for larger spatial and temporal scales,mainly due to the limited time coverage of observations and reanalysis data.Meanwhile,deep learning predictions of sea ice thickness(SIT)have yet to receive ample attention.In this study,two data-driven deep learning(DL)models are built based on the ConvLSTM and fully convolutional U-net(FC-Unet)algorithms and trained using CMIP6 historical simulations for transfer learning and fine-tuned using reanalysis/observations.These models enable monthly predictions of Arctic SIT without considering the complex physical processes involved.Through comprehensive assessments of prediction skills by season and region,the results suggest that using a broader set of CMIP6 data for transfer learning,as well as incorporating multiple climate variables as predictors,contribute to better prediction results,although both DL models can effectively predict the spatiotemporal features of SIT anomalies.Regarding the predicted SIT anomalies of the FC-Unet model,the spatial correlations with reanalysis reach an average level of 89%over all months,while the temporal anomaly correlation coefficients are close to unity in most cases.The models also demonstrate robust performances in predicting SIT and SIE during extreme events.The effectiveness and reliability of the proposed deep transfer learning models in predicting Arctic SIT can facilitate more accurate pan-Arctic predictions,aiding climate change research and real-time business applications.

Arctic Sea Ice Variations in the First Half of the 20th Century:A New Reconstruction Based on Hydrometeorological Data

The shrinking Arctic sea-ice area(SIA) in recent decades is a striking manifestation of the ongoing climate change.Variations of the Arctic sea ice have been continuously observed by satellites since 1979, relatively well monitored since the 1950s, but are highly uncertain in the earlier period due to a lack of observations. Several reconstructions of the historical gridded sea-ice concentration(SIC) data were recently presented based on synthesized regional sea-ice observations or by applying a hybrid model–empirical approach. Here, we present an SIC reconstruction for the period1901–2019 based on established co-variability between SIC and surface air temperature, sea surface temperature, and sea level pressure patterns. The reconstructed sea-ice data for March and September are compared to the frequently used Had ISST1.1 and SIBT1850 datasets. Our reconstruction shows a large decrease in SIA from the 1920 to 1940 concurrent with the Early 20th Century Warming event in the Arctic. Such a negative SIA anomaly is absent in Had ISST1.1 data. The amplitude of the SIA anomaly reaches about 0.8 mln km^(2) in March and 1.5 mln km^(2) in September. The anomaly is about three times stronger than that in the SIBT1850 dataset. The larger decrease in SIA in September is largely due to the stronger SIC reduction in the western sector of the Arctic Ocean in the 70°–80°N latitudinal zone. Our reconstruction provides gridded monthly data that can be used as boundary conditions for atmospheric reanalyses and model experiments to study the Arctic climate for the first half of the 20th century.

Physical and mechanical properties and microstructures of submarine soils in the Yellow Sea

In recent years,the exploration of seabed has been intensified,but the submarine soils of silt and sand in the Yellow Sea area have not been well investigated so far.In this study,the physical and mechanical properties of silt and sand from the Yellow Sea were measured using a direct shear apparatus and their microstructures were observed using a scanning electron microscope.The test results suggest that the shear strength of silt and sand increases linearly with the increase of normal stress.Based on the direct shear test,the scanning electron microscope was used to observe the section surface of sand.It is observed that the section surface becomes rough,with many“V”‐shaped cracks.Many particles appear on the surface of the silt structure and tend to be disintegrated.The X‐ray diffraction experiment reveals that the sand and silt have different compositions.The shear strength of sand is slightly greater than that of silt under high stress,which is related to the shape of soil particles and the mineral composition.These results can be a reference for further study of other soils in the Yellow Sea;meanwhile,they can serve as soil parameters for the stability and durability analyses of offshore infrastructure construction.

Projecting Wintertime Newly Formed Arctic Sea Ice through Weighting CMIP6 Model Performance and Independence

Precipitous Arctic sea-ice decline and the corresponding increase in Arctic open-water areas in summer months give more space for sea-ice growth in the subsequent cold seasons. Compared to the decline of the entire Arctic multiyear sea ice,changes in newly formed sea ice indicate more thermodynamic and dynamic information on Arctic atmosphere–ocean–ice interaction and northern mid–high latitude atmospheric teleconnections. Here, we use a large multimodel ensemble from phase 6 of the Coupled Model Intercomparison Project(CMIP6) to investigate future changes in wintertime newly formed Arctic sea ice. The commonly used model-democracy approach that gives equal weight to each model essentially assumes that all models are independent and equally plausible, which contradicts with the fact that there are large interdependencies in the ensemble and discrepancies in models' performances in reproducing observations. Therefore, instead of using the arithmetic mean of well-performing models or all available models for projections like in previous studies, we employ a newly developed model weighting scheme that weights all models in the ensemble with consideration of their performance and independence to provide more reliable projections. Model democracy leads to evident bias and large intermodel spread in CMIP6 projections of newly formed Arctic sea ice. However, we show that both the bias and the intermodel spread can be effectively reduced by the weighting scheme. Projections from the weighted models indicate that wintertime newly formed Arctic sea ice is likely to increase dramatically until the middle of this century regardless of the emissions scenario.Thereafter, it may decrease(or remain stable) if the Arctic warming crosses a threshold(or is extensively constrained).

Relative Impacts of Sea Ice Loss and Atmospheric Internal Variability on the Winter Arctic to East Asian Surface Air Temperature Based on Large-Ensemble Simulations with NorESM2

To quantify the relative contributions of Arctic sea ice and unforced atmospheric internal variability to the “warm Arctic, cold East Asia”(WACE) teleconnection, this study analyses three sets of large-ensemble simulations carried out by the Norwegian Earth System Model with a coupled atmosphere–land surface model, forced by seasonal sea ice conditions from preindustrial, present-day, and future periods. Each ensemble member within the same set uses the same forcing but with small perturbations to the atmospheric initial state. Hence, the difference between the present-day(or future) ensemble mean and the preindustrial ensemble mean provides the ice-loss-induced response, while the difference of the individual members within the present-day(or future) set is the effect of atmospheric internal variability. Results indicate that both present-day and future sea ice loss can force a negative phase of the Arctic Oscillation with a WACE pattern in winter. The magnitude of ice-induced Arctic warming is over four(ten) times larger than the ice-induced East Asian cooling in the present-day(future) experiment;the latter having a magnitude that is about 30% of the observed cooling. Sea ice loss contributes about 60%(80%) to the Arctic winter warming in the present-day(future) experiment. Atmospheric internal variability can also induce a WACE pattern with comparable magnitudes between the Arctic and East Asia. Ice-lossinduced East Asian cooling can easily be masked by atmospheric internal variability effects because random atmospheric internal variability may induce a larger magnitude warming. The observed WACE pattern occurs as a result of both Arctic sea ice loss and atmospheric internal variability, with the former dominating Arctic warming and the latter dominating East Asian cooling.

Spatiotemporal variation and freeze-thaw asymmetry of Arctic sea ice in multiple dimensions during 1979 to 2020

Arctic sea ice is broadly regarded as an indicator and amplifier of global climate change.The rapid changes in Arctic sea ice have been widely concerned.However,the spatiotemporal changes in the horizontal and vertical dimensions of Arctic sea ice and its asymmetry during the melt and freeze seasons are rarely quantified simultaneously based on multiple sources of the same long time series.In this study,the spatiotemporal variation and freeze-thaw asymmetry of Arctic sea ice were investigated from both the horizontal and vertical dimensions during 1979–2020 based on remote sensing and assimilation data.The results indicated that Arctic sea ice was declining at a remarkably high rate of–5.4×10^(4) km^(2)/a in sea ice area(SIA)and–2.2 cm/a in sea ice thickness(SIT)during 1979 to 2020,and the reduction of SIA and SIT was the largest in summer and the smallest in winter.Spatially,compared with other sub-regions,SIA showed a sharper declining trend in the Barents Sea,Kara Sea,and East Siberian Sea,while SIT presented a larger downward trend in the northern Canadian Archipelago,northern Greenland,and the East Siberian Sea.Regarding to the seasonal trend of sea ice on sub-region scale,the reduction rate of SIA exhibited an apparent spatial heterogeneity among seasons,especially in summer and winter,i.e.,the sub-regions linked to the open ocean exhibited a higher decline rate in winter;however,the other sub-regions blocked by the coastlines presented a greater decline rate in summer.For SIT,the sub-regions such as the Beaufort Sea,East Siberian Sea,Chukchi Sea,Central Arctic,and Canadian Archipelago always showed a higher downward rate in all seasons.Furthermore,a striking freeze-thaw asymmetry of Arctic sea ice was also detected.Comparing sea ice changes in different dimensions,sea ice over most regions in the Arctic showed an early retreat and rapid advance in the horizontal dimension but late melting and gradual freezing in the vertical dimension.The amount of sea ice melting and freezing was disequilibrium in the Arctic during the considered period,and the rate of sea ice melting was 0.3×10^(4) km^(2)/a and 0.01 cm/a higher than that of freezing in the horizontal and vertical dimensions,respectively.Moreover,there were notable shifts in the melting and freezing of Arctic sea ice in 1997/2003 and 2000/2004,respectively,in the horizontal/vertical dimension.

Spatial patterns of zooplankton abundance,biovolume,and size structure in response to environmental variables:a case study in the Yellow Sea and East China Sea

The Yellow Sea(YS)and East China Sea(ECS)are highly dynamic marginal seas of the northwestern Pacific Ocean.To gain an in-depth understanding of zooplankton community structure,zooplankton abundance,biovolume,and size structure in summer 2017 in the YS and ECS were assessed using ZooScan imaging analysis.Zooplankton abundance and biovolume ranged 2.94–1187.14 inds./m^(3)and 3.13–3438.51 mm^(3)/m^(3),respectively.Based on the biovolume data of the categorized size classes of 26 identified taxonomic groups,the zooplankton community was classified into five groups,and each group was coupled with distinctive oceanographic features.Under the influence of the Yellow Sea Cold Water Mass,the Yellow Sea offshore group featured the lowest bottom temperature(10.84±3.42℃)and the most abundant Calanoids(mainly in the 2–3 mm size class).In the Yellow Sea inshore group,Hydrozoans showed the largest biovolume and dominated in the 3–4-mm and>5-mm size classes.The East China Sea offshore group,which was affected by the Kuroshio Branch Current,featured high temperature and salinity,and the lowest bottom dissolved oxygen(2.58±0.5 mg/L).The lowest values of zooplankton abundance and biovolume in the East China Sea offshore group might be attributed to the bottom dissolved oxygen contents.The East China Sea inshore group,which was mainly influenced by the Zhejiang-Fujian Coastal Current and Changjiang Diluted Water,was characterized by high chlorophyll a and the largest biovolume of carnivorous Siphonophores(280.82±303.37 mm^(3)/m^(3)).The Changjiang River estuary offshore group showed the most abundant Cyclopoids,which might be associated with the less turbid water mass in this region.Seawater temperature was considered the most important factor in shaping the size compositions of Calanoids in different groups.

Wintertime Arctic Sea-Ice Decline Related to Multi-Year La Niña Events

Arctic sea ice has undergone a significant decline in the Barents-Kara Sea(BKS)since the late 1990s.Previous studies have shown that the decrease in sea ice caused by increased poleward moisture transport is modulated by tropical sea temperature changes(mainly referring to La Niña events).The occurrence of multi-year La Niña(MYLA)events has increased significantly in recent decades,and their impact on Arctic sea ice needs to be further explored.In this study,we investigate the relationship between sea-ice variation and different atmospheric diagnostics during MYLA and other La Niña(OTLA)years.The decline in BKS sea ice during MYLA winters is significantly stronger than that during OTLA years.This is because MYLA events tend to be accompanied by a warm Arctic-cold continent pattern with a barotropic high pressure blocked over the Urals region.Consequently,more frequent northward atmospheric rivers intrude into the BKS,intensifying longwave radiation downward to the underlying surface and melting the BKS sea ice.However,in the early winter of OTLA years,a negative North Atlantic Oscillation presents in the high latitudes of the Northern Hemisphere,which obstructs the atmospheric rivers to the south of Iceland.We infer that such a different response of BKS sea-ice decline to different La Niña events is related to stratospheric processes.Considering the rapid climate changes in the past,more frequent MYLA events may account for the substantial Arctic sea-ice loss in recent decades.

Contributors to tidal duration asymmetry with varied coastline configurations on western shelf of Yellow Sea

Coastal management in China is confronted with an urgent choice between natural restoration and maintenance of existing seawalls and reclaimed land for economic development.A key criterion for making this decision is the resilience to coastal flooding,which depends on the ability to predict tidal level.Tidal duration asymmetry(TDA)is a key parameter in determination of the arrival and duration of flood tides.This study selected the western inner shelf of the Yellow Sea(WYS)as the study area and investigated the responses of TDA to different shoreline configurations and relative sea level rise.The responses of TDA to shoreline reconstruction yielded spatial variability locally and remotely.In the nearshore area,the responses of TDA to the complex ocean environment mainly originated from the combined functions of reflection,bottom friction,and advection,which controlled the energy transfer from M2 or S2 constituents to their overtides or compound tides.The sensitivity of TDA to coastline typologies was not limited to coastal waters but could stretch over the entire inner shelf.The vulnerability of tidal responses was due to the displacement of the M2 amphidrome of the Kelvin wave on the WYS,which in turn changed tidal energy fluxes over the regime.The relative sea level rise could intensify the feedback of TDA to seawalls and land reclamation.

Sea Cucumber Fishery in Aurora, Philippines

This study was conducted to provide a preliminary assessment of the sea cucumber fishery in Aurora, Philippines. This was conducted from February to June 2013. All sea cucumber gatherers and traders, obtained through snowball sampling, in each identified sea cucumber fishery area in six coastal municipalities (Baler, Dipaculao, Dinalungan, Casiguran, Dilasag and Dingalan) were interviewed using a structured interview schedule and focused group discussions (FGD). Results revealed that gathering sea cucumbers were accomplished by handpicking, skin diving or compressor diving. A total of 15 commercial species were regularly gathered. Out of this, three species are of very high economic value (≥Php 4000/kg) (Holothuria nobilis, Holothuria scabra, and Actinopyga lecanora). The average number of kilograms harvested per hour per trip ranges from 0.21 (Holothuria fuscopunctata) to 2.71 (Holothuria scabra), while the average size of commonly gathered sea cucumber varies among species with Holothuria lecanora showed an average length (29.26 cm) greater than recorded 24 cm. Processing mainly involves washing, slicing, boiling, drying and packing. Processed sea cucumbers or trepan were sold to middlemen or direct buyers who usually offered higher prices (36.36% up to 69.20%) than the former. Problems encountered by sea cucumber gatherers and traders include a decline in total catch, a shift in area of collection from intertidal zones to deeper waters, an increase in the number of hours spent in finding and gathering sea cucumbers, the use of compressors in gathering, the decline of larger species and gathering of smaller sizes in huge amount, the absence of conservation program for sea cucumber, and the lenient implementation of government policies with regards to coastal resources management.

An ensemble learning method to retrieve sea ice roughness from Sentinel-1 SAR images

Sea ice surface roughness(SIR)affects the energy transfer between the atmosphere and the ocean,and it is also an important indicator for sea ice characteristics.To obtain a small-scale SIR with high spatial resolution,a novel method is proposed to retrieve SIR from Sentinel-1 synthetic aperture radar(SAR)images,utilizing an ensemble learning method.Firstly,the two-dimensional continuous wavelet transform is applied to obtain the spatial information of sea ice,including the scale and direction of ice patterns.Secondly,a model is developed using the Adaboost Regression model to establish a relationship among SIR,radar backscatter and the spatial information of sea ice.The proposed method is validated by using the SIR retrieved from SAR images and comparing it to the measurements obtained by the Airborne Topographic Mapper(ATM)in the summer Beaufort Sea.The determination of coefficient,mean absolute error,root-mean-square error and mean absolute percentage error of the testing data are 0.91,1.71 cm,2.82 cm,and 36.37%,respectively,which are reasonable.Moreover,K-fold cross-validation and learning curves are analyzed,which also demonstrate the method’s applicability in retrieving SIR from SAR images.

Deep Learning Shows Promise for Seasonal Prediction of Antarctic Sea Ice in a Rapid Decline Scenario

The rapidly changing Antarctic sea ice has garnered significant interest. To enhance the prediction skill for sea ice and respond to the Sea Ice Prediction Network-South's latest call, this study presents the reforecast results of Antarctic sea-ice area and extent from December to June of the coming year with a Convolutional Long Short-Term Memory(Conv LSTM)Network. The reforecast experiments demonstrate that Conv LSTM captures the interannual and interseasonal variability of Antarctic sea ice successfully, and performs better than the European Centre for Medium-Range Weather Forecasts. Based on this, we present the prediction from December 2023 to June 2024, indicating that the Antarctic sea ice will remain at lows, but may not create a new record low. This research highlights the promising application of deep learning in Antarctic sea-ice prediction.

Diversity, Abundance and Distribution Patterns of Epibenthic Echinoderms in Dungonab Bay, Red Sea, Sudan

The abundance, distribution and diversity of epibenthic echinoderm were investigated at Dungonab Bay in the Red Sea coastal water of the Sudan. Four permanent line transects were chosen. Eight (30 × 2) square metre belt transects along each permanent line transect at 20 metre intervals were used to collect data. The data were subjected to univariate and multivariate analyses. Spatial variations of epibenthic echinoderm abundance were assessed with one-way analysis of variance. Hierarchical agglomerative clustering was used to identify and illustrate the similarities in echinoderm abundance between line transects and between belt transects. Indices of richness (d), diversity (H'), evenness (J') and dominance (C) were used to explain the diversity of epibenthic echinoderm species. The distribution pattern of each echinoderm species was determined in each permanent line transect. A total of 986 individuals were recorded within sixteen species of epibenthic echinoderms in the four line transects. Holothuriidae was the dominant family (5 species and 342 individuals). The most abundant echinoderms species was Pearsonothuria graeffei (77 individuals, about 7.81%). Abundances intra-transects and intra-families were insignificant (f = 1.67, p = 0.183, df = 3 and f = 3.24, p = 0.083, df = 9, respectively). The highest values of Shannon-Wiener diversity index (H'), Pielou evenness index (J'), Margalef species richness index (d), and Simpson Dominance index (C) were 2.738, 0.9875, 2.791 and 0.07159, respectively. The distribution patterns of all species in the study transects varied between clumped and uniform, with the exception of Asthenosoma varium of the Echinothuridae family, which had clumped distribution patterns in all transects. The study concluded that Dungonab Bay supports rich and diverse communities of epibenthic echinoderms.

Limited Sea Surface Temperature Cooling Due to the Barrier Layer Promoting Super Typhoon Mangkhut(2018)

This study investigates the impact of the salinity barrier layer(BL)on the upper ocean response to Super Typhoon Mangkhut(2018)in the western North Pacific.After the passage of Mangkhut,a noticeable increase(~0.6 psu)in sea surface salinity and a weak decrease(<1℃)in sea surface temperature(SST)were observed on the right side of the typhoon track.Mangkhut-induced SST change can be divided into the three stages,corresponding to the variations in BL thickness and SST before,during,and after the passage of Mangkhut.During the pre-typhoon stage,SST slightly warmed due to the entrainment of BL warm water,which suppressed the cooling induced by surface heat fluxes and horizontal advection.During the forced stage,SST cooling was controlled by entrainment,and the preexisting BL reduced the total cooling by 0.89℃ d-1,thus significantly weakening the overall SST cooling induced by Mangkhut.During the relaxation stage,the SST cooling was primarily caused by the entrainment.Our results indicate that a preexisting BL can limit typhoon-induced SST cooling by suppressing the entrainment of cold thermocline water,which contributed to Mangkhut becoming the strongest typhoon in 2018.

Analysis of Sea Surface Temperature Cooling in Typhoon Events Passing the Kuroshio Current

The aim of this study is to investigate the sea surface temperature(SST) cooling as typhoons pass the Kuroshio Current.A numerical circulation model,denoted as the Stony Brook Parallel Ocean Model(sbPOM),was used to simulate the SST,which includes four wave-induced effect terms(i.e.,radiation stress,nonbreaking waves,Stokes drift,and breaking waves) simulated using the third-generation wave model,called WAVEWATCH-Ⅲ(WW3).The significant wave height(SWH) measurements from the Jason-2 altimeter were used to validate the WW3-simulated results,yielding a root mean square error(RMSE) of less than 0.50 m and a correlation coefficient(COR) of approximately 0.93.The water temperature measured from the Advanced Research and Global Observation Satellite was applied to validate the model simulation.Accordingly,the RMSE of the SST is 0.92℃ with a COR of approximately 0.99.As revealed in the sbPOM-simulated SST fields,a reduction in the SST at the Kuroshio Current region was observed as a typhoon passed,although the water temperature of the Kuroshio Current is relatively high.The variation of the SST is consistent with that of the current,whereas the maximum SST lagged behind the occurrence of the peak SWH.Moreover,the Stokes drift plays an important role in the SST cooling after analyzing four wave-induced terms in the background of the Kuroshio Current.The sensitivity experiment also showed that the accuracy of the water temperature was significantly reduced when including breaking waves,which play a negative role in the inside part of the ocean.The variation in the mean mixing layer depth(MLD) showed that a typhoon could enhance the mean MLD in the Kuroshio Current area in September and October,whereas a typhoon has little influence on the mean MLD in the Kuroshio Current area in May.Moreover,the mean MLD rapidly decreased with the weakening of the strong wind force and wave-induced effects when a typhoon crossed the Kuroshio Current.

Effects of Poria cocos polysaccharide on growth performance,physiological parameters,and lipid metabolism of spotted sea bass Lateolabrax maculatus

The aquaculture industry has developed significantly over the past few decades and has had a substantial impact on the global food supply and marine fisheries resources.However,some problems arise behind the scenes due to excessive intensive farming,such as slow animal growth,frequent disease,and lipid metabolism disorders.These problems have limited the sustainable development of the aquaculture industry,and a continuable solution is required.The use of fungal polysaccharide appears to provide a solution to these problems.Therefore,different supplemented levels of Poria cocos polysaccharide(PCP)(0,0.4,0.8,1.2,1.6,and 2.0 g/kg,respectively)were fed to spotted sea bass(Lateolabrax maculatus)in similar size(30.28±0.18 g)in current study.The effects of PCP on growth,physiological parameters,and lipid metabolism of spotted sea bass were investigated after a 4-week rearing period.Results showed,fish with PCP intake presented a significantly higher weight gain,specific growth rate,and a significantly lower feed conversion ratio.Significantly higher trypsin activity in liver and intestine were observed in fish with PCP intake.The superoxide dismutase activity in serum and liver of fish with PCP intake were significantly improved,while significantly higher serum total antioxidant capacity and hepatic catalase activity were also observed.However,no significant differences in lysozyme and alkaline phosphatase activity were evident among groups.Fish with PCP intake showed a significantly lower total cholesterol,but no noteworthy change in triglyceride and lipid-metabolismrelated genes expression were observed among groups.Results indicated that intake of PCP has a positive effect on growth and antioxidant capacity of spotted sea bass,but seems to have a limited effect on the non-specific immunity and lipid metabolism of spotted sea bass.Based on the regression analysis results,1.4 g/kg of PCP is the optimal dose for spotted sea bass in size(30.28±0.18 g).

Spatio-temporal variability of surface chlorophyll a in the Yellow Sea and the East China Sea based on reconstructions of satellite data of 2001-2020

Chlorophyll-a(Chl-a)concentration is a primary indicator for marine environmental monitoring.The spatio-temporal variations of sea surface Chl-a concentration in the Yellow Sea(YS)and the East China Sea(ECS)in 2001-2020 were investigated by reconstructing the MODIS Level 3 products with the data interpolation empirical orthogonal function(DINEOF)method.The reconstructed results by interpolating the combined MODIS daily+8-day datasets were found better than those merely by interpolating daily or 8-day data.Chl-a concentration in the YS and the ECS reached its maximum in spring,with blooms occurring,decreased in summer and autumn,and increased in late autumn and early winter.By performing empirical orthogonal function(EOF)decomposition of the reconstructed data fields and correlation analysis with several potential environmental factors,we found that the sea surface temperature(SST)plays a significant role in the seasonal variation of Chl a,especially during spring and summer.The increase of SST in spring and the upper-layer nutrients mixed up during the last winter might favor the occurrence of spring blooms.The high sea surface temperature(SST)throughout the summer would strengthen the vertical stratification and prevent nutrients supply from deep water,resulting in low surface Chl-a concentrations.The sea surface Chl-a concentration in the YS was found decreased significantly from 2012 to 2020,which was possibly related to the Pacific Decadal Oscillation(PDO).

An improved algorithm for retrieving thin sea ice thickness in the Arctic Ocean from SMOS and SMAP L-band radiometer data

The aim of this study was to develop an improved thin sea ice thickness(SIT)retrieval algorithm in the Arctic Ocean from the Soil Moisture Ocean Salinity and Soil Moisture Active Passive L-band radiometer data.This SIT retrieval algorithm was trained using the simulated SIT from the cumulative freezing degree days model during the freeze-up period over five carefully selected regions in the Beaufort,Chukchi,East Siberian,Laptev and Kara seas and utilized the microwave polarization ratio(PR)at incidence angle of 40°.The improvements of the proposed retrieval algorithm include the correction for the sea ice concentration impact,reliable reference SIT data over different representative regions of the Arctic Ocean and the utilization of microwave polarization ratio that is independent of ice temperature.The relationship between the SIT and PR was found to be almost stable across the five selected regions.The SIT retrievals were then compared to other two existing algorithms(i.e.,UH_SIT from the University of Hamburg and UB_SIT from the University of Bremen)and validated against independent SIT data obtained from moored upward looking sonars(ULS)and airborne electromagnetic(EM)induction sensors.The results suggest that the proposed algorithm could achieve comparable accuracies to UH_SIT and UB_SIT with root mean square error(RMSE)being about 0.20 m when validating using ULS SIT data and outperformed the UH_SIT and UB_SIT with RMSE being about 0.21 m when validatng using EM SIT data.The proposed algorithm can be used for thin sea ice thickness(<1.0 m)estimation in the Arctic Ocean and requires less auxiliary data in the SIT retrieval procedure which makes its implementation more practical.