2018 Vol. 40, No. 6
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2018, 40(6): .
Abstract:
2018, 40(6): 1-14.
doi: 10.3969/j.issn.0253-4193.2018.06.001
Abstract:
According to the state of art of South China Sea (SCS) which is with complex currents environment and a small number of mid-depth observations, a gridding seasonal velocity field is generated via Divand variational interpolation method using mid-depth velocity data of 1200 m derived from the satellite positioning of 114 Argo profiling floats deployed in SCS from 2006 to 2016 using the method of least square and based on the background and inertial currents. The conclusions could be drawn as follows. (1) Velocity trajectory of one single Argo profiling float could describe the concrete structure of the mesoscale phenomenon, e.g. the anti-cyclonic mesoscale eddy at the mid-depth (1 200 m) off the Vietnam east coast which has a radius of 120 km, a maximum current velocity of 9.6 cm/s and a average current velocity of 5.3 cm/s. (2) The gridding seasonal currents field generated from Argo demonstrates that the mid-depth current of basin scale has the anti-cyclonic structure in southern part of SCS and cyclonic structure in northern part. Meanwhile, there exists water exchange from SCS to the Pacific Ocean through Luzon Strait. (3) The generated gridding seasonal currents field is highly consistent with HYCOM Reanalysis and YoMaHa'07 data. Comparing the generated currents field with HYCOM Reanalysis data, the distribution of the departure of the two is normal, while the root mean square error of zonal component of the velocity of the currents is 3.28 cm/s and the counterpart of the meridional component is 3.26 cm/s. All in all, the features of the basin scale mid-depth circulation in SCS could be efficiently retrieved by the Argo trajectory data.
According to the state of art of South China Sea (SCS) which is with complex currents environment and a small number of mid-depth observations, a gridding seasonal velocity field is generated via Divand variational interpolation method using mid-depth velocity data of 1200 m derived from the satellite positioning of 114 Argo profiling floats deployed in SCS from 2006 to 2016 using the method of least square and based on the background and inertial currents. The conclusions could be drawn as follows. (1) Velocity trajectory of one single Argo profiling float could describe the concrete structure of the mesoscale phenomenon, e.g. the anti-cyclonic mesoscale eddy at the mid-depth (1 200 m) off the Vietnam east coast which has a radius of 120 km, a maximum current velocity of 9.6 cm/s and a average current velocity of 5.3 cm/s. (2) The gridding seasonal currents field generated from Argo demonstrates that the mid-depth current of basin scale has the anti-cyclonic structure in southern part of SCS and cyclonic structure in northern part. Meanwhile, there exists water exchange from SCS to the Pacific Ocean through Luzon Strait. (3) The generated gridding seasonal currents field is highly consistent with HYCOM Reanalysis and YoMaHa'07 data. Comparing the generated currents field with HYCOM Reanalysis data, the distribution of the departure of the two is normal, while the root mean square error of zonal component of the velocity of the currents is 3.28 cm/s and the counterpart of the meridional component is 3.26 cm/s. All in all, the features of the basin scale mid-depth circulation in SCS could be efficiently retrieved by the Argo trajectory data.
2018, 40(6): 15-28.
doi: 10.3969/j.issn.0253-4193.2018.06.002
Abstract:
Kuroshio and Gulf Stream are the two most typical western boundary currents in the world's ocean, and mesoscale eddies are very active in Kuroshio Extention (KE) and Gulf Stream extension (GSE) regions. In this paper, surface features of mesoscale eddies in KE and GSE regions and their effects on temperature and salinity fields are studied and compared using satellite altimeter data and Argo buoy data. The results show that eddy frequency is extremely high and eddy intensity is obviously larger near the main axes of both Kuroshio and Gulf stream, and cyclonic eddies (CE) and anticyclonic eddies (AE) dominate in the south and north sides of the main axes, respectively. Most eddies propagate westward with a little southward (equatorward) deflection. The amount of eddies in the two regions are both larger in summer and autumn, and eddy intensities are larger in spring and summer, meanwhile intensities of eddies in GSE are larger than those in KE. CE (AE) cause consistent negative (positive) temperature anomaly. CE (AE) in KE represent "negative-positive" ("positive-negative") salinity anomaly distribution from upper to lower layers, while CE (AE) in GSE exhibit a more consistent negative (positive) salinity anomaly in each layer. The average effect of mesoscale eddies on temperature and salinity fields in the two regions can reach more than 1 000×104 Pa depths.
Kuroshio and Gulf Stream are the two most typical western boundary currents in the world's ocean, and mesoscale eddies are very active in Kuroshio Extention (KE) and Gulf Stream extension (GSE) regions. In this paper, surface features of mesoscale eddies in KE and GSE regions and their effects on temperature and salinity fields are studied and compared using satellite altimeter data and Argo buoy data. The results show that eddy frequency is extremely high and eddy intensity is obviously larger near the main axes of both Kuroshio and Gulf stream, and cyclonic eddies (CE) and anticyclonic eddies (AE) dominate in the south and north sides of the main axes, respectively. Most eddies propagate westward with a little southward (equatorward) deflection. The amount of eddies in the two regions are both larger in summer and autumn, and eddy intensities are larger in spring and summer, meanwhile intensities of eddies in GSE are larger than those in KE. CE (AE) cause consistent negative (positive) temperature anomaly. CE (AE) in KE represent "negative-positive" ("positive-negative") salinity anomaly distribution from upper to lower layers, while CE (AE) in GSE exhibit a more consistent negative (positive) salinity anomaly in each layer. The average effect of mesoscale eddies on temperature and salinity fields in the two regions can reach more than 1 000×104 Pa depths.
2018, 40(6): 29-39.
doi: 10.3969/j.issn.0253-4193.2018.06.003
Abstract:
The Soil Moisture Active Passive (SMAP) was launched by National Aeronautics and Space Administration (NASA) in early 2015, which carried an L-band Radar with a conical scanning antenna. It has the constant incidence angle, the wide swath and the km-scale resolution. And thus it has a significant potential for observing sea ice. The paper establishes the 3.125 km matchup data set by using the University of Bremen sea ice concentration and SMAP radar data, and the 25 km matchup data set by using the National Snow and Ice Data Center (NSIDC) sea ice concentration and SMAP radar data. A sea ice concentration algorithm based on artificial neural network is proposed by the relation between sea ice concentration and HH-polarized NRCS, HH/HV polarized ratio, HH-polarized difference. The retrieved sea ice concentration is validated by using sea ice concentrations from NSDIC and the University of Bremen. The root mean square differences (RMSDs) and biases of sea ice concentration between SMAP Radar and the University of Bremen are 0.14 and 0.07, respectively. The RMSDs and biased of SMAP sea ice concentration versus NSDIC ones are 0.18 and 0.04, respectively. The results show that SMAP sea ice concentration is basically consistent with the operational sea ice concentration.
The Soil Moisture Active Passive (SMAP) was launched by National Aeronautics and Space Administration (NASA) in early 2015, which carried an L-band Radar with a conical scanning antenna. It has the constant incidence angle, the wide swath and the km-scale resolution. And thus it has a significant potential for observing sea ice. The paper establishes the 3.125 km matchup data set by using the University of Bremen sea ice concentration and SMAP radar data, and the 25 km matchup data set by using the National Snow and Ice Data Center (NSIDC) sea ice concentration and SMAP radar data. A sea ice concentration algorithm based on artificial neural network is proposed by the relation between sea ice concentration and HH-polarized NRCS, HH/HV polarized ratio, HH-polarized difference. The retrieved sea ice concentration is validated by using sea ice concentrations from NSDIC and the University of Bremen. The root mean square differences (RMSDs) and biases of sea ice concentration between SMAP Radar and the University of Bremen are 0.14 and 0.07, respectively. The RMSDs and biased of SMAP sea ice concentration versus NSDIC ones are 0.18 and 0.04, respectively. The results show that SMAP sea ice concentration is basically consistent with the operational sea ice concentration.
2018, 40(6): 40-50.
doi: 10.3969/j.issn.0253-4193.2018.06.004
Abstract:
Vegetation fraction coverage (VFC) is an important quantitative indicator of the vegetation growth. At present, remote sensing estimation work of VFC has been mainly implemented in land areas but seldom in estuary wetland. In this paper, we carried out VFC estimation of the Yellow River Estuary wetland based on homemade GF-1 WFV satellite image, and developed the analysis of VFC distribution characteristics based on vegetation type, soil salinity and vegetation index. The main conclusions we drew from this study are:(1) According to GF-1 WFV satellite image, VFC estimation model was built based on five vegetation index, including NDVI, SRI, SAVI, MSAVI and DVI. The largest determination coefficient R2 (0.904) and the smallest root-mean-square error RMSE (0.14) were obtained from the multivariate linear regression model, which was the best model of all, built upon NDVI, SRI, MSAVI and DVI. (2) Estimation precision of VFC estimation model was found depending on the value of VFC. The estimation precision was higher in areas with a VFC value larger than 0.8, compared to areas with a VFC value smaller than 0.6 and the maximum difference for RMSE is 0.04. (3) VFC areas that mainly occupied with suaeda and tidal flat phragmites were considered to be low VFC areas, which had VFC values in the range of 0.03 to 0.5, and salt salinities were around 1.5 g/L. Phragmites meadow, spartina and tamarix chinesis shrub occupied areas belonged to high VFC areas with VFC values varied from 0.8 to 1.0. The salt salinity of phragmites meadow was smaller than 1.2 g/L, and that of tamarix chinesis shrub was in between 1.4 and 2.0 g/L. Medium VFC vegetation with VFC values ranging from 0.5 to 0.8 was found in high VFC areas and possessed salt salinity around 1.8 g/L. (4) Among all studied areas, low and high VFC areas accounted for 25.1% and 20.2%, respectively, while medium VFC areas only took up 8.3% in proportion.
Vegetation fraction coverage (VFC) is an important quantitative indicator of the vegetation growth. At present, remote sensing estimation work of VFC has been mainly implemented in land areas but seldom in estuary wetland. In this paper, we carried out VFC estimation of the Yellow River Estuary wetland based on homemade GF-1 WFV satellite image, and developed the analysis of VFC distribution characteristics based on vegetation type, soil salinity and vegetation index. The main conclusions we drew from this study are:(1) According to GF-1 WFV satellite image, VFC estimation model was built based on five vegetation index, including NDVI, SRI, SAVI, MSAVI and DVI. The largest determination coefficient R2 (0.904) and the smallest root-mean-square error RMSE (0.14) were obtained from the multivariate linear regression model, which was the best model of all, built upon NDVI, SRI, MSAVI and DVI. (2) Estimation precision of VFC estimation model was found depending on the value of VFC. The estimation precision was higher in areas with a VFC value larger than 0.8, compared to areas with a VFC value smaller than 0.6 and the maximum difference for RMSE is 0.04. (3) VFC areas that mainly occupied with suaeda and tidal flat phragmites were considered to be low VFC areas, which had VFC values in the range of 0.03 to 0.5, and salt salinities were around 1.5 g/L. Phragmites meadow, spartina and tamarix chinesis shrub occupied areas belonged to high VFC areas with VFC values varied from 0.8 to 1.0. The salt salinity of phragmites meadow was smaller than 1.2 g/L, and that of tamarix chinesis shrub was in between 1.4 and 2.0 g/L. Medium VFC vegetation with VFC values ranging from 0.5 to 0.8 was found in high VFC areas and possessed salt salinity around 1.8 g/L. (4) Among all studied areas, low and high VFC areas accounted for 25.1% and 20.2%, respectively, while medium VFC areas only took up 8.3% in proportion.
2018, 40(6): 51-59.
doi: 10.3969/j.issn.0253-4193.2018.06.005
Abstract:
This study aims to use hyperspectral reflectance to estimate soil salinity. Taking the coastal saline soil of the Yellow River Delta as an example, we collected in situ ground surface reflectance and soil samples for salinity analysis, and integrated with the HICO (Hyperspectral Imager for the Coastal Ocean) imagery data to map the distribution of salinity. The spectral features were established by band combination method. The sensitive features were selected by correlation analysis. The optimal models were selected by the determination coefficients R2. The relationship between the in situ reflectance and the HICO hyperspectral reflectance is used to modify the model. And these models were applied to HICO images. The study showed that the models of band ratio (RI) and band difference (DI) with significantly high correlations with the soil salinity were established. The power function models established by DI(845, 473), DI(839, 490), DI(845, 496), DI(839, 501) were the best ones (the determination coefficients R2>0.86, and the relative prediction deviation RPD>3). The inversion results in the HICO from these models were consistent with each other, and can reflect the distribution of soil salinity for the Yellow River Delta. This study suggests that it is feasible to estimate the soil salinity by using the hyperspectral data, which can provide a reference for quantitative inversion of soil salinity in the coastal region.
This study aims to use hyperspectral reflectance to estimate soil salinity. Taking the coastal saline soil of the Yellow River Delta as an example, we collected in situ ground surface reflectance and soil samples for salinity analysis, and integrated with the HICO (Hyperspectral Imager for the Coastal Ocean) imagery data to map the distribution of salinity. The spectral features were established by band combination method. The sensitive features were selected by correlation analysis. The optimal models were selected by the determination coefficients R2. The relationship between the in situ reflectance and the HICO hyperspectral reflectance is used to modify the model. And these models were applied to HICO images. The study showed that the models of band ratio (RI) and band difference (DI) with significantly high correlations with the soil salinity were established. The power function models established by DI(845, 473), DI(839, 490), DI(845, 496), DI(839, 501) were the best ones (the determination coefficients R2>0.86, and the relative prediction deviation RPD>3). The inversion results in the HICO from these models were consistent with each other, and can reflect the distribution of soil salinity for the Yellow River Delta. This study suggests that it is feasible to estimate the soil salinity by using the hyperspectral data, which can provide a reference for quantitative inversion of soil salinity in the coastal region.
2018, 40(6): 60-73.
doi: 10.3969/j.issn.0253-4193.2018.06.006
Abstract:
The present study analyzed the distribution and pollution characteristic of heavy metals in surface sediments from the Liaodong Bay, and then evaluated the potential ecological risk caused by heavy metals to learn the environment quality of sediments. Content distributions of heavy metals including As,Cu,Cd,Cr,Hg,Ni,Pb and Zn in surface sediments from the Liaodong Bay were studied. Simultaneously,the potential ecological risks of these heavy metals were analyzed by the index method on potential ecological risk and geoaccumulation index(Igeo) and Environment quality in surface sediments from the Liaodong Bay was evaluated. The contents of As,Cu,Cd,Cr,Hg,Ni,Pb and Zn in surface sediments appeared higher near the Huludao,southeast sea of the Liugu estuary in the southwest part,near sea in the western. The results of pollution assessment by index of geoaccumulation and the potential ecological risk index were almost the same. The order of ecological risk of these heavy metal is as follow:Cd > Hg > Cu > Pb > As > Zn > Ni > Cr,with Cd,Hg and As being the potential risk elements for the ecological environment from the Liaodong Bay. The assessment result of ecological risk revealed this area belongs to moderate potential ecological risk. The environmental quality assessment showed that the heavy metals in surface sediments from the Liaodong Bay were not likely to cause harmful biological effects,but Cd and Hg were significantly enriched,therefore much attention should be paid to these areas.
The present study analyzed the distribution and pollution characteristic of heavy metals in surface sediments from the Liaodong Bay, and then evaluated the potential ecological risk caused by heavy metals to learn the environment quality of sediments. Content distributions of heavy metals including As,Cu,Cd,Cr,Hg,Ni,Pb and Zn in surface sediments from the Liaodong Bay were studied. Simultaneously,the potential ecological risks of these heavy metals were analyzed by the index method on potential ecological risk and geoaccumulation index(Igeo) and Environment quality in surface sediments from the Liaodong Bay was evaluated. The contents of As,Cu,Cd,Cr,Hg,Ni,Pb and Zn in surface sediments appeared higher near the Huludao,southeast sea of the Liugu estuary in the southwest part,near sea in the western. The results of pollution assessment by index of geoaccumulation and the potential ecological risk index were almost the same. The order of ecological risk of these heavy metal is as follow:Cd > Hg > Cu > Pb > As > Zn > Ni > Cr,with Cd,Hg and As being the potential risk elements for the ecological environment from the Liaodong Bay. The assessment result of ecological risk revealed this area belongs to moderate potential ecological risk. The environmental quality assessment showed that the heavy metals in surface sediments from the Liaodong Bay were not likely to cause harmful biological effects,but Cd and Hg were significantly enriched,therefore much attention should be paid to these areas.
2018, 40(6): 74-82.
doi: 10.3969/j.issn.0253-4193.2018.06.007
Abstract:
Cololabis saira is extremely sensitive to marine environmental factors.Different climate conditions may have different effects on abundance index of Cololabis saira in the Northwest Pacific.We defined the year as cold year or warm year by annual average of Pacific Decadal Oscillation(PDO) index. Based on the data of the CPUE (catch per unit effort) and sea surface temperature (SST) data from remote sensing in the feeding grounds and spawning grounds in the Northwest Pacific from 1990 to 2014, the relationship between CPUE and SST is analyzed, and the forecasting model of abundance index is also established by using the linear regression models for the cold and warm index years.The results show that the SST of feeding ground is significantly related to the CPUE in April during cold years(P<0.05), and this phenomenon may be related to the Kuroshio enhancement in April. The SST of feeding ground is also significantly related to the CPUE in November during warm years(P<0.05), and this phenomenon may be related to the reduction of SST in November. It is also found that the forecasting modelsbetween CPUE and SST in the feeding ground during April and November are built, which is significant in statistics(P<0.05). During the PDO cold times (the year of 2012) and PDO warm times (the year of 2014), the relative error between CPUE predicted value and actual value is 14.03% and -16.26%, respectively, which have better fitting effect. The research shows that under different climate condition, the environmental factors used to forecast abundance index of Cololabis saira different. It is concluded that the forecasting model of abundance index can be used for the operation in the Cololabis saira fishery.
Cololabis saira is extremely sensitive to marine environmental factors.Different climate conditions may have different effects on abundance index of Cololabis saira in the Northwest Pacific.We defined the year as cold year or warm year by annual average of Pacific Decadal Oscillation(PDO) index. Based on the data of the CPUE (catch per unit effort) and sea surface temperature (SST) data from remote sensing in the feeding grounds and spawning grounds in the Northwest Pacific from 1990 to 2014, the relationship between CPUE and SST is analyzed, and the forecasting model of abundance index is also established by using the linear regression models for the cold and warm index years.The results show that the SST of feeding ground is significantly related to the CPUE in April during cold years(P<0.05), and this phenomenon may be related to the Kuroshio enhancement in April. The SST of feeding ground is also significantly related to the CPUE in November during warm years(P<0.05), and this phenomenon may be related to the reduction of SST in November. It is also found that the forecasting modelsbetween CPUE and SST in the feeding ground during April and November are built, which is significant in statistics(P<0.05). During the PDO cold times (the year of 2012) and PDO warm times (the year of 2014), the relative error between CPUE predicted value and actual value is 14.03% and -16.26%, respectively, which have better fitting effect. The research shows that under different climate condition, the environmental factors used to forecast abundance index of Cololabis saira different. It is concluded that the forecasting model of abundance index can be used for the operation in the Cololabis saira fishery.
2018, 40(6): 83-91.
doi: 10.3969/j.issn.0253-4193.2018.06.008
Abstract:
Based on the data collected by bottom-trawl surveys in the Haizhou Bay and adjacent waters during spring in 2011 and 2013-2015, habitat suitability index (HSI) model of Johnius belangerii was constructed in this study. According to the data of resource density, bottom temperature, bottom salinity and depth, boosted regression tree (BRT) was used to evaluate the weight of each environmental variable in the HSI model. The arithmetic mean model (AMM) and the geometric mean model (GMM) were used to build HSI model, and the best model was selected by cross validations. Results showed that the optimal range of each environmental variable of juvenile J. belangerii in spring with bottom temperature, bottom salinity and depth were 17.4-18℃, 29.2-30.8, and less than 7 m, respectively. For adults, the optimal range of bottom temperature, bottom salinity and depth were 17.3-18℃, 28.8-30.8 and <12 m, respectively. BRT model showed that the weight of bottom temperature, bottom salinity and depth for juveniles were 25.26%, 26.58% and 48.16% respectively, and the depth played a key role among these environmental variables. The weight of bottom temperature, bottom salinity and depth for adults were 47.08%, 20.29% and 32.63% respectively. And the bottom temperature was the most important environmental variable for adults. Cross validation showed that the weighted HSI model performed better for both juveniles and adults with lower AIC (Akaike information criterion) values. In Haizhou Bay, the optimal habitat for J. belangerii in spring varies with the growth stage. The most suitable habitats (HSI ≥ 0.7) for juveniles were mainly distributed in the shallow coastal waters (<7 m) of Shandong and Jiangsu alongshore during spring. For adults, the area of the highest habitat quality was wider than juveniles, and it mainly distributed in the shallow waters less than 12 m isobath areas. The distribution of J. belangerii was closely related to its biological traits, environmental factors, Yellow Sea Cold Water Mass and coastal currents in the Haizhou Bay, China.
Based on the data collected by bottom-trawl surveys in the Haizhou Bay and adjacent waters during spring in 2011 and 2013-2015, habitat suitability index (HSI) model of Johnius belangerii was constructed in this study. According to the data of resource density, bottom temperature, bottom salinity and depth, boosted regression tree (BRT) was used to evaluate the weight of each environmental variable in the HSI model. The arithmetic mean model (AMM) and the geometric mean model (GMM) were used to build HSI model, and the best model was selected by cross validations. Results showed that the optimal range of each environmental variable of juvenile J. belangerii in spring with bottom temperature, bottom salinity and depth were 17.4-18℃, 29.2-30.8, and less than 7 m, respectively. For adults, the optimal range of bottom temperature, bottom salinity and depth were 17.3-18℃, 28.8-30.8 and <12 m, respectively. BRT model showed that the weight of bottom temperature, bottom salinity and depth for juveniles were 25.26%, 26.58% and 48.16% respectively, and the depth played a key role among these environmental variables. The weight of bottom temperature, bottom salinity and depth for adults were 47.08%, 20.29% and 32.63% respectively. And the bottom temperature was the most important environmental variable for adults. Cross validation showed that the weighted HSI model performed better for both juveniles and adults with lower AIC (Akaike information criterion) values. In Haizhou Bay, the optimal habitat for J. belangerii in spring varies with the growth stage. The most suitable habitats (HSI ≥ 0.7) for juveniles were mainly distributed in the shallow coastal waters (<7 m) of Shandong and Jiangsu alongshore during spring. For adults, the area of the highest habitat quality was wider than juveniles, and it mainly distributed in the shallow waters less than 12 m isobath areas. The distribution of J. belangerii was closely related to its biological traits, environmental factors, Yellow Sea Cold Water Mass and coastal currents in the Haizhou Bay, China.
2018, 40(6): 92-103.
doi: 10.3969/j.issn.0253-4193.2018.06.009
Abstract:
The genus Oithona is one of small size cyclopoid copepods which widely distributed and occurs in all kinds of marine environments (estuarine, coastal and oceanic waters). However, routine identification of the species has remained challenging due to the small body size and subtle morphological differences among them. We started with a survey of species diversity in the genus Oithona in the South China Sea using a morphological approach, then obtained sequences from mitochondrial COⅠ gene from several individuals of different species, performed tests on DNA taxonomy (ABGD and GMYC) and built a phylogenetic tree with the same gene sequence data download from DNA database. The results of delimitation using ABGD and GMYC model were consistent with morphological approach. The genetic distance within species was 0.0%-1.6% while 17.7%-44.5% between species. Both Bayes and Maximum Likelihood phylogenetic tree showed that each species was clustered together as a monophyletic group. O.simplex first separated from others species indicated pioneer speciation in Oithona. Two cryptic species were found in O.similis and O.plumifera, which were from the South China Sea and Mediterranean, Korea Strait and North Sea, respectively the genetic distance reached to 18.6% and 22.9%.
The genus Oithona is one of small size cyclopoid copepods which widely distributed and occurs in all kinds of marine environments (estuarine, coastal and oceanic waters). However, routine identification of the species has remained challenging due to the small body size and subtle morphological differences among them. We started with a survey of species diversity in the genus Oithona in the South China Sea using a morphological approach, then obtained sequences from mitochondrial COⅠ gene from several individuals of different species, performed tests on DNA taxonomy (ABGD and GMYC) and built a phylogenetic tree with the same gene sequence data download from DNA database. The results of delimitation using ABGD and GMYC model were consistent with morphological approach. The genetic distance within species was 0.0%-1.6% while 17.7%-44.5% between species. Both Bayes and Maximum Likelihood phylogenetic tree showed that each species was clustered together as a monophyletic group. O.simplex first separated from others species indicated pioneer speciation in Oithona. Two cryptic species were found in O.similis and O.plumifera, which were from the South China Sea and Mediterranean, Korea Strait and North Sea, respectively the genetic distance reached to 18.6% and 22.9%.
2018, 40(6): 104-112.
doi: 10.3969/j.issn.0253-4193.2018.06.010
Abstract:
In order to clarify the relationship between the formation of Karenia mikimotoi bloom and environmental factors, and grasp the rules of its occurrence and development, the meteorological, hydrological and nutrient conditions of the formation of K. mikimotoi bloom during the late spring and early summer of 2012 in the Sansha Bay were analyzed. Combined with laboratory experiment, the correlation between the formation of K. mikimotoi bloom and the environmental factors were discussed in this study. The results show that K. mikimotoi bloom usually occurs in the sea water with temperature and salinity ranging from 20.5-25.0℃ and 26.0-32.3, and the suitable temperature and salinity for K. mikimotoi are 22.0-25.0℃and 26.0-30.0, respectively. Pearson correlation analysis shows that the cell density of K. mikimotoi is positively correlated with chlorophyll a, inorganic phosphorus and chemical oxygen demand, and negatively correlated with transparency and ammonia nitrogen; K. mikimotoi cell has a low demand for phosphate, and the formation of bloom may be mainly affected by ammonia nitrogen in water. Based on field investigation and simulation results, comprehensive analysis shows that the stable hydrological and meteorological conditions, the inorganic nitrogen input during the early stage rainfall, as well as the lower light intensity due to continuous overcast and rainy conditions were the important conditions for the formation and maintenance of the red tide.
In order to clarify the relationship between the formation of Karenia mikimotoi bloom and environmental factors, and grasp the rules of its occurrence and development, the meteorological, hydrological and nutrient conditions of the formation of K. mikimotoi bloom during the late spring and early summer of 2012 in the Sansha Bay were analyzed. Combined with laboratory experiment, the correlation between the formation of K. mikimotoi bloom and the environmental factors were discussed in this study. The results show that K. mikimotoi bloom usually occurs in the sea water with temperature and salinity ranging from 20.5-25.0℃ and 26.0-32.3, and the suitable temperature and salinity for K. mikimotoi are 22.0-25.0℃and 26.0-30.0, respectively. Pearson correlation analysis shows that the cell density of K. mikimotoi is positively correlated with chlorophyll a, inorganic phosphorus and chemical oxygen demand, and negatively correlated with transparency and ammonia nitrogen; K. mikimotoi cell has a low demand for phosphate, and the formation of bloom may be mainly affected by ammonia nitrogen in water. Based on field investigation and simulation results, comprehensive analysis shows that the stable hydrological and meteorological conditions, the inorganic nitrogen input during the early stage rainfall, as well as the lower light intensity due to continuous overcast and rainy conditions were the important conditions for the formation and maintenance of the red tide.
2018, 40(6): 113-130.
doi: 10.3969/j.issn.0253-4193.2018.06.011
Abstract:
The aim of this study was to investigate the community structure, diversity and correlation with environmental factors of the archaeal and bacterial in the surface sediments of Liaohe Estuary. Using the method of constructing 16S rRNA gene library of archaea and bacteria, application Illumina Miseq sequencing technology for sequence analysis. The results showed that the diversity of bacteria in the surface sediments of Liaohe Estuary was higher than that of archaea, and the diversity of archaea and bacteria in the nearshore was higher than that in the off-lying sea, that is, the diversity of the low salt area (0.8-7.04) was higher than that of middle salt area (13.1-20.7) and high salt area (24.2-31.5). The main archaea communities were Thaumarchaeota (72.73%) and Euryarchaeota (25.05%), while Crenarchaeota (0.001%) was found only in the low salt area. Proteobacteria (61.94%) was the dominant bacteria group, followed by Bacteroidetes (11.21%) and Acidobacteria (5.59%), other phyla, such as Cyanobacteria (3.03%) accounted for less. The redundancy (RDA) analysis between samples and environmental factors shows that:the main environmental factors affecting the distribution of archaeal community in surface sediments are as follows:NH4+ > Silt > pH > Salinity > Cond > Sand, bacterial community distribution is mainly affected by DO > Silt > Sand > Clay > TP. It can be seen that there are spatial heterogeneity in the community structure of microorganisms under different environmental conditions, and the response of different microorganisms to the same environmental conditions is different.
The aim of this study was to investigate the community structure, diversity and correlation with environmental factors of the archaeal and bacterial in the surface sediments of Liaohe Estuary. Using the method of constructing 16S rRNA gene library of archaea and bacteria, application Illumina Miseq sequencing technology for sequence analysis. The results showed that the diversity of bacteria in the surface sediments of Liaohe Estuary was higher than that of archaea, and the diversity of archaea and bacteria in the nearshore was higher than that in the off-lying sea, that is, the diversity of the low salt area (0.8-7.04) was higher than that of middle salt area (13.1-20.7) and high salt area (24.2-31.5). The main archaea communities were Thaumarchaeota (72.73%) and Euryarchaeota (25.05%), while Crenarchaeota (0.001%) was found only in the low salt area. Proteobacteria (61.94%) was the dominant bacteria group, followed by Bacteroidetes (11.21%) and Acidobacteria (5.59%), other phyla, such as Cyanobacteria (3.03%) accounted for less. The redundancy (RDA) analysis between samples and environmental factors shows that:the main environmental factors affecting the distribution of archaeal community in surface sediments are as follows:NH4+ > Silt > pH > Salinity > Cond > Sand, bacterial community distribution is mainly affected by DO > Silt > Sand > Clay > TP. It can be seen that there are spatial heterogeneity in the community structure of microorganisms under different environmental conditions, and the response of different microorganisms to the same environmental conditions is different.
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