Fluorometric discrimination technique of phytoplankton population based on wavelet analysis

The discrete excitation-emission-matrix fluorescence spectra (EEMS) at 12 excitation wavelengths (400, 430, 450, 460, 470, 490, 500, 510, 525, 550, 570, and 590 nm) and emission wavelengths ranging from 600-750 nm were determined for 43 phytoplankton species. A two-rank fluorescence spectra database was established by wavelet analysis and a fluorometric discrimination technique for determining phytoplankton population was developed. For laboratory simulatively mixed samples, the samples mixed from 43 algal species (the algae of one division accounted for 25%, 50%, 75%, 85%, and 100% of the gross biomass, respectively), the average discrimination rates at the level of division were 65.0%, 87.5%, 98.6%, 99.0%, and 99.1%, with average relative contents of 18.9%, 44.5%, 68.9%, 73.4%, and 82.9%, respectively; the samples mixed from 32 red tide algal species (the dominant species accounted for 60%, 70%, 80%, 90%, and 100% of the gross biomass, respectively), the average correct discrimination rates of the dominant species at the level of genus were 63.3%, 74.2%, 78.8%, 83.4%, and 79.4%, respectively. For the 81 laboratory mixed samples with the dominant species accounting for 75% of the gross biomass (chlorophyll), the discrimination rates of the dominant species were 95.1% and 72.8% at the level of division and genus, respectively. For the 12 samples collected from the mesocosm experiment in Maidao Bay of Qingdao in August 2007, the dominant species of the 11 samples were recognized at the division level and the dominant species of four of the five samples in which the dominant species accounted for more than 80% of the gross biomass were discriminated at the genus level; for the 12 samples obtained from Jiaozhou Bay in August 2007, the dominant species of all the 12 samples were recognized at the division level. The technique can be directly applied to fluorescence spectrophotometers and to the developing of an in situ algae fluorescence auto-analyzer for phytoplankton population.     

Fluorescence discrimination and determination technique for phytoplankton composition by Coif2 wavelet packet

An in vivo fluorescence discrimination technique for phytoplankton population was developed by using Wavelet packet transform, cluster analysis and non-negative least squares. The technique was used to analyze water samples from different sea regions. For simulative mixtures, when dominant species account for 60%, 70%, 80%, 90% at the division level, the correct discrimination ratios (CDRs) are 83.0%, 99.1%, 99.7% and 99.9% with the relative contents of 58.5%, 68.4%, 77.7% and 86.3%, respectively; when the algae dominance are 60%, 70%, 80%, 90%, 100% at the genus level, the CDRs are 86.1%, 94.9%, 95.2%, 96.8% and 96.7%, respectively. For laboratory mixtures, the CDRs are 88.1% and 78.4% at the division and genus level, respectively. For field samples, the CDRs were 91.7% and 80% at the division and genus level, respectively (mesocosm experiments), and the CDRs were 100% and 66.7% at the division and genus level, respectively (Jiaozhou Bay). The fluorometric technique was used to estimate the phytoplankton community composition and relative abundance of different classes for the April 2010 cruise in the Yellow Sea with the results agreeing with those in published papers by other authors.     

Examination of Silicate Limitation of Primary Production in Jiaozhou Bay,China Ⅱ.Critical Value and Time of Silicate Limitation and Satisfaction of the Phytoplankton Growth

Analysis and comparison of Jiaozhou Bay data collected from May 1991 to February 1994 revealed the spatiotemporal variations of the ambient Si(OH)₄:NO₃ (Si:N) concentration rations and the seasonal variations of (Si:N) ratios in Jiaozhou Bay and showed that the Si:N ratios were <1 throughout Jiaozhou Bay in spring, autumn, and winter. These results provide further evidence that silicate limits the growth of phytoplankton (i.e. diatoms) in spring, autumn and winter. Moreover, comparison of the spatiotemporal variations of the Si:N ratio and primary production in Jiaozhou Bay suggested their close relationship. The spatiotemporal pattern of dissolved silicate matched well that of primary production in Jiaozhou Bay. Along with the environmental change of Jiaozhou Bay in the last thirty years, the N and P concentrations tended to rise, whereas Si concentration showed cyclic seasonal variations. With the variation of nutrient Si limiting the primary production in mind, the authors found that the range of values of primary production is divided into three parts: the basic value of Si limited primary production, the extent of Si limited primary production and the critical value of Si limited primary production, which can be calculated for Jiaozhou Bay by Equations (1), (2) and (3), showing that the time of the critical value of Si limitation of phytoplankton growth in Jiaozhou Bay is around November 3 to November 13 in autumn; and that the time of the critical value of Si satisfaction of phytoplankton growth in Jiaozhou Bay is around May 22 to June 7 in spring. Moreover, the calculated critical value of Si satisfactory for phytoplankton growth is 2.15–0.76 μmol/L and the critical value of Si limitation of phytoplankton growth is 1.42–0.36 μmol/L; so that the time period of Si limitation of phytoplankton growth is around November 13 to May 22 in the next year; the time period of Si satisfactory for phytoplankton growth is around June 7 to November 3. This result also explains why critical values of nutrient silicon affect phytoplankton growth in spring and autumn are different in different waters of Jiaozhou Bay and also indicates how the silicate concentration affects the phytoplankton assemblage structure. The dilution of silicate concentration by seawater exchange affects the growth of phytoplankton so that the primary production of phytoplankton declines outside Jiaozhou Bay earlier than inside Jiaozhou Bay by one and half months. This study showed that Jiaozhou Bay phytoplankton badly need silicon and respond very sensitively and rapidly to the variation of silicon. This study was funded by NSFC (No. 40036010) and subsidized by Special Funds from National Key Basic Research Program of P. R. China (G19990437), the Postdoctoral Foundation of Ocean University of Qingdao, the Director's Foundation of the Beihai Monitoring Center of the State Oceanic Administration and the Foundation of Shanghai Fisheries University.     

EXAMINATION OF SILICATE LIMITATION OF PRIMARY PRODUCTION IN JIAOZHOU BAY, CHINA I. SILICATE BEING A LIMITING FACTOR OF PHYTOPLANKTON PRIMARY PRODUCTION

ＩＮＴＲＯＤＵＣＴＩＯＮＴｈｅｐｒｏｄｕｃｔｉｏｎｏｆｐｈｙｔｏｐｌａｎｋｔｏｎｉｓｔｈｅｆｉｒｓｔｔａｃｈｅｉｎｔｈｅｐｒｏｄｕｃｔｉｏｎｂｙｍａｒｉｎｅｏｒｇａｎｉｓｍｓａｎｄｉｎｔｈｅｍａｒｉｎｅｆｏｏｄｃｈａｉｎ .Ｋｎｏｗｌｅｄｇｅｏｆｐｒｉｍａｒｙｐｒｏｄｕｃｔｉｏｎｉｎｍａｒｉｎｅｗａｔｅｒｓｉｓｐｒｅｒｅｑｕｉｓｉｔｅｆｏｒｅｘｐｌｏｉｔａｔｉｏｎａｎｄｍａｎａｇｅｍｅｎｔｏｆｔｈｅｏｃｅａｎ’ｓｌｉｖｉｎｇｒｅｓｏｕｒｃｅｓ.Ｔｈｅｐｒｉｍａｒｙｐｒｏｄｕｃｔｉｏｎｉｎｍａｒｉｎ…     

EXAMINATION OF SILICATE LIMITATION OF PRIMARY PRODUCTION IN JIAOZHOU BAY, CHINA Ⅰ. SILICATE BEING A LIMITING FACTOR OF PHYTOPLANKTON PRIMARY PRODUCTION

Jiaozhou Bay data collected from May 1991 to February 1994, in 12 seasonal investigations, and provided the authors by the Ecological Station of Jiaozhou B ay, were analyzed to determine the spatiotemporal variations in temperature, light, nutrients (NO-3-N, NO-2-N, NH+4-N, SiO2-3-Si, PO3-4-P), phytoplankton, and primary production in Jiaozhou Bay. The results indicated that only silicate correlated well in time and space with, and had important effects on, the characteristics, dynamic cycles and trends of, primary production in Jiaozhou Bay. The authors developed a corresponding dynamic model of primary production and silicate and water temperature. Eq.(1) of the model shows that the primary production variation is controlled by the nutrient Si and affected by water temp erature; that the main factor controlling the primary production is Si; that water temper ature affects the composition of the structure of phytoplankton assemblage; that the different populations of the phytoplankton assemblage occupy different ecologica l niches for C, the apparent ratio of conversion of silicate in seawater into phytoplankton biomas and D, the coefficient of water temperature's effect on phytoplankton biomass. The authors researched the silicon source of Jiaozhou Bay , the biogeochemical sediment process of the silicon, the phytoplankton predominan t species and the phytoplankton structure. The authors considered silicate a limit ing factor of primary production in Jiaozhou Bay, whose decreasing concentration of silicate from terrestrial source is supposedly due to dilution by current and up take by phytoplankton; quantified the silicate assimilated by phytoplankton, the intrins ic ratio of conversion of silicon into phytoplankton biomass, the proportion of silicate uptaken by phytoplankton and diluted by current; and found that the primary production of the phytoplankton is determined by the quantity of the silicate assimilated by them. The phenomenon of apparently high plant-nutrient concentrations but low phytoplankton biomass in some waters is reasonably explained in this paper.     

Influence of Seawater Temperature on Phytoplankton Growth in Jiaozhou Bay, China

The phytoplankton reproduction capacity (PRC), as a new concept regarding chlorophyll-a and primary production (PP) is described. PRC is different from PP, carbon assimilation number (CAN) or photosynthetic rate ( P^B ) . PRC quantifies phytoplankton growth with a special consideration of the effect of seawater temperature. Observation data in Jiaozhou Bay, Qingdao, China, collected from May 1991 to February 1994 were used to analyze the horizontal distribution and seasonal variation of the PRC in Jiaozhou Bay in order to determine the characteristics, dynamic cycles and trends of phytoplankton growth in Jiaozhou Bay; and to develop a corresponding dynamic model of seawater temperature vs. PRC. Simulation curves showed that seawater temperature has a dual function of limiting and enhancing PRC. PRC‘s periodicity and fluctuation are similar to those of the seawater temperature. Nutrient silicon in Jiaozhou Bay satisfies phytoplankton growth from June 7 to November 3. When nutrients N, P and Si satisfy the phytoplankton growth and solar irradiation is sufficient, the PRC would reflect the influence of seawater temperature on phytoplankton growth. Moreover, the result quantitatively explains the scenario of one-peak or two-peak phytoplankton reproduction in Jiaozhou Bay, and also quantitatively elucidates the internal mechanism of the one- or two-peak phytoplankton reproduction in the global marine areas.     

Examination of Silicate Limitation of Primary Production in Jiaozhou Bay, North ChinaⅢ.Judgment Method, Rules and Uniqueness of Nutrient Limitation Among N, P, and Si

ＩＮＴＲＯＤＵＣＴＩＯＮＮａｎｄＰｉｎｐｕｔｔｅｄｉｎｔｏＪｉａｏｚｈｏｕＢａｙｂｙｒｉｖｅｒｓａｎｄｂｙｓｅｗａｇｅｅｆｆｌｕｅｎｔｓｏｆｃｉｔｉｅｓ ,ｈａｖｅｍａｄｅｔｈｅＢａｙｂｅｃｏｍｅｍｏｒｅａｎｄｍｏｒｅｅｕｔｒｏｐｈｉｃｄａｙｂｙｄａｙ .Ｓｈｅｎ ( 1994)ｔｈｏｕｇｈｔｔｈａｔｐｈｙｔｏｐｌａｎｋｔｏｎｇｒｏｗｔｈｗａｓｌｉｍｉｔｅｄｂｙｔｈｅｃｈａｎｇｅｆｒｏｍｎｉｔｒｏｇｅｎｔｏｐｈｏｓｐｈｏｒｏｕｓ ;ａｎｄｔｈａｔｔｈｅｓｉｌｉｃａｔｅｃｏｎｃｅｎｔｒａｔｉｏｎｉｎＪｉａｏｚｈ…     

Silicon limitation on primary production and its destiny in Jiaozhou Bay, China VIII: The variation of atmospheric carbon caused by both phytoplankton and human

Statistical analysis on data collected in the Jiaozhou Bay (Shandong, China) from May 1991 to February 1994 and those collected in Hawaii from March 1958 to December 2007 shows dynamic and cyclic changes in atmospheric carbon in the Northern Pacific Ocean (NPO), as well as the variation in space-time distribution of phytoplankton primary production and atmospheric carbon in the study regions. The study indicates that the human beings have imposed an important impact on the changing trends of the atmospheric carbon. Primary production in the Jiaozhou Bay presents a good example in this regard. In this paper, dynamic models of the atmospheric carbon in the NPO, the cyclic variations in the atmospheric carbon, and primary production in the Jiaozhou Bay are studied with simulation curves presented. A set of equations were established that able to calculate the rate and acceleration of increasing carbon discharged anthropologically into the atmosphere and the conversion rate of phytoplankton to atmospheric carbon. Our calculation shows that the amount of atmospheric carbon absorbed by one unit of primary production in the Jiaozhou Bay is (3.21−9.74)×10⁻⁹/(mgC·m⁻²d⁻¹), and the amount of primary production consumed by a unit of atmospheric carbon is 102.66–311.52 (mgC·m⁻²d⁻¹/10⁻⁶). Therefore, we consider that the variation of atmospheric carbon is a dynamic process controlled by the increase of carbon compound and its cyclic variation, and those from anthropologic discharge, and phytoplankton growth.     

Examination of Silicate Limitation of Primary Production in Jiaozhou Bay,North China：Ⅲ.Judgment Method ,Rules and Uniqueness of Nutrient Limitation Among N,P,and Si

Analysis and comparison of Jiaozhou Bay data collected from May 1991 to February 1994 (12 seasonal investigations) provided by the Ecological Station of Jiaozhou Bay revealed the characteristic spatiotemporal variation of the ambient concentration Si∶DIN and Si∶16P ratios and the seasonal variation of Jiaozhou Bay Si∶DIN and Si∶16P ratios showing that the Si∶DIN ratios were <1 throughout the year in Jiaozhou Bay; and that the Si∶16P ratios were <1 throughout Jiaozhou Bay in spring, autumn and winter. The results proved that silicate limited phytoplankton growth in spring, autumn and winter in Jiaozhou Bay. Analysis of the Si∶DIN and Si∶P ratios showed that the nutrient Si has been limiting the growth of phytoplankton throughout the year in some Jiaozhou Bay waters; and that the silicate deficiency changed the phytoplankton assemblage structure. Analysis of discontinuous 1962 to 1998 nutrient data showed that there was no N or P limitation of phytoplankton growth in that period. The authors consider that the annual cyclic change of silicate limits phytoplankton growth in spring, autumn and winter every year in Jiaozhou Bay; and that in many Jiaozhou Bay waters where the phytoplankton as the predominant species need a great amount of silicate, analysis of the nutrients N or P limitation of phytoplankton growth relying only on the N and P nutrients and DIN∶P ratio could yield inaccurate conclusions. The results obtained by applying the rules of absolute and relative limitation fully support this view. The authors consider that the main function of nutrient silicon is to regulate and control the mechanism of the phytoplankton growth process in the ecological system in estuaries, bays and the sea. The authors consider that according to the evolution theory of Darwin, continuous environmental pressure gradually changes the phytoplankton assemblage's structure and the physiology of diatoms. Diatoms requiring a great deal of silicon either constantly decrease or reduce their requirement for silicon. This will cause a series of huge changes in the ecosystem so that the whole ecosystem requires continuous renewal, change and balancing. Human beings have to reduce marine pollution and enhance the capacity of continental sources to transport silicon to sustain the continuity and stability in the marine ecosystem. This study was funded by the NSFC (No. 40036010) and subsidized by Special Funds from the National Key Basic Research Program of P. R. China (G199990437), the Postdoctoral Foundation of Ocean University of Qingdao, the Director's Foundation of the Beihai Monitoring Center of the State Oceanic Administration and the Foundation of Shanghai Fisheries University.     

EXAMINATION OF SILICATE LIMITATION OF PRIMARY PRODUCTION IN JIAOZHOU BAY, CHINA——I. SILICATE BEING A LIMITING FACTOR OF PHYTOPLANKTON PRIMARY PRODUCTION

Jiaozhou Bay data collected from May 1991 to February 1994, in 12 seasonal investigations, and provided the authors by the Ecological Station of Jiaozhou Bay, were analyzed to determine the spatiotemporal variations in temperature, light, nutrients (NO3^--N, NO2^--N, NH4^ -N, SIO3^2--Si, PO4^3--P), phytoplankton, and primary production in Jiaozhou Bay. The results indicated that only silicate correlated well in time and space with, and had important effects on, the characteristics, dynamic cycles and trends of, primary production in Jiaozhou Bay. The authors developed a corresponding dynamic model of primary production and silicate and water temperature. Eq. ( 1 ) of the model shows that the primary production variation is controlled by the nutrient Si and affected by water temperature; that the main factor controlling the primary production is Si; that water temperature affects the composition of the structure of phytoplankton assemblage; that the different populations of the phytoplankton assemblage occupy different ecological niches for C, the apparent ratio of conversion of silicate in seawater into phytoplankton biomas and D, the coefficient of water temperature‘s effect on phytoplankton biomass. The authors researched the silicon source of Jiaozhou Bay, the biogeochemical sediment process of the silicon, the phytoplankton predominant species and the phytoplankton structure. The authors considered silicate a limiting factor of primary production in Jiaozhou Bay, whose decreasing concentration of silicate from terrestrial source is supposedly due to dilution by current and uptake by phytoplankton; quantified the silicate assimilated by phytoplankton, the intrinsic ratio of conversion of silicon into phytoplankton biomass, the proportion of silicate uptaken by phytoplankton and diluted by current; and found that the primary production of the phytoplankton is determined by the quantity of the silicate assimilated by them. The phenomenon of apparently high plant-nutrient concentTations but low phytoplankton biomass in some waters is reasonably explained in this paper.     

Silicon limitation on primary production and its destiny in Jiaozhou Bay, China——Ⅳ：Study on cross-bay transect from estuary to ocean

The authors analyzed the data collected in the Ecological Station Jiaozhou Bay from May 1991 to November 1994, including 12 seasonal investigations, to determine the characteristics, dynamic cycles and variation trends of the silicate in the bay. The results indicated that the rivers around Jiaozhou Bay provided abundant supply of silicate to the bay. The silicate concentration there depended on river flow variation. The horizontal variation of silicate concentration on the transect showed that the silicate concentration decreased with distance from shorelines. The vertical variation of it showed that silicate sank and deposited on the sea bottom by phytoplankton uptake and death, and zooplankton excretion. In this way, silicon would endlessly be transferred from terrestrial sources to the sea bottom. The silicon took up by phytoplankton and by other biogeochemical processes led to insufficient silicon supply for phytoplankton growth. In this paper, a 2D dynamic model of river flow versus silicate concentration was established by which silicate concentrations of 0.028–0.062 μmol/L in seawater was yielded by inputting certain seasonal unit river flows (m³/s), or in other words, the silicate supply rate; and when the unit river flow was set to zero, meaning no river input, the silicate concentrations were between 0.05–0.69 μmol/L in the bay. In terms of the silicate supply rate, Jiaozhou Bay was divided into three parts. The division shows a given river flow could generate several different silicon levels in corresponding regions, so as to the silicon-limitation levels to the phytoplankton in these regions. Another dynamic model of river flow versus primary production was set up by which the phytoplankton primary production of 5.21–15.55 (mgC/m²·d)/(m³/s) were obtained in our case at unit river flow values via silicate concentration or primary production conversion rate. Similarly, the values of primary production of 121.98–195.33 (mgC/m²·d) were achieved at zero unit river flow condition. A primary production conversion rate reflects the sensitivity to silicon depletion so as to different phytoplankton primary production and silicon requirements by different phytoplankton assemblages in different marine areas. In addition, the authors differentiated two equations (Eqs. 1 and 2) in the models to obtain the river flow variation that determines the silicate concentration variation, and in turn, the variation of primary production. These results proved further that nutrient silicon is a limiting factor for phytoplankton growth. This study was funded by NSFC (No. 40036010), and the Director's Fund of the Beihai Sea Monitoring Center, the State Oceanic Administration.     

Assessment of phytoplankton class abundance using fluorescence excitation-emission matrix by parallel factor analysis and nonnegative least squares

The feasibility of using fluorescence excitation-emission matrix (EEM) along with parallel factor analysis (PARAFAC) and nonnegative least squares (NNLS) method for the differentiation of phytoplankton taxonomic groups was investigated. Forty-one phytoplankton species belonging to 28 genera of five divisions were studied. First, the PARAFAC model was applied to EEMs, and 15 fluorescence components were generated. Second, 15 fluorescence components were found to have a strong discriminating capability based on Bayesian discriminant analysis (BDA). Third, all spectra of the fluorescence component compositions for the 41 phytoplankton species were spectrographically sorted into 61 reference spectra using hierarchical cluster analysis (HCA), and then, the reference spectra were used to establish a database. Finally, the phytoplankton taxonomic groups was differentiated by the reference spectra database using the NNLS method. The five phytoplankton groups were differentiated with the correct discrimination ratios (CDRs) of 100% for single-species samples at the division level. The CDRs for the mixtures were above 91% for the dominant phytoplankton species and above 73% for the subdominant phytoplankton species. Sixteen of the 85 field samples collected from the Changjiang River estuary were analyzed by both HPLC-CHEMTAX and the fluorometric technique developed. The results of both methods reveal that Bacillariophyta was the dominant algal group in these 16 samples and that the subdominant algal groups comprised Dinophyta, Chlorophyta and Cryptophyta. The differentiation results by the fluorometric technique were in good agreement with those from HPLC-CHEMTAX. The results indicate that the fluorometric technique could differentiate algal taxonomic groups accurately at the division level.     

COUPLED PHYSICAL-ECOLOGICAL MODELLING IN THE CENTRAL PART OF JIAOZHOU BAY Ⅱ.COUPLED WITH AN ECOLOGICAL MODEL

Sharpies‘ 1-D physical rrozlel maploying tide-wind driven turbulence closure and surface heating-cooling physics, was coupled with an eculogical rnodet with 9-biochemical components: phytoplankton, zooplankton, shellfish, autotmphic and heterotrophic bacterioplankton, dissolved organic carbon (DOC), suspended detritus and sinking particles to simulate the armual evolution of ecosystem in thecentral part of Jiaozhou Bay. The coupled modeling results showed that the phytoplankton shading effectcould reduce seawater temperamre by 2℃, so that photosynthesis efficiency should be less than 8% ; that the loss of phytoplankton by zooplankton grazing in winter tended to be compensated by phytoplankton advection and diffusion from the otrtside of the Bay; that the incidem irradiance intensity could be the mostimportant factor for phytoplankton grcr, wth rate; and that it was the bacterial secondary prnduction that maintained the maximum zooplankton biomass in winter usually observed in the 1990s, indicating that themicrobial food loop was extremely important for ecosystem study of Jiaozhou Bay.     

Inorganic Elemental Determinations of Marine Traditional Chinese Medicine Meretricis concha from Jiaozhou Bay:The construction of Inorganic Elemental Fingerprint Based on Chemometric Analysis

The goal of this paper is to explore the relationship between the inorganic elemental fingerprint and the geographical origin identification of Meretricis concha,which is a commonly used marine traditional Chinese medicine(TCM) for the treatment of asthma and scald burns.For that,the inorganic elemental contents of Meretricis concha from five sampling points in Jiaozhou Bay have been determined by means of inductively coupled plasma optical emission spectrometry,and the comparative investigations based on the contents of 14 inorganic elements(Al,As,Cd,Co,Cr,Cu,Fe,Hg,Mn,Mo,Ni,Pb,Se and Zn) of the samples from Jiaozhou Bay and the previous reported Rushan Bay were performed.It has been found that the samples from the two bays are approximately classified into two kinds using hierarchical cluster analysis,and a four-factor model based on principle component analysis could explain approximately 75% of the detection data,also linear discriminant analysis can be used to develop a prediction model to distinguish the samples from Jiaozhou Bay and Rushan Bay with accuracy of about 93%.The results of the present investigation suggested that the inorganic elemental fingerprint based on the combination of the measured elemental content and chemometric analysis is a promising approach for verifying the geographical origin of Meretricis concha,and this strategy should be valuable for the authenticity discrimination of some marine TCM.     

Examination of Daytime Length''''s Influence on Phytoplankton Growth in Jiaozhou Bay, China

1　INTRODUCTIONSystematicstudyisusefulforhumanvisualizationandcomprehensionofanetworkofcomplicatedcompo nentsandprocessesinvolvingfrequentenergyflow ,consideringenergyasthebasisofbothstructureandprocess (Automa ,1 993) .Energylanguageisaconceptfordepictingasysteminwhichallphenomenaareac companiedbyenergytransformation .Thefunctionoftheecosystemovertheworlddependsontheenergyfixationbymarineplantphotosynthesis ,mostofthemarefixedbymicrophytoplanktonnearseasurfaceexposedtosunlight (Niebaken …     

Examination of Daytime Length＇s Influence on Phytoplankton Growth in Jiaozhou Bay, China

This study showed how the daytime length in Jiaozhou Bay affected the water temperature, which in turn affected the phytoplankton growth when solar radiation was sufficient for phytoplankton photosynthesis. Jiaozhou Bay observation data collected from May 1991 to February 1994 were used to analyze the daytime length vs water temperature relationship. Our study showed that daytime length and the variation controlled the cycle of water temperature flunctuation. Should the cyclic variation curve of the daytime length be moved back for two months it would be superimposed with temperature change. The values of daytime length and temperature that calculated in the dynamical model of daytime length lag vs water temperature were consistent with observed values. The light radiation and daytime length in this model determined the photochemistry process and the enzymic catalysis process of phytoplankton photosynthesis. In addition, by considering the effect of the daytime length on water temperature and photosynthesis, we could comprehend the joint effect of daytime length, water temperature, and nutrients, on the spatiotemperal variation of primary production in Jiaozhou Bay.     

Biogenic silicate accumulation in sediments, Jiaozhou Bay

1 INTRODUCTION Silicate, or silicic acid (H4SiO4), is a very im- portant nutrient in the ocean. Unlike other major nu- trients such as phosphate and nitrate or ammonium, which are needed by almost all marine plankton, silicate is an essential chemical req…     

Comparison in diversity of eukaryotic algae in surface sediments from different functional sea areas of Qingdao coast,the Yellow Sea,China: a metabarcoding approach

Journal of Oceanology and Limnology - Surface sediment samples were collected in three different functional sea areas in Qingdao coast, East China, including the inner Jiaozhou Bay, the Laoshan...     

Chlorophyll fluorescence extraction from water-leaving radiance of algae-containing water through polarization

When measuring reflectance spectra, it is very important to accurately extract chlorophyll fluorescence from elastic- scattering light in water-leaving radiance. The elastic scattering of light by water particles produces partially polarized light. In contrast, chlorophyll fluorescence in planktonic algae yields completely unpolarized light. These properties can be used to separate fluorescent signals from the water-leaving radiance and thus to determine chlorophyll concentration. The algal species Aureococcus anophagefferens was used to conduct a laboratory polarization experiment. For the tests, we used a field spectroradiometer and a polarizer; measurements were collected using two different observation modes. The chlorophyll fluorescence curve extracted through polarization shows an excellent match with the results obtained using the fluorospectro photometer for both measurement modes, suggesting that polarization-based chlorophyll fluorescence extraction may be feasible. The extracted fluorescence is more reliable at incident zenith angles ranging from 30° to 60°. For algae-containing water, the results improve with increasing chlorophyll concentration. This method could help improve chlorophyll concentration measurement and the remote-sensing detection of resulting harmful algae blooms.     

Environmental capacity of petroleum hydrocarbon pollutants in Jiaozhou Bay, China: Modeling and calculation

An environmental capacity model for the petroleum hydrocarbon pollutions (PHs) in Jiaozhou Bay is constructed based on field surveys, mesocosm, and parallel laboratory experiments. Simulated results of PHs seasonal successions in 2003 match the field surveys of Jiaozhou Bay resaonably well with a highest value in July. The Monte Carlo analysis confirms that the variation of PHs concentration significantly correlates with the river input. The water body in the bay is reasonably subjected to self-purification processes, such as volatilization to the atmosphere, biodegradation by microorganism, and transport to the Yellow Sea by water exchange. The environmental capacity of PHs in Jiaozhou Bay is 1500 tons per year IF the seawater quality criterion (Grade Ⅰ/Ⅱ, 0.05 mgL-1) in the region is to be satisfied. The contribution to self-purification by volatilization, biodegradation, and transport to the Yellow Sea accounts for 48%, 28%, and 23%, respectively, which make these three processes the main ways of PHs purification in Jiaozhou Bay.