A bio-optical inversion model to retrieve absorption contributions and phytoplankton size structure from total minus water spectral absorption using genetic algorithm

We propose a bio-optical inversion model that retrieves the absorption contributions of phytoplankton and colored detrital matter(CDM),as well as the phytoplankton size classes(PSCs),from total minus water absorption spectra.The model is based on three-component separation of phytoplankton size structure and a genetic algorithm.The model performance was tested on two independent datasets(the NASA bio-Optical Marine Algorithm Dataset(NOMAD) and the northern South China Sea(NSCS) dataset).The relationships between the estimated and measured values were strongly linear,especially for aCDM(412),and the Root Mean Square Error(RMSE) of the CDM exponential slope(SCDM) was relatively low.Next,the inversion model was directly applied to in-situ total minus water absorption spectra determined by an underwater meter during a cruise in September 2008,to retrieve the phytoplankton size structure in the seawater.By comparing the measured and retrieved chlorophyll a concentrations,we demonstrated that total and size-specific chlorophyll a concentrations could be retrieved by the model with relatively high accuracy.Finally,we applied the bio-optical inversion model to investigate changes in phytoplankton size structure induced by an anti-cyclonic eddy in the NSCS.     

Measurement and feature analysis of absorption spectra of four algal species

Two methods for particulate pigments(i.e.,quantitative filter technique,QFT,and in vivo measurement,InVivo,respectively)and two methods for dissolved pigments(i.e.,Acetone Extracts,AceEx,and high-performance liquid chromatography,HPLC,respectively) were used to obtain the optical absorption coefficient spectra for cultures of four typical algal species.Through normalization and analysis of the spectra,it is shown that(1) the four methods are able to measure optical absorption spectra of particulate and/or dissolved pigments;(2)that the optical absorption spectra of particulate and dissolved pigments were consistent in terms of the peak position in the blue wavelength,and the difference of the peak position in the near infrared wavelength was ~10nm between each other;and(3)that the leveling effect of the absorption spectra of particulate pigments was significant.These four methods can all effectively measure the absorption coefficients of phytoplankton pigments,while each one has its unique advantages in different applications.Therefore,appropriate method should be carefully selected for various application due to their intrinsic difference.     

Determination of the spatial and temporal variability of phytoplankton community structure in Daya Bay via HPLC-CHEMTAX pigment analysis

The spatial and temporal variability of the phytoplankton community structure in Daya Bay, South China Sea, were identified by using HPLC-CHEMTAX analytical techniques. The highest chlorophyll a(Chl a) concentrations were observed during summer(with an average value of 0.84 μg/L) and lowest ones during winter(with an average value of 0.33 μg/L). CHEMTAX processing revealed the seasonal succession of phytoplankton species in Daya Bay. During winter, diatoms were the dominant phytoplankton species and contributed 41.5% to total Chl a. Based on Chl a concentration, the average ratio of dinofl agellates to total phytoplankton biomass substantially increased with increasing temperature and nitrogen to phosphorus(N/P) ratio, reaching 52.2% in spring. Nutrient limitation shifted from phosphorus to nitrogen during summer. Moreover, this period was associated with the predominance of diatoms, which accounted for 71.1% of Chl a. Prasinophytes and cryptophytes were the other two dominant groups and particularly dominated during winter. Cyanobacteria became an important group during summer and autumn. Canonical correspondence analysis suggested that chrysophytes, dinofl agellates, and cryptophytes were strongly associated with high nitrate concentration, ammonium, dissolved inorganic nitrogen(DIN), and N/P ratio, and were negatively associated with temperature and phosphate. Diatoms and cyanobacteria were strongly associated with temperature, phosphate, and salinity, and are negatively influenced by nitrate, ammonium, DIN, and N/P ratio. Microscopic observations and pigment HPLC information were in good agreement for diatoms and dinofl agellates in the bay. This study demonstrated the usefulness of pigment analysis in investigating the distribution of phytoplankton groups in a complex physical environment, such as Daya Bay.     

Characteristics of phytoplankton community structure during and after a bloom of the dinoflagellate Scrippsiella trochoidea by HPLC pigment analysis

A bloom of the dinoflagellate Scrippsiella trochoidea was detected for the first time in inner Tolo Harbor, Hong Kong in 2 000. Water samples were collected at eight stations along a transect passing through a red tide patch for microscopic analysis of phytoplankton composition and high-performance liquid chromatography (HPLC) analysis of phytoplankton pigments. During the bloom, the density of dinoflagellates was 1.1×10⁶ cells L⁻¹ within the patch and 8.6×10⁵ cells L⁻¹ outside the patch where the phytoplankton community was dominated by diatoms. After the bloom the S. trochoidea began to decrease in density and was replaced by diatoms as the dominating bloom-causing organisms at all stations, and the density of dinoflagellates at most stations was less than 1.0 × 10⁶ cells L⁻¹. The status of S. trochoidea as the causative species of the bloom was indicated by the presence of peridinin, the marker pigment for dinoflagellates. The shift from dinoflagellates to diatoms was marked by the decline of peridinin and the prevalence of fucoxanthin. Phytoplankton pigment markers also revealed the presence of other minor phytoplankton assemblages such as cryptomonads and blue-green algal.     

Multiple excitation wavelength fluorescence emission spectra technique for discrimination of phytoplankton

In vivo fluorescence methods are efficient tools for studying the distribution of phytoplankton in nature.Different algae species usually have different pigments with different ratios,which results in different fluorescence emission spectra.Based on multiple excitation wavelength fluorescence emission spectra,a discrimination technique is established in this study.The discrimination method,established by multivariate linear regression and weighted least-squares,was used to differentiate the samples cultured in the laboratory and collected from Jiaozhou Bay near Qingdao at the division level.The correctly discriminated samples were ≥ 86% for single algae samples,≥ 88% for simulatively mixed ones,≥ 91% for physically mixed ones and 100% for samples collected from Jiaozhou Bay.The result in this research is more definite for the physically mixed samples in the laboratory.The method described here can be employed to monitor the phytoplankton population in the marine environment.     

The absorption of water color components and spectral modes in the Pearl River estuary

In-situ data from cruises in the Pearl River estuary and adjacent marine areas were collected during March to May 2001. The absorption coefficients of the water color components were studied in detail containing total suspended matter (TSM), chlorophyll-a (chl-a), colored dissolved organic matter (CDOM), and de-pigment particles. For absorption coefficient of TSM, ap, and that of de-pigment particles, ad, correlations of ap(440)-TSM, ad(440)-TSM, ap(440)-chl-a and ad-chl-a were done (the italicized term means the concentration). There was a good correlation between ap(440) and chl-a concentration. An empirical relationship model between aph(675) and chl-a was developed showing a strong correlation of 0.93. Based on the two models the chl-a and aph(λ) were correlated. The values of calculated empirical spectral slope for CDOM absorption coefficients and that of de-pigment particles, 0.017 0 and 0.011 6 respectively, both are within a relative standard error of 10.0%.     

Phytoplankton size class derived from phytoplankton absorption and chlorophyll-a concentrations in the northern South China Sea

A previously developed model was modified to derive three phytoplankton size classes (micro-, nano-, and pico-phytoplankton) from the overall chlorophyll-a concentration, assuming that each class has a specific absorption coefficient. The modified model performed well using in-situ data from the northern South China Sea, and the results were reliable and accurate. The relative errors of the size-fractioned chlorophyll-a concentration for each size class were: micro-: 21%, nano-: 41%, pico-: 26%, and nano+pico: 23%. The model was then applied on ocean color remote sensing data to examine the distribution and variation of phytoplankton size classes in northern South China Sea on a large scale.     

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.     

Characterization of water constituents spectra absorption in Chagan Lake of Jilin Province, Northeast China

Research on the optical characteristics of water color constituents in Chagan Lake of Jilin Province,Northeast China was carried out in order to investigate the variability of the spectra absorption parameters as inputs to bio-optical models and remote sensing algorithms for converting observed spectral signals into water quality information.Samples of total particulates,non-algal particles and colored dissolved organic matter (CDOM) were first prepared by quantitative filter technique (QFT) and then absorp...     

Reanalysis of principal component analysis to resume past vegetation and environment

In the paper 11 pollen types were selected from the original pollen and spore records of 54 samples in Fenzhuang profile of Beijing region, then 54 × 11 matrix was set up. Based on the pollen data of Fenzhuang profile from the Late Pleistocene to the Early Holocene, the paper gives a further analysis to subdivide zone of the pollen assemblages and changes of paleovegetation and paleoenvironment in this area using principal component analysis (PCA). PCA can play an complementary role for subdividing zone, at the same time, it can eliminate the difference to subdivide zone of the pollen assemblages caused by artificial factors. Finally to the biodiversity in plant communities and complex geographical environment in Beijing region, using great dispersal of accumulative percent of total in PCA (for cumulative rate only 57% from the first three factors of PCA), may sufficiently correspond to the environmental characteristic, so as to recover past climate condition much better. Supported by National Natural Science Foundation of China (No. 49571066, 39470132).     

Reanalysis of principal component analysis to resume past vegetation and environment

In the paper 11 pollen types were selected from the original pollen and spore records of 54 samples in Fenzhuang profile of Beijing region, then 54 × 11 matrix was set up. Based on the pollen data of Fenzhuang profile from the Late Pleistocene to the Early Holocene, the paper gives a further analysis to subdivide zone of the pollen assemblages and changes of paleovegetation and paleoenvironment in this area using principal component analysis (PCA). PCA can play an complementary role for subdividing zone, at the same time, it can eliminate the difference to subdivide zone of the pollen assemblages caused by artificial factors. Finally to the biodiversity in plant communities and complex geographical environment in Beijing region, using great dispersal of accumulative percent of total in PCA (for cumulative rate only 57% from the first three factors of PCA), may sufficiently correspond to the environmental characteristic, so as to recover past climate condition much better.     

鸢乌贼和杜氏枪乌贼营养成分分析与比较

分析鸢乌贼(Symplectoteuthis oualaniensis)和杜氏枪乌贼(Loligo duvauceli)头足和胴体的营养成分。结果表明,鸢乌贼头足、胴体粗蛋白质量分数(干基)分别为90.76%、90.58%,杜氏枪乌贼头足、胴体粗蛋白质量分数低于鸢乌贼。必须氨基酸占总氨基酸质量分数的高低顺序为杜氏枪乌贼胴体41.40%杜氏枪乌贼头足38.91%鸢乌贼头足32.25%鸢乌贼胴体38.04%。鸢乌贼头足、胴体的第一限制氨基酸均为缬氨酸,氨基酸评分AAS分别为85、76;杜氏枪乌贼头足的第一限制氨基酸为蛋氨酸,AAS为98,胴体的AAS值大于100。鸢乌贼头足、胴体分别检测出12种和11种不饱和脂肪酸,杜氏枪乌贼头足、胴体各检测出13种,两种乌贼的头足和胴体不饱和脂肪酸占总脂肪酸质量分数均高于65%。与其他鱿鱼相比较,鸢乌贼的DHA含量较高。鸢乌贼富含Mg、Zn,杜氏枪乌贼则富含Ca、Cu、Mn。     

Digital Spectra and Analysis of Altitudinal Belts in Tianshan Mountains, China

Based on the framework of the geo-info spectra of montane altitudinal belts, this paper firstly reviews six classification systems for the spectra of mountain altitudinal belts in China and considers that detailed regional study of altitudinal belts is the key for reaching standardization and systemization of mountain altitudinal belts. Only can this further identify and resolve problems with the study of altitudinal belts. The factors forming the spectra of altitudinal belts are analyzed in the Tianshan Mountains of China, and a digital altitudinal belt system is constructed for the northern flank, southern flank, the heartland, and Ili valley in the west. The characteristics of each belt are revealed with a summarization of the pattern of areal differentiation of altitudinal belts.     

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.     

A research on statistical retrieval algorithms and spectral characteristics of the total absorption coefficients in the Yellow Sea and the East China Sea

1 INTRODUCTION The Yellow Sea and the East China Sea are typical coastal Case-II waters with high sediment load and complicate optical properties. The total absorption coefficient of sea water is one of the main parameters influencing the calculation of o…     

Simulation of phytoplankton biomass in Quanzhou Bay using a back propagation network model and sensitivity analysis for environmental variables

Prediction and sensitivity models,to elucidate the response of phytoplankton biomass to environmental factors in Quanzhou Bay,Fujian,China,were developed using a back propagation(BP) network.The environmental indicators of coastal phytoplankton biomass were determined and monitoring data for the bay from 2008 was used to train,test and build a three-layer BP artificial neural network with multi-input and single-output.Ten water quality parameters were used to forecast phytoplankton biomass(measured as chlorophyll-a concentration).Correlation coefficient between biomass values predicted by the model and those observed was 0.964,whilst the average relative error of the network was-3.46% and average absolute error was 10.53%.The model thus has high level of accuracy and is suitable for analysis of the influence of aquatic environmental factors on phytoplankton biomass.A global sensitivity analysis was performed to determine the influence of different environmental indicators on phytoplankton biomass.Indicators were classified according to the sensitivity of response and its risk degree.The results indicate that the parameters most relevant to phytoplankton biomass are estuary-related and include pH,sea surface temperature,sea surface salinity,chemical oxygen demand and ammonium.     

Application of principal component analysis to evaluation of black soil degradation in Jilin

Principal Component Analysis(PCA) can simplify the structure of database by replacing multi-dimensional parameters with relatively less comprehensive variables in order to ensure the minimum lost in initial data.In this paper,eighteen black soil samples from different sites were tested and thirteen distinctive indexes were chosen to evaluate the degeneration of black soil.By using principal component analysis,variables of thirteen dimensions can be diminished to six unrelated principal indexes.Analysis show...     

Application of principal component analysis to evaluation of black soil degradation in Jilin

Principal Component Analysis(PCA) can simplify the structure of database by replacing multi-dimensional parameters with relatively less comprehensive variables in order to ensure the minimum lost in initial data.In this paper,eighteen black soil samples from different sites were tested and thirteen distinctive indexes were chosen to evaluate the degeneration of black soil.By using principal component analysis,variables of thirteen dimensions can be diminished to six unrelated principal indexes.Analysis shows that the soluble salt content,Fulvic acids(FA) and aggregation degree have a high weighing coefficient,indicating these three indexes are the major parts for the evaluation of black soil degradation.It also provides a new path to the degenerated black soil treatment in Northeast China.     

Responses of phytoplankton and its satellite bacteria to exogenous ethanol

Journal of Oceanology and Limnology - The response of phytoplankton and its satellite bacteria to various concentrations (0.01%–10% v/v) of ethanol is studied. To elucidate the effect of...     

Abundance quantification by independent component analysis of hyperspectral imagery for oil spill coverage calculation

The estimation of oil spill coverage is an important part of monitoring of oil spills at sea.The spatial resolution of images collected by airborne hyper-spectral remote sensing limits both the detection of oil spills and the accuracy of estimates of their size.We consider at-sea oil spills with zonal distribution in this paper and improve the traditional independent component analysis algorithm.For each independent component we added two constraint conditions:non-negativity and constant sum.We use priority weighting by higher-order statistics,and then the spectral angle match method to overcome the order nondeterminacy.By these steps,endmembers can be extracted and abundance quantified simultaneously.To examine the coverage of a real oil spill and correct our estimate,a simulation experiment and a real experiment were designed using the algorithm described above.The result indicated that,for the simulation data,the abundance estimation error is 2.52% and minimum root mean square error of the reconstructed image is 0.030 6.We estimated the oil spill rate and area based on eight hyper-spectral remote sensing images collected by an airborne survey of Shandong Changdao in 2011.The total oil spill area was 0.224 km~2,and the oil spill rate was 22.89%.The method we demonstrate in this paper can be used for the automatic monitoring of oil spill coverage rates.It also allows the accurate estimation of the oil spill area.