由粒子吸收光谱提取浮游植物吸收光谱的人工神经网络方法

基于现场实验数据集及人工神经网络技术,论文提出了一种从海中粒子吸收光谱提取浮游植物吸收光谱的方法。这个数据集包含了海中粒子吸收光谱和对应的浮游植物吸收光谱,并被分为三个子集:训练集、印证集和试验集。本研究所利用的人工神经网络系统为多层感知器,训练后的人工神经网络的性能由印证集和试验集来评价。实验结果表明,文中所提出的方法可成功地提取浮游植物的吸收光谱,其提取精度与传统的实验方法相当。     

海洋浮游植物粒径组成及其生物粒径效应研究

海洋生态系主要由生产者、消费者和分解者构成[1],它们的群落结构和功能 ,生理、生物过程 ,以及在生态系中的物质、能量流动等在很大程度上都与生物粒径大小有关[2～4]。自20世纪60年代 ,随着生物粒径测量技术的不断完善人们提出了海洋生物粒径谱假说 ,即海洋生态系是由最小生物 (如细菌 )至最大生物 (如鲸 )组成的一个生物粒径连续分级谱[5～7]。海洋浮游植物是主要的海洋初级生产者 ,是海洋食物网(链 )的初始环节 [8],因此在生物粒径谱假说的指导下 ,人们逐渐开展了海洋浮游植物粒径组成及其影响因素 ,以及海洋浮游植物生物、化学过程粒径…     

基于浮游植物流式细胞仪对胶州湾春季浮游植物的研究

本文基于浮游植物流式细胞仪Cyto Sub对2014年春季胶州湾浮游植物功能群组成及其与环境因子的关系开展研究。Cyto Sub共检测出6个浮游植物类群,分别是聚球藻、微微型真核浮游植物、隐藻、微型单细胞藻、小型单细胞藻和链状藻。多元统计分析显示胶州湾春季浮游植物可划分为两个群落,群落1主要由湾外站位组成,浮游植物生物量浓度为15.15μg/L(以碳含量计,以下同),以小型单细胞藻、链状藻和微型单细胞藻为主;群落2主要由湾内站位组成,浮游植物生物量浓度为72.83μg/L,以链状藻为主。胶州湾的优势类群为链状藻,其丰度与水温和营养盐浓度呈显著正相关关系。与其他浮游植物粒级研究方法的比较表明,当调查海域优势种为小粒径的链状藻时,该方法能够快速、准确地测量出各个浮游植物类群的粒径参数,从而推算出浮游植物群落的粒级结构。     

基于南海北部海区浮游植物吸收光谱斜率变化的粒级结构反演

浮游植物的粒级结构是一个重要的生物参数。基于南海北部海区不同水体环境下测量的生物光学数据, 作者深入研究了粒级结构对浮游植物吸收光谱的影响。结果表明, 选择443和510nm波段计算得到的浮游植物光谱斜率S对粒级结构的变化具有较高的敏感性, 其随着小型浮游植物比例的增大呈不断增加的趋势。S与水体叶绿素a浓度、浮游植物吸收系数(aph(443))之间表现出明显的正相关特征。以40%为界对不同粒级浮游植物的优势进行定义, 发现在S与叶绿素a浓度、aph(443)的关系分布中小型(Micro)和微微型(Pico)浮游植物占据优势的水体表现出较为明显的分界, 叶绿素a浓度和aph(443)分别在0.70mg•m-3和0.05m-1附近, 相应的S在0.0004(m•nm)-1左右。基于实测数据建立的遥感反射率蓝绿波段比值与S之间的统计关系, 决定系数高达0.91, 为从水色遥感数据反演浮游植物粒级结构提供了重要手段。     

太湖水体浮游植物光谱吸收系数参数化模型研究

针对太湖水域特有藻种组成的浮游植物光谱吸收系数,利用实测数据对Ciotti光谱吸收系数模型进行改进和演化,得到新的基于藻类粒径组成(模型3)和种类组成(模型4)的太湖水体浮游植物光谱吸收系数模型。对模型进行比较发现,模型3和模型4能够较好地模拟太湖水体浮游植物的光谱吸收系数,分别适用于中、低和高叶绿素质量浓度的太湖水体浮游植物的光谱吸收系数的拟合。     

北部湾浮游植物粒径分级叶绿素a和初级生产力的分布特征

1994年5月23B至6月4日现场观测了北部湾浮游植物细胞丰度、叶绿素a浓度和初级生产力的分布.测区平均叶绿素a浓度为0.94±0.45/d3.平均初级生产力(C)为351±172mg/(m2·d),浮游植物细胞丰度为0.97×104-10050×104个/m3,鉴定浮游植物4门56属176种.地理环境和水文状况的差异使上述参数分布具有明显的区域性特征,近岸区高于湾中部,测区北部高干南部;温跃层以下水层叶绿素a浓度高于上层水,周6观测站平均叶绿素a浓度湾北部(0.47±0.15g/dm3)高于湾南部(0.15±0.02dm3).北部湾水域光合浮游生物以微型和微微型细胞(小于20m)占优势,其对总初级生产力的贡献(占91%)高于对总叶绿素a的贡献(占77%).     

罗源湾和闽南—台湾浅滩海域浮游植物的光合参数

本工作采用~(14)C示踪法,于1987～1989年现场测定了罗源湾和闵南-台湾浅滩渔场浮游植物碳同化速率。结合叶绿素和细胞含碳量的测定,描述了浮游植物光合参数的季节变化,探讨温度对同化系数和碳比积累速率的影响。结果表明,罗源湾碳比积累速率平均为0.64d~(-1),闽南-台湾浅滩渔场碳比积累速率平均为0.85d~(-1),这反映了两个海区初级生产力的差别。温度对碳比积累速率的影响可以采用Goldman和Carpenter的模式来描述。     

象山港中、西部秋季浮游植物粒径分级、叶绿素a和初级生产力

１９９４年１０月结合水色遥感光谱实验,对象山港中、西部浮游植物细胞丰度、优势种类、叶绿素ａ浓度和初级生产力的分布做了现场观测。表层水中共鉴定出浮游植物２４种,隶属３门１７属,细胞丰度为１．０５×１０４±１．１４×１０４个／ｄｍ３;叶绿素ａ浓度为１．０７±０．５９μｇ／ｄｍ３,潜在初级生产力为３．８６±３．６０ｍｇＣ／（ｍ３·ｈ）。港区西部的浮游植物细胞丰度、叶绿素ａ浓度和初级生产力均高于港区中部;表层叶绿素ａ浓度高于中层和底层。浮游植物细胞粒径分级结果表明,微型和微微型浮游植物细胞（＜２０μｍ）对总叶绿素ａ的贡献占８６％,对初级生产力的贡献占８９％;小型浮游植物细胞（＞２０μｍ）对总叶绿素ａ的贡献占１４％,对初级生产力的贡献占１１％。     

海水养殖池塘浮游植物碳的计算机模拟

应用光学显微镜法对实验系统浮游植物进行了野外定量研究.测定了系统中浮游植物的种类组成和生物碳素变动,为模型有效性验证提供了野外数据;根据Ecopath能量平衡模型原理建立了海水养殖池塘浮游植物碳的计算机模型,初步确定了包括15个参数的浮游植物模块参数库,通过单因子分析法进行参数敏感性检验,确定了3个敏感性参数,并利用野外实际测定数据进行了模型验证.模拟结果表明本模型成功模拟了海水养殖系统浮游植物碳变动.在建模过程中,光限制因子与水温为影响浮游植物碳的主要内源因素,浮游动物捕食作用为外源影响因素.     

用多层感知器模型由吸收光谱反演浮游植物色素

浮游植物吸收光谱已逐渐成为高光谱水色遥感的可获取参量。文章采用了多层感知器模型, 由珠江口担杆群岛附近水体的浮游植物吸收光谱进行了色素浓度的反演, 感知器的输入量是浮游植物吸收光谱, 输出量分别对应叶绿素a、叶绿素b、叶绿素c、光保护类胡萝卜素和非光保护类胡萝卜素五大类主要色素的浓度。分析结果表明, 叶绿素a和叶绿素c估算结果的平均相对偏差比较低, 在测试数据集中两者的偏差分别为19.06%和15.90%; 光保护类胡萝卜素和非光保护类胡萝卜素的估算浓度的相对偏差比较高, 对于测试数据而言, 分别为37.62%和36.96%; 叶绿素b浓度在测试数据集中的估算相对偏差约为27.47%。五大类色素在测试数据集和训练数据集的估算偏差比较接近, 已训练好的多层感知器可用于担杆岛水体中色素信息的反演。同时, 此色素反演方法也为遥感监测水体浮游植物种群动态提供了重要的手段。     

Gaussian decomposition and component pigment spectral analysis of phytoplankton absorption spectra

The absorption spectrum of phytoplankton is an important bio-optical parameter for ocean color hyperspectral remote sensing;its magnitude and shape can be aff ected considerably by pigment composition and concentration. We conducted Gaussian decomposition to the absorption spectra of phytoplankton pigment and studied the spectral components of the phytoplankton, in which the package effect was investigated using pigment concentration data and phytoplankton absorption spectra. The decomposition results were compared with the corresponding concentrations of the five main pigment groups (chlorophylls a , b , and c , photo-synthetic carotenoids (PSC), and photo-protective carotenoids (PPC)). The results indicate that the majority of residual errors in the Gaussian decomposition are <0.001 m^-1 , and R 2 of the power regression between characteristic bands and HPLC pigment concentrations (except for chlorophyll b) was 0.65 or greater for surface water samples at autumn cruise. In addition, we determined a strong predictive capability for chlorophylls a , c , PPC, and PSC. We also tested the estimation of pigment concentrations from the empirical specific absorption coeffi cient of pigment composition. The empirical decomposition showed that the Ficek model was the closest to the original spectra with the smallest residual errors.The pigment decomposition results and HPLC measurements of pigment concentration are in a high consistency as the scatter plots are distributed largely near the 1:1 line in spite of prominent seasonal variations. The Wozniak model showed a better fit than the Ficek model for Ch1 a , and the median relative error was small. The pigment component information estimated from the phytoplankton absorption spectra can help better remote sensing of hyperspectral ocean color that related to the changes in phytoplankton communities and varieties.     

基于船载走航观测高光谱颗粒物吸收系数反演浮游植物粒级结构*

利用高光谱监测数据反演浮游植物种群组成是当前海洋光学和水色遥感的研究热点。文章采用大西洋经向断面航次中走航式观测系统测量的海水总颗粒物吸收光谱数据, 尝试建立了两种模型对浮游植物粒级结构(Phytoplankton size class, 简称PSC)进行反演和比较讨论。一类模型是基于总颗粒物吸收光谱高斯分解获得的典型波段高斯带强度与色素浓度之间的关系, 建立了偏最小二乘回归模型(Partial Least Squares regression model, 简称PLS回归模型); 另一类模型是采用长波波段吸收基线高度推算海水总叶绿素a浓度, 进而根据Brewin等(2010)生物量算法推算PSC的三组分模型(简称三组分模型)。模型比较验证结果显示, 两类模型对海水总叶绿素浓度的反演都有较高的精度, 相对偏差ME在15%左右; 对于三个粒级浮游植物对应的叶绿素浓度(Pico级C_p, Nano级C_n, Micro级C_m)的反演效果也相当, PLS回归模型反演的ME分别为28.4%、31.9%和41%, 三组分模型反演的ME分别为31%、35.9%、37.7%。研究结果初步表明了采用高光谱吸收系数反演浮游植物种群结构的潜在优势, 可为不同海域走航式高光谱观测系统的推广应用提供思路。     

南海北部藻类粒级结构及色素成分对浮游植物吸收系数的影响

在珠江口、广东沿岸及南海北部三个航次生物-光学数据的基础上,研究了色素打包效应和色素成分的变化对浮游植物吸收系数的影响,结果表明,两种因素对吸收系数都有较大的贡献,但在不同的水体它们的影响程度各有不同.对网采浮游植物含量较高的珠江口和广东沿岸的水体而言,色素打包效应较强,对675 nm处比吸收系数的贡献平均分别为40%和20%;对微型浮游植物占主导地位的南海北部航次的水体,打包效应较弱,对675 nm处比吸收系数的影响平均仅为6%.采用多元线性回归的方法对吸收光谱进行分析,发现除叶绿素a之外的辅助色素对吸收系数的贡献主要表现在蓝绿光波段,三个航次440 nm波长处对总吸收的贡献平均分别为44%,43%和53%,其中对珠江口和广东沿岸航次的水体主要是光合类胡萝卜素的吸收贡献,而对南海北部航次的水体除了光合类胡萝卜素以外还要受到光保护类胡萝卜素的影响.由于河口、近岸和外海水体藻类粒级结构和辅助色素成分对浮游植物吸收系数的贡献有明显的差异,在南海北部水体建立比较精确的生物光学模型时,需考虑藻类粒级结构及色素成分对浮游植物吸收系数的影响.     

Variability of phytoplankton absorption in the northern South China Sea: influence of the size structure and pigment composition of algal populations

Data from three cruises conducted in the Zhujiang River (ZR), coastal waters of Guangdong (CWGD) and the northern South China Sea (NSCS) during 2003 and 2004 were examined for assessing the relative importance of pigment composition and packaging effect in modifying the specific absorption coefficients of phytoplankton. The three survey regions differ widely in their phytoplankton community with large cells dominating the ZR and CWGD waters and small cells dominating the NSCS region. Variations in the size structure and the accessory pigments have much effect on the chlorophyll a-specific absorption coefficient of phytoplankton. The size index accounted for about 42% and 33% of the variation of the specific absorption coefficient at 440 and 675 nm, respectively. Using the multiple regression analysis approach, pigment concentrations for each sample were calculated. The accessory pigments other than chlorophyll a contribute to absorption mainly in the blue-to-green region of the spectrum and their absorptions account for about 44%, 43% and 53% on the average of the total phytoplankton absorption at 440 nm for the ZR, CWGD and NSCS regions. Among the accessory pigments, the photosynthetic carotenoids (noted PSC) play a dominant role in the ZR and CWGD waters, while in the NSCS the nonphotosynthetic carotenoids (noted PPC) as well as PSC have important contributions. Because the variations of both the size structure and accessory pigments in algal populations contributed to the variability of the specific absorption coefficient in the study regions, these factors may be considered explicitly in future bio-optical algorithms to derive chlorophyll a concentration more accurately.     

A spectral response approach for detecting dominant phytoplankton size class from satellite remote sensing

An important goal in ocean colour remote sensing is to accurately detect different phytoplank- ton groups with the potential uses including the validation of multi-phytoplankton carbon cycle models; synoptically monitoring the health of our oceans, and improving our understanding of the bio-geochemical interactions between phytoplankton and their environment. In this paper a new algorithm is developed for detecting three dominant phytoplankton size classes based on distinct differences in their optical signatures. The technique is validated against an independent cou- pled satellite reflectance and in situ pigment dataset and run on the 10-year NASA Sea viewing Wide Field of view Sensor (SeaWiFS) data series. Results indicate that on average 3.6% of the global oceanic surface layer is dominated by microplankton, 18.0% by nanoplankton and 78.4% by picoplankton. Results, however, are seen to vary depending on season and ocean basin.     

南海典型海区浮游植物吸收光谱特征及遥感反演产品的精度评估

基于遥感手段准确估算浮游植物吸收系数a_ph(l), 可为长时间、大尺度范围识别浮游植物功能种群提供有力的数据和方法支撑。利用2003至2012年获取自南海、琼东、广东近岸和珠江口各典型海区的实测a_ph(l)数据, 对比分析表层光谱特征, 初步判断浮游植物种群结构差异; 基于MODIS-Aqua二级遥感反射率产品, 分别采用经验算法PL和半分析算法QAA对a_ph(l)遥感产品进行精度评估。结果表明, 以南海、琼东为代表的清洁海域和以广东沿岸、珠江口为代表的浑浊海域表层a_ph(l)光谱差异明显; a_ph(l)在清洁海域量值较小但在颗粒物吸收中居于主导, 而在浑浊海域并不占优; 浮游植物单位吸收系数a_ph^*(l)存在明显的空间差异, 色素打包效应以及色素组成是造成差异的可能原因。经验算法PL较之于半分析算法QAA反演得到的a_ph(l)(l=412, 443, 490)遥感产品精度更高, 平均相对误差APD小于22%; 采用区域优化算法NOCI获得的Chl-a产品作为输入参数, 算法PL所得的a_ph(l)遥感产品APD不超过14%。结果表明, 基于水色遥感产品进行a_ph(l)遥感产品精度评估和探讨不同海区浮游植物功能种群具有较强应用前景。     

Partitioning particulate absorption coefficient into contributions of phytoplankton and nonalgal particles: A case study in the northern South China Sea

We measured the absorption coefficients of suspended particles (a_p(λ)) during three cruises from coastal waters to open ocean in the northern South China Sea (NSCS). The absorption contributions of phytoplankton (a_ph(λ)) and nonalgal particles (a_NAP(λ)) were determined using the methanol extraction method. Based on the dataset of about 360 samples, we examined the spectral relationships of the particle absorption coefficients. The results show that a_p(λ) spectra are well linearly correlated with a_p(443) over the wavebands between 420–650 nm; a_ph(λ) could be well expressed as the second-order quadratic equations of a_ph(443) among the blue-green wavebands, and a_NAP(λ) follows the general exponential function. Based on these spectral relationships, a model was proposed for partitioning the total particulate absorption coefficients into the contributions of phytoplankton and nonalgal particles using the nonlinear optimization method. The model was validated by comparing the computed results with in situ absorption coefficients. In some wavebands, such as 412 nm, 443 nm, 490 nm and 683 nm, we obtained good correlations with the percentage root mean square error (RMSE) values being controlled within 25% and the slopes being closer to 1.0. For samples from coastal waters, the discrepancy was a little large, which might be due to the higher absorption contributions from certain pheopigments. Overall, this model provides us much insight into phytoplankton absorption retrieval from in situ measurements and remote sensing ocean color data.     

Chlorophyll-specific absorption coefficients and pigments of phytoplankton off Sanriku, northwestern North Pacific

The variety in shape and magnitude of thein vivo chlorophyll-specific absorption spectra of phytoplankton was investigated in relation to differences in pigment composition off Sanriku, northwestern North Pacific. Site-to-site variations of the absorption coefficients,a _ph ^* (λ), and pigment composition were clearly observed. At warm-streamer stations, higher values ofa _ph ^* (440) anda _ph ^* (650) were found with relatively high concentrations of chlorophyllb (a green algae marker). At stations located in the Oyashio water (cold streamer),a _ph ^* (440) values were lower and fucoxanthin (a diatom marker) concentrations were higher, compared to the other stations. The peak in the absorption spectra at the Oyashio stations was shifted toward shorter wavelengths, which was probably due to the presence of phaeopigments. In a Kuroshio warm-core ring, the magnitude ofa _ph ^* (440) was in between those at the warm-streamer and Oyashio stations, and the diagnostic pigment was peridinin (a dinoflagellate marker). These findings indicated that major differences in phytoplankton absorption spectra of each water mass were a result of differences in the phytoplankton pigment composition of each water mass, which was probably related to the phytoplankton community.