基于深度学习技术的藻类智能监测系统开发

浮游藻类对水环境的变化非常敏感,是评价水环境质量的重要指示生物.传统的浮游藻类监测依靠人工采样分析,需要专业检测人员使用显微镜对藻细胞逐一鉴定并计数,耗时耗力且严重依赖检测人员的专业知识与鉴定经验,限制了浮游藻类监测工作的标准化推广和普及应用.利用神经网络模型建立了一套浮游藻类智能监测系统,该系统能够实现浮游藻类检测的...     

阳澄湖浮游藻类现状调查及水质评价

对苏州阳澄湖2009年-2011年的浮游藻类现状进行调查,采用硅藻指数和Shannon-wiener指数两种生物学指数评价阳澄湖水体污染状况.结果表明,在阳澄湖发现浮游藻类219种(包括变种),秋季的浮游藻类种类数多于春季；阳澄湖水质尚好,东湖南富营养化程度较为严重.目前阳澄湖的有机污染处于缓慢上升的态势,富营养化水平也不断提高.     

浮游藻类环境DNA宏条形码监测引物的比较与验证

环境DNA (eDNA)宏条形码技术通量高、重复性好,在未来生态环境监测中有巨大的应用潜力。目前,浮游藻类环境DNA监测仍处在发展阶段,尚缺乏统一的浮游藻类扩增引物。利用同一个野外环境样本,比较8对通用引物在浮游藻类环境DNA监测中的差异,为初步建立规范化的浮游藻类环境DNA监测方法提供支撑。结果表明,不同引物对浮游藻类扩增存在明显偏好性,靶向扩增16S rDNA的引物主要检出硅藻,其次是隐藻和绿藻;靶向扩增18S rDNA的1391、AD3和ANF 3对引物具有较高的浮游藻类扩增效率和物种辨识度,分别检出67、62、63个浮游藻属,其检出的浮游藻类的相对丰度排序均为硅藻>绿藻>隐藻>金藻>甲藻,可以作为通用引物用于浮游藻类环境DNA宏条形码监测。     

珠江口四大口门及近滩水域浮游藻类和关键水质因子的监测与分析

对珠江口四大口门虎门、蕉门、洪奇沥、横门及近滩为主的水域进行浮游藻类发生与关键水质因子 (溶解氧(DO)、活性磷 (PO3- 4-P)、硝酸盐 (NO- 3-N) )的监测与总结 ,得出二者间具有较高相关性。为珠江口水域水质、浮游藻类生态及赤潮研究做些基础工作与贡献。     

滇池浮游藻类群落构成调查

对滇池浮游藻类群落组成和空间分布开展了2次调查,鉴定出藻类8门66属159种及变种,绿藻种类最多,蓝藻次之。5、12月滇池全湖平均藻类密度分别为1.398×108、2.180×108个/升,蓝藻门微囊藻属为优势藻类。5月的调查中滇池外海藻类生物量呈北高南低的格局,而12月则呈现南部和中部高,北部低。外海的藻类生物量明显高于草海,草海藻类群落构成与外海明显不同,主要表现为绿藻门藻类所占比例较高。12月滇池外海及全湖藻类生物量都显著高于5月。与上一次(2006—2007年)滇池浮游藻类的系统调查相比,滇池(主要是外海)浮游藻类在物种数量、常见藻类、优势藻类及生物量水平方面与之接近。     

冰封期呼伦湖浮游藻类群落结构及其与水环境因子的关系

为探讨冰封状态下呼伦湖的水生态系统演变过程,2015年12月—2016年3月环湖设置6个采样点进行浮游藻类及湖水水质的监测。浮游藻类以绿藻门Chlorophyta种类最多(52.5%),其次为硅藻门Bacillariophyta(29.8%),蓝藻门Cyanophyta(10.5%)。物种丰富度和3种生物多样性指数(Shannon-Wiener多样性指数、Margalef丰富度指数、Pielou均匀度指数)从12月至次年3月呈下降趋势。浮游藻类丰度自12月至次年3月呈现上升趋势。典范对应分析(CCA)排序结果表明:NH₃-N、TN、TP、电导率、DO、BOD₅、CODMn和pH是影响呼伦湖浮游藻类群落结构特征的主要环境因子,其中,NH₃-N、TN和TP分别对硅藻门、绿藻门和蓝藻门的影响较大。     

鄱阳湖浮游藻类群落特征及与环境因子典范对应分析

通过2018—2019年夏冬季在鄱阳湖布设17个采样点,采样检测浮游藻类和水质参数,并采用典范对应分析法研究该湖浮游藻类群落结构特征及其与环境因子的相互关系。结果表明,两次调查共检测出浮游藻类7门31科58属,浮游藻类丰度范围为3.5×105 L-1～1.15×107 L-1,主要由绿藻门、硅藻门和蓝藻门组成,绿藻门为夏、冬季主要优势种群。典范对应分析结果显示,鄱阳湖冬季湖区水环境空间差异较大,而夏季差异较小;夏季氮磷营养盐和DO是影响浮游藻类群落时空分布的主要环境因子,冬季氮磷营养盐、BOD5和IMn是影响浮游藻类群落时空分布的主要环境因子。     

西安市景观水体营养状态调查及浮游藻类多样性研究

对西安市城区景观水体浮游藻类状况及生物多样性进行了研究。结果表明,7个景观水体中有5个水体的水质未达到Ⅴ类水质标准,主要超标项目为pH值和TN;7个水体的ρ(N)/ρ(P)为16.6~43.6,磷为限制性因子;其中2个水体富营养化严重,DO含量低,水质达不到要求,其优势藻种为蓝藻门,含量占浮游藻类总数的64.3%~93.4%;而水质较好的贫营养水体优势种为黄藻门,含量占到浮游藻类总数的54.3%;通过6种生物多样性指数与景观水体营养状态的拟合,发现MeNaughton's多样性指数适合城区景观水体的富营养化评价。     

宁波市主要湖库浮游藻类调查及营养状态研究

对宁波市11个湖库水质进行了调研,包括浮游藻类和理化指标。从浮游藻类的生物量、优势种以及藻类群落组成等指标评价了水质;还用修正的营养状态指数法评价了水质。结果表明,部分湖库已经出现富营养化。用浮游藻类评价与修正的营养状态指数法评价这些湖库,结果不完全一致,对此做了原因分析。同时提出防止湖库受污染的几点建议。     

江阴地区主要河道浮游藻类群落特征

2010年9月和2011年1月、4月、7月共4次对江阴6条主要河道的浮游藻类群落特征开展调查分析。共发现浮游藻类7门141属种,种类丰富度和现存量夏秋季高于秋冬季。优势种属呈季节性演替,即冬季梅尼小环藻(Cyclotellameneghiniana)、颗粒直链硅藻(Aulacoseira granulata)-春季梅尼小环藻、啮蚀隐藻(Cryptomonas erosa)、裸藻属(Euglenaspp.)、衣藻属(Chlamydomonas spp.)、卵囊藻属(Oocystis spp.)-夏季巨颤藻(Oscillatoria princeps)、阿氏浮丝藻(Planktothrixagardhii)-秋季巨颤藻、阿氏浮丝藻、梅尼小环藻。南北向河道(锡澄运河、白屈港河和张家港河)的浮游藻类季节波动性大于东西向河道(应天河、东横河和西横河)。通过指示生物法,调查河道处于α,β-中污染状态。     

太湖浮游植物种类组成时空变化规律

从2010年的3月到2010年的10月，通过春、夏、秋3个季度的采样，对太湖东部的浮游植物种类组成及其变化进行渊查，发现浮游植物92属279种，太湖东部五个采样点位的浮游植物常见种季节变化明显，而各湖区浮游植物种类绀成空间变化较小。通过对太湖东部浮游植物种类组成的时空变化的规律的初步探索，为预警监测及水环境保护提供技术支持。     

大庆库里泡浮游植物群落时空变化及其与环境因子的相关性

库里泡是黑龙江省大庆市重要的排污、泄洪湖库之一。近年来,由于大庆市生活及工业污水排放总量逐年增加,库里泡水体质量有所下降。为掌握库里泡浮游植物群落结构特征及水环境状况,于2019年春、夏、秋3季在库里泡共设置了13个采样点,对浮游植物群落及其与水环境变量的相关关系进行了研究。利用群落相似性分析(ANOSIM)检验浮游植物群落的组间及组内差异;采用相似性百分比(SIMPER)分析辨别对群落时空格局有显著影响的物种;通过冗余分析(RDA)确认环境变量及浮游植物优势种的生态分布特征,并对主要影响因子进行辨别。结果显示:研究期间共鉴定出浮游植物106种,隶属于6门8纲13目23科49属。库里泡的浮游植物群落组成为绿藻-硅藻型,而蓝藻、隐藻、甲藻、裸藻种类相对较少,占比仅为25%。其中,优势种有15种,主要为狭形纤维藻(Ankistrodesmus angustus)、四尾栅藻(Scenedesmus quadricauda)和梅尼小环藻(Cyclotella meneghiniana)等。ANOSIM和SIMPER分析结果表明,季节差异和生境差异对库里泡浮游植物群落结构的构建具有一定的驱动作用。RDA结果表明,影响库里泡浮游植物群落时空格局的主要环境变量为水温、总磷和总氮。营养状态指数评价结果显示,库里泡水质为中度富营养。经与近10年间的库里泡相关研究对比发现,库里泡水体浮游植物群落结构较为稳定,浮游植物优势类群略有改变。     

Seasonal dynamics of phytoplankton and its relationship with the environmental factors in Dongping Lake, China

Dongping Lake is the final adjusting and storing lake in the east route of the South-to-North Water Diversion Project in China, and there has been serious concern regarding the water quality. Understanding the process of phytoplankton variation can be particularly useful in water quality improvement and management decisions. In this study, the phytoplankton taxonomic composition, abundance, temporal variations, spatial distribution, and diversity were studied based on a monthly sampling campaign from three sampling stations between May 2010 and May 2011. A total of 132 species (8 phyla, 72 genera), including 64 species of Chlorophyta, 26 species of Bacillariophyta, 21 species of Cyanophyta, 12 species of Euglenophyta, 3 species of Cryptophyta, 2 species of Xanthophyta, 1 species of Pyrrophyta, and 3 species of Chrysophyta were identified. Average phytoplankton diversity index and evenness values were 3.83 and 0.77, respectively, revealing a high biodiversity of phytoplankton community. The phytoplankton abundance averaged 5.11?×?10⁶ cells/L, with Bacillariophyta dominant in winter and spring, but Cyanophyta in summer and autumn. There were 14 predominant species including Pseudanabaena limnetica, Chlamydomonas simplex, Cyclotella stelligera, and Chroomonas acuta. Phytoplankton community structure and water quality variables changed substantially over the survey period; redundancy analysis, Pearson correlations, and regression analysis as an integrated approach were applied to analyze the relationships among them. Total phosphorus and ammonium played governing roles in the phytoplankton dynamics of Dongping Lake during all periods investigated.     

于桥水库浮游植物群落特征

于桥水库是天津市惟一饮用水水源地,为了研究该水库浮游植物群落特征,于2012年春、夏、秋对于桥水库浮游植物进行了监测分析。结果表明:该水库共鉴定出绿藻(Chlorophyta)、蓝藻(Cyanophyta)、硅藻(Diatoms)、裸藻(Euglenophyta)、甲藻(Pyrrophyta)、隐藻(Cryptophyta)和黄藻(Xanthophyta)7门114种,群落组成以绿藻-硅藻门为主;浮游植物细胞密度具有明显的季节变化规律,表现为春季较低,夏季急剧增长,到了秋季又有所回落。优势种对于桥水库水质的评价结果表明,春季为中营养水体,夏季为富营养化水体,秋季为中富营养水体。春、夏、秋季于桥水库香农-韦弗多样性指数平均值分别为3.22、2.51和3.17,说明2012年于桥水库春季、秋季为贫营养水体,夏季为中营养水体,且有暴发水华的危险。     

Temporal and spatial variability of phytoplankton monitored by a combination of monitoring buoys,pigment analysis and fast screening microscopy in the Fehmarn Belt Estuary

For 2 years, a baseline investigation was carried out to collect reference information of the present environmental status in the Fehmarn Belt and adjacent area. The temporal and spatial variability of phytoplankton was monitored by a combination of monitoring buoys, pigment analysis and fast screening microscopy. The overall phytoplankton succession in the Fehmarn Belt area was found to be influenced primarily by the seasonal changes, where various diatoms dominated the spring and autumn blooms and flagellates like Chrysochromulina sp., Dictyocha speculum and various dinoflagellates were occasionally abundant in late spring and summer. The phytoplankton groups were remarkably uniform horizontally in the investigation area while large differences in both biomasses and composition of individual phytoplankton groups were seen vertically in the water column, especially in the summer periods, in which the two-layer exchange flow between the North Sea and the Baltic Sea is showing a particularly strong stratification in the Fehmarn Belt. The chlorophyll a concentrations ranged continuously from 1 to 3 μg/L at the three permanent buoy stations during the 2 years of monitoring, except for the spring and autumn blooms where chlorophyll a increased up to 18 μg/L in the spring of 2010 and up to 8 μg/L in the autumn of 2009. Recurrent blooms of filamentous cyanobacteria are common during the summer period in the Baltic Sea and adjacent areas, but excessive blooms of cyanobacteria did not occur in 2009 and 2010 in the Fehmarn Belt area. The combination of the HPLC pigment analysis method and monitoring buoys continuously measuring fluorescence at selected stations with fast screening of samples in the microscope proved advantageous for obtaining information on both the phytoplankton succession and dynamic and, at the same time, getting information on duration and intensity of the blooms as well as specific information on the dominant species present both temporally and spatially in the large Fehmarn Belt area.     

太阳山湿地浮游植物优势功能群季节演替特征及驱动因子分析

为探明太阳山湿地浮游植物优势功能群季节演替规律及其主要驱动因子,于2019年4月(春季)、7月(夏季)、10月(秋季)和2020年1月(冬季)采样分析了太阳山湿地浮游植物的种类组成、优势种、丰度、生物量及季节变化,同时测定了水环境理化因子指标,采用冗余分析方法研究了浮游植物优势功能群的优势度、丰度与水环境因子之间的关系。结果表明:太阳山湿地浮游植物可分为22个功能类群;优势功能群的季节演替和空间分异特征明显,存在一定的规律性。春、秋、冬3个季节的浮游植物以硅藻门为主,夏季以绿藻门和蓝藻门为主。春季优势功能群主要为D、C、P,以硅藻门种类为主;夏季优势功能群主要为J、Lo、TC、M、H1,以硅藻门、绿藻门、蓝藻门种类为主;秋季优势功能群主要为D、S1、MP,以硅藻门、绿藻门种类为主;冬季优势功能群主要为D、X3,以硅藻门种类为主。影响太阳山湿地浮游植物优势功能群季节演替的水环境因子有水温(WT)、pH、溶解氧(DO)、透明度(SD)、盐度(Sal)、氮磷营养元素含量、化学需氧量(COD_Cr)和高锰酸盐指数(COD_Mn)。4个湖区浮游植物优势功能群的时空差异与水环境因子密切相关,其中,西湖区浮游植物优势功能群的季节演替驱动因子为pH、DO、WT、总磷(TP),东湖区为pH、DO、WT、氮磷营养元素含量,南湖区为pH、DO、COD_Cr、五日生化需氧量(BOD₅),小南湖区为pH、DO、WT、BOD₅、COD_Cr、TP。pH、DO、WT、BOD₅、SD等水环境因子的季节差异以及TP、TN、氨氮(NH₃-N)、COD_Mn等水环境因子的湖区差异是太阳山湿地浮游植物优势功能群出现季节演替的主要原因。     

新安江水库浮游植物群落特征及影响因素分析

为了解新安江水库浮游植物群落特征及影响因素,于2008年1月—2009年12月,对其浮游植物和相关理化因子进行了单月1次的采样。共检测到浮游植物103种(属),浮游植物密度为1.46×106~2.55×107cells/L,年平均密度为6.09×106cells/L,春、秋季出现2个密度峰值;浮游植物组成随季节变化有所不同,春、冬季硅藻、隐藻占优势,夏季蓝藻、绿藻占优势,秋季蓝藻、硅藻占优势;浮游植物密度与TP、Chl-a及上月降水量均呈显著正相关,与透明度呈显著负相关,与TN相关性不明显;水库的水文形势季节性变化显著影响浮游植物结构和密度的变化,浮游植物生长短期效应明显受流域降水和温度双重影响;从大尺度生态效应角度看,食物网的下行效应可能是目前影响新安江水库浮游植物密度的主导因素,大规模滤食性的杂食性鱼类对浮游动物造成较高的捕食压力,间接促进了浮游植物种群的增长;磷是关键的营养盐因子,保持水体低磷浓度和氮磷比大于100,对降低浮游植物密度有现实意义。     

调水后东平湖浮游植物群落结构及水质生物评价

东平湖是南水北调东线工程的重要调蓄湖泊,在防洪、灌溉、休闲旅游、水产养殖及水资源供应等方面发挥着至关重要的作用.为了解南水北调东线调水后的东平湖浮游植物群落结构及水体健康状态,于2016年4月(春季)、7月(夏季)、10月(秋季)及2017年1月(冬季)对东平湖不同空间区域(根据调水路线划分为进水区、湖中区和出水区)的...     

Phytoplankton variation and its relationship with the environmental factors in Nansi Lake, China

Nansi Lake is an important storage lake in the east route of the South-to-North Water Diversion Project in China, about which there has been serious concern regarding the water quality. In this study, the phytoplankton taxonomic composition, abundance, temporal variations, spatial distribution, and diversity were studied based on a monthly sampling campaign from five sampling stations between January 2010 and December 2010. A total of 159 species (8 phyla, 79 genera), including 74 species of Chlorophyta, 36 species of Bacillariophyta, 19 species of Cyanophyta (including 2 water bloom causative species), 21 species of Euglenophyta, 3 species of Cryptophyta, 5 species of Xanthophyta, 2 species of Pyrrophyta, and 2 species of Chrysophyta, were identified. Average phytoplankton diversity index and evenness values were 4.33 and 0.81, respectively, revealing high biodiversity of phytoplankton community. The phytoplankton abundance averaged at 9.51?×?10⁶ cells L^?1 and was much higher than previous investigations carried out in 1983–1984. The dominant species were Bacillariophyta, Chlorophyta in winter and spring, and Chlorophyta and Cyanophyta in summer and atutumn. There were 14 predominant species including Chlorella vulgaris, Cyclotella stelligera, Pseudanabaena limnetica, and Chroomonas acuta. Phytoplankton community structure and environmental variable changed substantially over the survey period. Redundancy Analysis was used to analyze the relationship between them. Temperature was considered to be the key factor driving the change in phytoplankton community composition in Nansi Lake during the 2010 study period.