滇池外海蓝藻水华爆发反演及规律探讨

气象条件和营养盐浓度一直被认为是导致蓝藻水华爆发的两个重要因素。通过滇池外海Chla浓度时空分异性分析,得出晖湾中测点最易爆发蓝藻水华且爆发时间集中在每年6—9月。同时,采用基于缺失数据多重插补的EMB算法将气象条件和蓝藻水华爆发的不完全数据集进行反演,建立了滇池外海2004—2008年4—10月完整的气象、营养盐及蓝藻爆发的基础数据集,解决了表观蓝藻水华爆发研究中观测数据缺失的问题。据此,探讨了滇池外海晖湾中测点Chla、TN和TP与蓝藻水华爆发关系,进而提出了控制滇池外海蓝藻水华的一种新思路。     

蓝藻水华对水产养殖业影响的研究进展

近些年蓝藻水华的大规模爆发是水产养殖业面临的一个重要问题。文章从蓝藻水华形成的原因、蓝藻水华对水产养殖业的危害、蓝藻水华的防治方法等方面进行了论述, 并比较了不同防治方法的优劣。结合我国水产养殖业的现状, 提出在水产养殖业中可以考虑将物理、化学、生物方法联用使蓝藻的浓度处在一个低水平的动态平衡, 从而有效防止蓝藻的过度繁殖。联用方法在蓝藻水华的防控工作中有着巨大的潜力, 若能深入挖掘其中相互作用的关系和机制, 并应用指导于实践, 将对水产养殖业以及水生环境保护做出贡献。     

微囊藻气囊尺寸与gvpA/gvpC基因的关系

我国是世界上湖泊富营养化最严重的国家之一。太湖、巢湖、滇池等大型浅水湖泊由于富营养化导致蓝藻水华连年爆发, 水质日趋恶化,丧失了原有的功能, 制约着地区经济发展。水华一般是指藻类过量繁殖形成的水体表面聚集物1。在我国, 微囊藻(Microcystis)和某些蓝藻是造成水华的最为常见的种类2。蓝藻水华可产生异味物质、腐烂发臭, 还可产生毒素危害人类健康。       

微囊藻毒素生物合成及其检测的分子生物学研究进展

随着世界各地水体富营养化的日益加剧,蓝藻水华的爆发频率越来越高,爆发范围也越来越广,已经成为国内外学者高度关注的重大环境问题。微囊藻水华是淡水水体中危害最严重的一类,特别是在我国巢湖、太湖和滇池等大型湖泊,经常爆发微囊藻水华,给水体生态系统和人类健康带来了巨大的危害。本文简介了微囊藻毒素的化学结构与危害,综述了微囊藻毒素mcy基因簇、Adda生物活性结构以及肽链合成与环化等关键生物合成过程,并重点归纳了聚合酶链式反应(polymerase chain reaction,PCR)、实时定量PCR(real time quantitative PCR detecting system,QPCR)、基因芯片(gene microarray)和变性梯度凝胶电泳(denaturing gradient gel electrophoresis,DGGE)等用于藻毒素检测的分子生物学技术方法,最后对相关研究进行了展望。     

微囊藻毒素研究进展

随着大量含氮和磷的废水流入湖泊和江河,导致淡水蓝藻水华污染现象日趋严重。蓝藻水华污染的最主要危害是释放以微囊藻毒素（Ｍｉｃｒｏｃｙｓｔｉｎ,ＭＣ）为主的多种藻毒素,因此如何有效控制蓝藻水华污染和去除ＭＣ是摆在中外环境科学领域的一个难题。主要针对ＭＣ的产生、物化性质、毒性、分析方法和迁移转化方面的国内外最新研究进展进行了综述,并对重要的研究领域进行了展望。     

滇池束丝藻水华毒性生物检测

近年来,由于外源污染物大量入湖,致使滇池水体呈富营养状态,蓝藻水华频繁爆发。束丝藻属与微囊藻属随季节演替,成为滇池蓝藻水华的两大优势种群。束丝藻水华暴发期间,滇池放养的滤食性鱼类出现死亡,其原因可能是由于丝状藻体堵塞鱼鳃部而引起,但也不能排除束丝藻毒素的影响。有毒束丝藻水华对鱼类的危害主要表现在几个方面:鱼类受到有毒束丝藻细胞所分泌毒素,如四氢嘌呤碱等毒性毒害;与束丝藻共生细菌毒害;或束丝藻死亡后分解消耗水体中溶解氧造成水体缺氧等都是可以使鱼致死的原因。       

蓝藻水华及其所产生藻类毒素的研究进展

蓝藻水华已经成为人类所关注的重要环境问题之一。在最近的几十年里,我国的湖泊生态系统受到损害,水体质量有所下降,我国的经济和发展受到一定的制约。藻类毒素的产生是蓝藻水华带来的主要危害之一,有研究表明世界上25%~75%的蓝藻水华会产生藻毒素。本文对蓝藻水华及其所产生的藻类毒素的种类、毒性作用等方面进行综合阐述,旨在为生态环境保护和人类健康提供理论依据。     

巢湖蓝藻水华形成原因探索及"优势种光合假说"

为探索蓝藻水华的形成原因,从2007以来对巢湖西区浮游藻类种类、优势种季节变化、初级生产力、水质参数及优势种的光合生理生态学特性作了观测。关于蓝藻水华形成过程中迅猛发展的原因,近80a已提出了10种假说,但对解释巢湖形成的蓝藻水华,尚显不足。本文基于我们对蓝藻水华的了解,提出了如下“优势种光合假说”：（1）蓝藻水华包含各种藻类,蓝藻水华发生不仅与藻细胞浓度有关,还与水体初级生产力直接有关。巢湖中这两者在夏季最大,在冬季最小。但无定量关系。（2）水华藻类中生长最快、细胞密度最大的是优势种,含有多个优势种时可能随季节更替。巢湖几乎整年发生蓝藻水华,已检测出4种优势种都是蓝藻,从早春起先是水华鱼腥藻,以后有绿色微囊藻、惠氏微囊藻和铜绿微囊藻。（3）各种环境因子都影响优势种生长,其中少数主导因子影响较大。在巢湖富营养条件下,光强、温度和pH值是主导因子。（4）主导因子对优势种光合活性的影响,可决定其能否处于优势。巢湖的温度和pH值变化可能促进了惠氏微囊藻取代绿色微囊藻,铜绿微囊藻取代惠氏微囊藻,而光强变化可能调节冬季时水华鱼腥藻取代了绿色微囊藻,春季时正好是相反的取代。     

蓝藻毒素对底栖动物的毒理学研究进展

近年,由于人类活动加剧,大量氮磷等营养物质流入湖泊等缓流水体,导致水体富营养化。而由此引起有害蓝藻水华的频繁爆发,使生态环境和人类健康受到严重威胁。相关研究表明,蓝藻水华的爆发不仅能够使水体水质恶化,其中一些产毒藻类还会产生大量蓝藻毒素,对水生生物产生重要影响。底栖动物作为水体生态系统的重要组成部分,在食物网中有重要作用,同时其中的许多种类又与人类息息相关,因此关于水华蓝藻毒素对淡水底栖动物的毒理学研究具有重要意义。在介绍蓝藻毒素概况的基础上,综述了蓝藻毒素的致毒机理和对底栖动物的影响,展望了研究方向。     

洱海蓝藻爆发的时空特征及影响因子

湖泊生态环境对区域气候变化和流域人类活动十分敏感。随着流域的持续开发,洱海作为云贵高原第二大淡水湖泊面临着严重的生态与环境问题,主要包括水质恶化和生态功能的衰退,其中蓝藻水华问题尤为突出。针对湖泊现代监测数据存在时间序列较短、连续监测记录缺乏、监测位点不完全一致等问题,应用沉积物记录开展色素等多指标分析和环境变化重建研究,并对洱海湖区南、中、北3个湖盆的沉积物记录进行对比分析,从而探讨洱海富营养化与蓝藻爆发的历史与变化特征,并识别藻类响应模式的空间异同。沉积物色素记录结果表明,洱海蓝藻生物量变化具有明显的时空差异性,呈现由南至北,先后增加、最后呈现蓝藻水华全湖性持续爆发的模式。进一步的简约模型方差分解结果表明气候变暖和营养盐富集是洱海蓝藻生物量变化的主要驱动因子,此外相对较浅的南部湖盆还受到水位波动、水动力减弱、水生植物演化的综合影响。因此,在气候变暖的背景下,控制水体营养盐输入、合理调控湖泊水位、提高水体透明度并恢复水生植物是控制洱海蓝藻水华爆发和进行生态恢复的重要措施。     

湖泊蓝藻水华发生机理研究进展

蓝藻水华是富营养化湖泊常见的生态灾害,通过产生毒素、死亡分解时使水体缺氧和破坏正常的食物网威胁到饮用水安全、公众健康和景观,会造成严重的经济损失和社会问题,揭示其发生机理是进行防治的基础。综述了蓝藻水华发生机理的主要假说和证据,主要分为环境因子(营养盐、氮磷比、温度、微量元素、浮游动物牧食、水文和气象条件等)和生理生态特性(伪空泡、胶质鞘、CO2浓缩机制、适应低光强、贮藏营养物质、防晒、产毒素和固氮等)两个方面;评述了主要新理论,展望了今后的研究。到目前为止的研究表明寻找一两个关键因子并不能阐明蓝藻水华的发生机理。现存的理论或假说尽管已经在蓝藻水华的防治实践中产生重要作用,但仍然未能清楚地阐释其发生的客观规律。认为蓝藻水华是在各种环境因子(外因)的耦合驱动下,水华蓝藻由于其独特的生理生态特性(内因),产生巨大的生物量而在浮游植物群落中占绝对优势,在合适的水文气象条件下集聚于水表而形成。因此水华机理的研究应同时关注水华蓝藻的生理生态学规律和蓝藻水华发生的各种环境条件。不同环境因子协同影响水华蓝藻的不同生理生态特性的表达,从而影响水华的发生过程,将可能是以后研究的重点。蓝藻水华机理的研究在微观方面正趋向于应用分子生物学手段分析蓝藻生理过程,宏观方面则将广泛应用遥感遥测技术观测全湖蓝藻的变化规律。今后加强对水华蓝藻生理生态特性的基因表达与调控和环境多因子耦合作用于蓝藻水华过程的研究将有重要意义。蓝藻水华的机理研究包括现象、过程和原因3个层次的问题,通过大量的现象和过程的研究,不断揭示其发生过程中水华蓝藻的群落演替、种群发展、细胞活性和分子机理等变化规律,才能找到其发生的真正原因,为其防治提供理论依据和更好的治理措施。在蓝藻水华防治方面,控制营养盐和生态修复可能将是今后很长时间内最根本最有效和最具操作性的方法。     

Abiotic factors influencing cyanobacterial bloom development in the Gulf of Finland (Baltic Sea)

Blooms of cyanobacteria are a recurrent phenomenon in the Baltic Sea, including the Gulf of Finland. The spatial extension, duration, intensity and species composition of these blooms varies widely between years. Alg@line data collected regularly from ferries as well as weather service and marine monitoring data from 1997 to 2005 are analysed to determine the main abiotic factors influencing the intensity and species composition of cyanobacterial blooms in the Gulf of Finland. It is demonstrated that the development of the Nodularia spumigena Mertens bloom is highly dependent on weather conditions such as photosynthetically active radiation and water temperature. Nutrient conditions, especially the surplus of phosphorus (according to Redfield ratio) related to the pre-bloom upwelling events in the Gulf, affect the intensity of Aphanizomenon sp. (L.) Ralfs blooms. Differences in bloom timing and duration indicate that, if the preconditions (like nutrient ratio/concentration and weather conditions) for bloom formation are favourable, then the Aphanizomenon bloom starts earlier, the overall bloom period is longer and the Nodularia peak might appear in a wider time window. Handling editor: K. Martens     

Investigating the Use of a Bayesian Network to Model the Risk of Lyngbya majuscula Bloom Initiation in Deception Bay,Queensland, Australia

Modelling the risk factors driving an environmental problem can be problematic when published data describing variables and their interactions are sparse. In such cases, expert opinion forms a vital source of information. Here we demonstrate the utility of a Bayesian Net (BN) model to integrate available information in a risk analysis setting. As an example, we use this methodology to explore the major factors influencing initiation of Lyngbya majuscula blooms in Deception Bay, Queensland, Australia. Over the past decade Lyngbya blooms have increased in both frequency and extent on seagrass beds in Deception Bay, with a range of adverse effects. This model was used to identify the main factors that could trigger a Lyngbya bloom. The five factors found to have the greatest effect on Lyngbya bloom initiation were: the available nutrient pool, water temperature, redox state of the sediments, current velocity, and light. Scenario analysis was also conducted to determine the sensitivity of the model to different combinations of variable states. The model has been used to identify knowledge gaps and therefore to direct additional research efforts in Deception Bay. With minor changes the model can be used to better understand the factors triggering Lyngbya blooms in other coastal regions.     

Assessment of brown tide blooms, caused by Aureococcus anophagefferens, and contributing factors in New Jersey coastal bays: 2000–2002

A 3 year study (2000–2002) in Barnegat Bay-Little Egg Harbor (BB/LEH), New Jersey (USA), was conducted by the New Jersey Department of Environmental Protection, Division of Science Research and Technology (DSRT) in cooperation with several partners to assess brown tide blooms in coastal waters in NJ. Water samples were collected by boat and helicopter at coastal stations from 2000 to 2002 along with field measurements. Aureococcus anophagefferens were enumerated and associated environmental factors were analyzed. A. anophagefferens abundances were classified using the Brown Tide Bloom Index and mapped, along with salinity and temperature parameters, to their geo-referenced location using the ArcView GIS. The highest A. anophagefferens abundances (>10⁶ cells ml⁻¹), including category 3 blooms (≥200,000 cells ml⁻¹) and category 2 blooms (≥35,000 to ≤200,000 cells ml⁻¹), recurred during each of the 3 years of sampling and covered significant geographic areas of the estuary, especially in Little Egg Harbor. While category 3 blooms were generally associated with warmer water temperatures (>16 °C) and higher salinity (>25–26 ppt), these factors were not sufficient alone to explain the timing or distribution of A. anophagefferens blooms. There was no significant relationship between brown tide abundances and dissolved organic nitrogen measured in 2002 but this was consistent with other studies. Extended drought conditions, with corresponding low freshwater inputs and elevated bay water salinities, occurring during this time were conducive to blooms. A. anophagefferens abundances were well above the reported levels that have been reported to cause negative impacts on shellfish. It was shown that over 50% of the submerged aquatic vegetation (SAV) habitat located in Barnegat Bay/Little Egg Harbor was categorized as having a high frequency of category 2 or 3 blooms for all 3 years.     

Applied simulations and integrated modelling for the understanding of toxic and harmful algal blooms (ASIMUTH): Integrated HAB forecast systems for Europe's Atlantic Arc

Reasons for the emergent interest in HABs are abundant, including concerns associated with human health, adverse effects on biological resources, economic losses attributed to recreation, tourism and seafood related industries, and the cost of maintaining public advisory services and monitoring programs for shellfish toxins and water quality. The impact of HABs can potentially be mitigated by early warning of their development. In this regard the project ASIMUTH (Applied Simulations and Integrated Modelling for the Understanding of Toxic and Harmful algal blooms) was borne in order to develop short term HAB alert systems for Atlantic Europe. This was achieved using information on the most current marine conditions (weather, water characteristics, toxicity, harmful algal presence etc.) combined with high resolution local numerical predictions. This integrated, multidisciplinary, trans-boundary approach to the study of HABs developed during ASIMUTH led to a better understanding of the physical, chemical and ecological factors controlling these blooms, as well as their impact on human activities. The outcome was an appropriate alert system for an effective management of areas that are usually associated with HAB events and where these episodes may have a more significant negative impact on human activities. Specifically for the aquaculture industry, the information provided enabled farmers to adapt their working practices in time to prevent mortalities in finfish farms and/or manage their shellfish harvest more effectively. This paper summarises the modelling and alert developments generated by the ASIMUTH project.     

The influence of light, stream gradient, and iron on Didymosphenia geminata bloom development in the Black Hills, South Dakota

The aquatic nuisance species Didymosphenia geminata was first documented in Rapid Creek of South Dakota’s Black Hills during 2002. Since then, blooms have occurred primarily in a 39-km section of Rapid Creek while blooms were rarely observed in other Black Hills streams. In this study, we evaluated factors related to the presence and development of visible colonies of D. geminata in four streams of the Black Hills. At the watershed scale, stream gradient was negatively associated with the occurrence of D. geminata whereas stream width was positively related to D. geminata presence. At the stream scale, D. geminata coverage was inversely related to canopy coverage and iron concentration. At the local scale, shading by bridges virtually eliminated growth of D. geminata colonies under bridges. At all three scales, proxy measures of light such as stream width, canopy coverage, and bridge shading revealed that light availability was an important factor influencing the presence and coverage of D. geminata colonies. In general, streams that had relatively wide stream reaches (mean = 9.9 m), shallow gradients (mean = 0.22%), and little canopy cover (mean = 13%) were associated with D. geminata blooms. In addition, iron concentrations in streams with D. geminata colonies were lower than in streams without blooms.     

Response of bacterial communities to cyanobacterial harmful algal blooms in Lake Taihu,China

Cyanobacterial harmful algal blooms are prevalent around the world, influencing aquatic organisms and altering the physico-chemical properties in freshwater systems. However, the response of bacterial communities to toxic cyanobacterial blooms and associated microcystins (MC) remain poorly understood even though global concentrations of MC have increased dramatically in the past few decades. To address this issue, the dynamics of bacterial community composition (BCC) in the water column and how BCC is influenced by both harmful cyanobacterial blooms and environmental factors were investigated on a monthly basis from August 2013 to July 2014 in Lake Taihu, China. Non-metric multidimensional scaling (NMDS) revealed that seasonal variation in BCC was significant, and that the succession of BCC greatly depends on changes in environmental conditions. Redundancy analysis (RDA) results showed that the overall variation of BCC was explained mainly by dissolved oxygen (DO), nitrate nitrogen (NO₃⁻-N), and Microcystis. The alpha biodiversity of the bacterial community was different among months with the highest diversity in February and the lowest diversity in October. Furthermore, significant negative relationships were found between alpha biodiversity indices and Microcystis abundance as well as with intracellular MC concentrations, indicating that Microcystis and associated MC may influence the bacterial community structure by reducing its biodiversity. This study shows that potential associations exist between toxic cyanobacterial blooms and bacterial communities but more investigations are needed to obtain a mechanistic understanding of their complex relationships.     

New modelling of complex fish migration by application of chaos theory and neural network

Rules or patterns of movement or migration were still vague even for the main commercial fishes due to different routs in scale or in different, times resulting from complex environments to complex behaviour concept. The quantitative model of fish migration has been investigated using chaos theory to mimic more realistic fish movements by time steps from environmental and biological stimuli. The model uses three steps within a model neural network such as input stimuli, central decision‐making and response output in fish movements. The stimuli in the first step include the main physical (temperature, salinity, light, flow etc .) and biotic factors (prey, predator, life cycle etc .) which could be quantified as intensity parameters which were then normalized as ratios. The decision‐making process can be generated available signals for motor neuron using Lorenz chaos equations by the relevant stimuli. The response of fish movements from the output signal representing speed and direction can be re‐regulated as object‐oriented migration depending on physiological state or life cycle by third response filtering. The simulation results seen as 2‐dimensional seasonal migration for demersal fishes in the southern sea of the Korean Peninsula represented more realistic meandering tracks than the interpolated tracks in previous reports.     

Dynamics of bacterial community structure during blooms of Cochlodinium polykrikoides (Gymnodiniales,Dinophyceae) in Korean coastal waters

Recent studies of dinoflagellates have reported that blooms can be closely related to the characteristics of the associated bacteria, but studies of the correlation between the toxic dinoflagellate, Cochlodinium polykrikoides and their associated bacterial community composition has not been explored. To understand this correlation, changes in bacterial community structure through the evolution of a C. polykrikoides bloom in Korean coastal waters via clone library analysis were investigated. Although there were no apparent changes in physio-chemical factors during the onset of the C. polykrikoides bloom, the abundance of bacteria bourgeoned in parallel with C. polykrikoides densities. Alpha-, gamma-proteobacteria and Flavobacteria were found to be dominant phyletic groups during C. polykrikoides blooms. The proportion of gamma-proteobacteria was lower (11.8%) during peak of the bloom period compared to the post-bloom period (26.2%). In contrast, alpha-proteobacteria increased in dominance during blooms. Among the alpha-proteobacteria, members of Rhodobacterales abruptly increased from 38% of the alpha-proteobacteria before the bloom to 74% and 56% during the early bloom and peak bloom stages, respectively. Moreover, multiple sites concurrently hosting C. polykrikoides blooms also contained high portions of Rhodobacterales and principal component analysis (PCA) demonstrated that Rhodobacterales had a positive, significant correlation with C. polykrikoides abundances (p ≤ 0.01, Pearson correlation coefficients). Collectively, this study reveals the specific clades of bacteria that increase (Rhodobacterales) and decrease (gamma-proteobacteria) in abundance C. polykrikoides during blooms.