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。     

2002-2021年渤海叶绿素a浓度变化及环境响应分析

基于2013-2021年渤海遥感反射率和叶绿素a浓度等实测数据,开展了该海域MODIS影像的叶绿素a浓度遥感反演模型研究。选择OC3经典模型形式,采用渤海的实测数据进行拟合分析,获取了适用于渤海的模型局地化参数,通过真实性检验得到叶绿素a浓度的遥感反演结果与实测值的决定系数为0.84,平均相对误差为24.77%,均方根误差为5.56 μg/L,反演精度较佳。利用该算法反演获取了渤海2002-2021年叶绿素a的月度、季度和年度平均浓度,分析了其时空变化特征,同时结合2001-2021年渤海非优良水质比例开展了环境响应分析。分析结果显示:2001-2021年,渤海非优良水质比例与同时期叶绿素a浓度变化趋势基本一致,呈现先变差后变好的倒V形趋势;5年平均的非优良水质比例与叶绿素a浓度变化趋势更直观地反映了2001-2021年渤海整体的水环境变化趋势,与非优良水质比例相比,叶绿素a浓度对渤海水环境的改善响应更快。     

洞庭湖水体叶绿素a时空分布及与环境因子的相关性

2013年6月至2014年5月逐月对洞庭湖水体叶绿素a质量浓度和主要环境因子进行测定,分析洞庭湖水体叶绿素a质量浓度的时空分布特征,探讨洞庭湖水体叶绿素a质量浓度与环境因子的相关性。结果表明,洞庭湖水体叶绿素a质量浓度为0.11~8.62 mg/m~3,年均值为(1.89±1.23)mg/m~3,属贫营养;叶绿素a质量浓度随季节变化明显,总体呈现夏、秋季明显大于冬、春季的规律;在空间上,总体表现为西洞庭湖和东洞庭湖明显大于南洞庭湖。全湖叶绿素a质量浓度与水温、电导率、COD和TP呈极显著正相关,与DO、NH3-N、TN和TN/TP呈极显著负相关,与NO-3-N呈显著负相关,与p H和透明度无显著相关性。全湖TN/TP的年均值为28.5,磷可能是洞庭湖水体浮游植物生长的限制性营养盐。     

基于Landsat系列卫星分析1985—2015年东平湖叶绿素a浓度变化趋势

基于Landsat-5 TM数据和地面同步水质监测数据发现，近红外波段与红色波段比值与叶绿素a实测浓度存在较高相关性，并以此建立了提取水体表层叶绿素a浓度的遥感信息模型。经验证，该模型用于叶绿素a浓度反演的精度良好，平均相对误差为14.5%。将该模型应用于Landsat卫星系列数据，提取了东平湖1985-2015年每年度丰水期叶绿素a浓度信息，得到共31幅东平湖叶绿素a浓度分布图，并对其进行了时空分析。结果表明：1985-2015年，东平湖叶绿素a平均浓度范围为32.4~81.4 μg/L，空间分布上一般表现为湖周边浅水区高于湖中心深水区，且空间差异变化明显；时间序列上，东平湖叶绿素a浓度表现出一定的波动性，在1987、1988、1992年出现较高值，总体看来，在95%置信水平上秩相关系数为-0.592，浓度呈下降趋势。     

生态工程治理玄武湖水污染效果的监测与评价

选取总磷、总氮、叶绿素a、浮游生物、浮游植物等多项环境监测指标，对利用生态工程治疗玄武湖水环境污染的效果进行了环境监测与评价。指出生态工程治理玄武湖水环境污染效果显著，经过治理使湖水中生物多样性大大增加，浮游植物大幅减少，湖水透明度增加，总磷、总氮等主要指标大幅下降，生态工程区中的水环境已从高度富营养化降到中度富营养化。     

超声提取分光光度法测定地表水浮游植物中的叶绿素a

对研磨法和超声法测定浮游植物中的叶绿素a进行了比较。结果表明,超声法对浮游植物叶绿素a的萃取效率优于研磨法,人为误差小,精密度较高,且简便安全,适宜推广应用。     

叶绿素a在监视赤潮和评价水环境中的应用

阐述了赤潮的发生与水中藻类浮游植物的关系。指出测定水中叶绿素的含量 ,是对水中浮游植物的一种定量测量方法。重点介绍了叶绿素a监测的原理和方法。例举了叶绿素a在监视赤潮和评价水质环境方面的事例     

地表水浮游植物叶绿素a测定方法比较研究

比较了浮游植物叶绿素a测定方法中的丙酮萃取法和热乙醇萃取法.结果表明,应用反复冻融植物细胞的丙酮萃取法对地表水中浮游植物叶绿素a的萃取率显著高于其他方法,且重复测定的精密度较高.     

新安江水库主要入流营养盐的时间变化特征及其影响因素分析

流域上游来水是水库的重要补给源，其水质状况直接决定下游受纳水库的生态系统状态和功能，研究入库来水营养盐的时间演变特征并揭示其变化的影响因素，为水库水质管理提供重要科学依据。以新安江水库安徽辖区为研究区，分析了2007—2016年期间流域入库水质的变化特征，探讨水文、气象等环境条件对入库水质的影响。研究结果表明，2007年以来，COD_Mn和透明度表现为下降趋势，TN、TP、NH₃-N呈明显上升趋势，来水营养水平上升，但叶绿素a呈下降趋势。流域降水带来的水文情势的变化对来水水质起重要作用，来水中N、P营养盐丰水期显著高于枯水期，同流域降水过程显著正相关。     

基于环境一号卫星CCD数据的巢湖叶绿素a的动态监测

环境一号卫星CCD数据具有获取周期短、空间分辨率高等特点,能够及时准确地监测叶绿素a的浓度变化和分布,其在内陆湖泊水质遥感监测方面具有良好的应用前景。文章通过星地同步地面实验,建立起巢湖水体的叶绿素a浓度遥感反演模型,利用2009年4月至2010年3月的环境一号卫星CCD数据,分季节对巢湖叶绿素a行动态监测和分析。结果表明,巢湖叶绿素a具有明显的时空分布特征,夏季叶绿素a浓度最高,冬季最低,秋季高于春季;西半湖湖区叶绿素a浓度一般高于东半湖湖区,西北部和中部湖区空间变化比较大,东部湖区变化较小。     

溪源水库蓄水前后冬春季水体营养盐和浮游植物特征研究

于2007—2008年溪源水库蓄水前,2014—2015年溪源水库蓄水后对溪源宫水源地水体进行采样,分析了冬春季水体的理化指标、浮游植物生物量及群落组成。蓄水前共鉴定出浮游植物6门26属43种,水体水质状况较好,浮游植物细胞密度平均为7.31×10~5cells/L,以硅藻、绿藻门为优势门类,两者占浮游植物总生物量的比例约为54.7%、32.2%,水体呈贫-中营养状态。蓄水后,水体氮、磷营养盐浓度分别约为蓄水前的2.4倍、3倍,浮游植物细胞密度平均为1.42×10~7cells/L,约为蓄水前的20倍,且群落结构发生改变,优势门类为硅藻、蓝藻、绿藻,所占比例分别为40.2%、38.7%、14.4%,蓝藻门比例有显著提高,约为蓄水前的5倍。说明建库蓄水对浮游植物的影响显著。     

基于浮游植物群落的青岛世园会天水水库水体评价

于2014年5—9月逐月对青岛世园会园区内的天水水库进行了浮游植物群落结构研究,共发现浮游植物7门42属66种,密度变化范围为18.48×104~427.00×104个/L,优势种为克罗脆杆藻(Fragilaria crotonensis)、铜绿微囊藻(Microcystis aeruginosa)和尖尾蓝隐藻(Chroomonas acuta),监测期间浮游植物密度逐渐升高,均匀度和多样性指数呈下降趋势。聚类结果显示,监测区域大致可按月分为3个浮游植物群落,分别为绿藻型、硅藻-隐藻型、蓝藻型。冗余分析表明,氨氮、CODMn及总氮与水库浮游植物的群落结构关系最为密切。水质评价显示,天水水库水质处于中度污染,营养水平为中营养。     

Recent trends of plutonium fallout observed in Japan: plutonium as a proxy for desertification

Plutonium in monthly deposition samples collected in Tsukuba (the Meteorological Research Institute), Japan from 1990 to end of 2001 is reported, together with monthly plutonium deposition in Nagasaki and Yonaguni in 2000. The annual deposition of (239,240)Pu during the period from 1990 to 2001 shows no systematic interannual variation. However, monthly (239,240)Pu depositions show a typical seasonal variation with a maximum in spring season (March to April), which corresponds to seasonal cycle of soil dusts originating from the East Asian arid area. Plutonium isotopic ratios in the deposition samples suggest that significant amounts of the recent (239,240)Pu deposition observed in Japan are attributed to the resuspension of plutonium-bearing surface soil particles; resuspended plutonium originates from the East Asian arid areas. The recent increased tendency of (239,240)Pu content in residues in deposition samples may reflect desertification in the East Asian continent.     

Microcystins and cyanobacteria trends in a 14 year monitoring of a temperate eutrophic reservoir (Aguieira, Portugal)

A monitoring program of cyanobacteria and cyanotoxins in the framework of the surveillance of the Water Treatment Plant efficiency of the municipality of Santa Comba D?o (Portugal) was conducted from 1994 until 2007. With these data we aimed to answer the question, are MCs produced evenly over the years in a single water body? Samples were taken by the local health authorities in the site of the Water treatment plant and analyzed for total phytoplankton, cyanobacteria and the hepatotoxic cyanotoxins microcystins (MCs). Apart from 1999 and 2000, cyanobacteria represented a high proportion of total phytoplankton, attaining during several months of the year more than 90% of total phytoplankton density. A total of 24 cyanobacteria species were identified and Microcystis aeruginosa, Anabaena flos-aquae and Aphanizomenon flos-aquae were the main potentially toxic cyanobacteria species present throughout the period. MC concentration varied between 0.3 μg MC-LR eq l?1 in October 98 and 87.0 μg MC-LR eq l?1 in September 2001. The evolution of the average cell quota does not reveal any especial trend, although in 2001 the quota was the highest but not significantly different from the other years. The threshold limit of 5000 cells per ml of Microcystis aeruginosa should be taken into consideration in monitoring programs because the 10,000 cells per ml proposed by several other national programs might not be enough to prevent human health risks. Due to high annual variation in MC cell quota, monitoring programs of cyanobacteria and MC should be extended in time, since short term studies do not provide us the data needed for a safe management of a water body used for human purposes.     

Water quality assessment using integrated modeling and monitoring in Narva Bay, Gulf of Finland

A coupled three-dimensional hydrodynamic–ecological model was used for the assessment of water quality in Narva Bay during one biologically active season. Narva Bay is located in the south-eastern Gulf of Finland. Narva River with a catchment’s area covering part of Russia and Estonia discharges water and nutrients to Narva Bay. The ecological model includes phytoplankton carbon, nitrogen and phosphorus, chlorophyll a, zooplankton, detritus carbon, nitrogen and phosphorus, inorganic nitrogen, inorganic phosphorus and dissolved oxygen as state variables. Both the hydrodynamic and ecosystem models were validated using a limited number of measurements. The hydrodynamic model validation included comparison of time series of currents and temperature and salinity profiles. The ecological model results were compared with the monitoring data of phytoplankton biomass, total nitrogen and phosphorus and dissolved oxygen. The comparison of hydrodynamic parameters, phytoplankton biomass, surface layer total phosphorus and dissolved oxygen and near-bottom layer total nitrogen was reasonable. Time series of spatially mean values and standard deviations of selected parameters were calculated for the whole Narva Bay. Combining model results and monitoring data, the characteristic concentrations of phytoplankton biomass, total nitrogen and phosphorus and near-bottom dissolved oxygen were estimated. Phytoplankton biomass and total phosphorus showed seasonal variations, of 0.6–1.1 and 0.022–0.032 mg/l, respectively, during spring bloom, 0.1–0.3 and 0.015–0.025 mg/l in summer and 0.2–0.6 and 0.017–0.035 mg/l during autumn bloom. Total nitrogen and near-bottom oxygen concentrations were rather steady, being 0.25–0.35 and 2–6 mg/l, respectively. The total nitrogen and phosphorus concentrations show that according to the classification of Estonian coastal waters, Narva Bay water belongs to a good water quality class.     

Revisiting the Chesapeake Bay Phytoplankton Index of Biotic Integrity

In 2006, a phytoplankton index of biotic integrity (PIBI) was published for Chesapeake Bay Lacouture et al. (Estuaries 29(4):598–616, 2006). The PIBI was developed from data collected during the first 18 years (1985–2002) of the Chesapeake Bay Program long-term phytoplankton and water quality monitoring programs. Combinations of up to nine phytoplankton metrics were selected to characterize bay habitat health according to plankton community condition in spring and summer seasons across four salinity zones. The independent data available at the time for index validation was not sufficient to test the PIBI because they lacked critical index parameters (pheophytin and dissolved organic carbon) and reference samples for some seasons and salinity zones. An additional 8 years of monitoring data (2003–2010) are now available to validate the original index, reassess index performance and re-examine long-term trends in PIBI conditions in the Bay. The PIBI remains sensitive to changes in nutrient and light conditions. Evaluation of the PIBI results over the entire 1985–2010 time period shows no discernible trends in the overall health of Bay habitat based on phytoplankton community conditions. This lack of overall PIBI trend appears to be a combined response to declines in water clarity and improvements in dissolved inorganic nitrogen and dissolved phosphorus conditions in the bay.     

地表水中TOC与COD换算关系研究

总有机碳(TOC)相对于化学需氧量(COD) 能够更全面地反映水体中有机物的污染程度,且TOC测定仪操作简单,数据准确。通过18个地表水水质自动监测站对水中有机污染物的COD与TOC监测数据的相关性研究,建立了TOC与COD之间的线性回归方程,为地表水的TOC监测代替COD监测提供了数据支持。     

Phytoplankton patterns along a series of small man-made reservoirs in Kenya

We studied nine small man-made reservoirs located in different climate regions of Kenya to get an insight into the relationship between phytoplankton community structure and its environment. The investigated ponds form three groups of three reservoirs each found in the rural areas of Machakos district, Mount Kenya region, and Lake Victoria area with varied climatic characteristics. The ponds were sampled in monthly intervals between May 2007 and June 2008 for physicochemical variables including water chemistry, phytoplankton community composition, zooplankton abundance, and bacterial numbers. All ponds were classified as hypertrophic. Seasonal changes were reflected in the phytoplankton pattern, as all ponds showed a community shift after the short dry season in February. Due to high nutrient loads and increased turbidity, Cyanobacteria, which were initially thought to be predominating in all investigated water bodies, were found to play only a minor role except for the Bomet reservoir in Lake Victoria region. Instead, Chloro- and Streptophyta, Dinophyta, and Euglenophyta were abundant in the pelagial. A principal component analysis explained around 85 % of the data variance with four principal components (PCs) interpreted as “location”, “ions”, “zooplankton”, and “particulate matter”. A clear separation of ponds with and without cattle access based on algal species community data was found indicating the need for a sustainable use and regular monitoring program as the local population is largely dependent on these sensitive small-scale ecosystems.     

Long-term trends and short-term variability of water quality in Skive Fjord, Denmark – nutrient load and mussels are the primary pressures and drivers that influence water quality

Nineteen years of monitoring data from the eutrophic Skive Fjord, Denmark were examined for linkages to external pressures and drivers, including nutrient inputs, meteorology and stocks of blue mussels. Linkages were examined by: 1) time-series analysis to document effects of nutrient reduction programs, 2) Pearson Rank correlations, 3) multivariate statistical analysis (PLS) to identify water quality variables with high predictability and their linkages to pressures, and 4) regression analysis to quantify relationships between pressures and water quality. Freshwater input, nitrogen load and phosphorus load showed decreasing trends through the period 1984–2002. The load reductions were only partially translated into trends in water quality: phosphorus decreased in most seasons, while total nitrogen decreased during winter and spring only. Phosphorus concentration had the highest predictability (explained by seasonal temperature variation) followed by transparency, silicate, tot-N, chlorophyll-a, primary productivity, phytoplankton diversity and phytoplankton turnover. The variation in pressures other than nutrient input confounded the relations between loads and water quality. High biomass of mussels led to reduced chlorophyll-a and increased transparency, while short-term variability in water column mixing led to changes in chlorophyll-a due to nutrient entrainment and coupling to benthic mussels.