ISSN 1001 0742 Journal of Environmental Sciences Vol. 26 No. 2 2014 Aquatic environment CONTENTS Removal of total cyanide in coking wastewater during a coagulation process: Significance of organic polymers Jian Shen, He Zhao, Hongbin Cao, Yi Zhang, Yongsheng Chen 231 Removal of arsenate with hydrous ferric oxide coprecipitation: Effect of humic acid Jingjing Du, Chuanyong Jing, Jinming Duan, Yongli Zhang, Shan Hu 240 Arsenic removal from groundwater by acclimated sludge under autohydrogenotrophic conditions Siqing Xia, Shuang Shen, Xiaoyin Xu, Jun Liang, Lijie Zhou 248 Characteristics of greenhouse gas emission in three full-scale wastewater treatment processes Xu Yan, Lin Li, Junxin Liu 256 Effect of temperature on anoxic metabolism of nitrites to nitrous oxide by polyphosphate accumulating organisms Zhijia Miao, Wei Zeng, Shuying Wang, Yongzhen Peng, Guihua Cao, Dongchen Weng, Guisong Xue, Qing Yang 264 Efficacy of two chemical coagulants and three different filtration media on removal of Aspergillus flavus from surface water Hamid Mohammad Al-Gabr, Tianling Zheng, Xin Yu 274 Beyond hypoxia: Occurrence and characteristics of black blooms due to the decomposition of the submerged plant Potamogeton crispus in a shallow lake Qiushi Shen, Qilin Zhou, Jingge Shang, Shiguang Shao, Lei Zhang, Chengxin Fan 281 Spatial and temporal variations of two cyanobacteria in the mesotrophic Miyun reservoir, China Ming Su, Jianwei Yu, Shenling Pan, Wei An, Min Yang 289 Quantification of viable bacteria in wastewater treatment plants by using propidium monoazide combined with quantitative PCR (PMA-qPCR) Dan Li, Tiezheng Tong, Siyu Zeng, Yiwen Lin, Shuxu Wu, Miao He 299 Antimony(V) removal from water by hydrated ferric oxides supported by calcite sand and polymeric anion exchanger Yangyang Miao, Feichao Han, Bingcai Pan, Yingjie Niu, Guangze Nie, Lu Lv 307 A comparison on the phytoremediation ability of triazophos by different macrophytes Zhu Li, Huiping Xiao, Shuiping Cheng, Liping Zhang, Xiaolong Xie, Zhenbin Wu 315 Biostability in distribution systems in one city in southern China: Characteristics, modeling and control strategy Pinpin Lu, Xiaojian Zhang, Chiqian Zhang, Zhangbin Niu, Shuguang Xie, Chao Chen 323 Atmospheric environment Characteristics of ozone and ozone precursors (VOCs and NOx) around a petroleum refinery in Beijing, China Wei Wei, Shuiyuan Cheng, Guohao Li, Gang Wang, Haiyang Wang 332 Identification of sources of lead in the atmosphere by chemical speciation using X-ray absorption near-edge structure (XANES) spectroscopy Kohei Sakata, Aya Sakaguchi, Masaharu Tanimizu, Yuichi Takaku, Yuka Yokoyama, Yoshio Takahashi 343 Online monitoring of water-soluble ionic composition of PM 10 during early summer over Lanzhou City Jin Fan, Xiaoying Yue, Yi Jing, Qiang Chen, Shigong Wang 353 Effect of traffic restriction on atmospheric particle concentrations and their size distributions in urban Lanzhou, Northwestern China Suping Zhao, Ye Yu, Na Liu, Jianjun He, Jinbei Chen 362 Environmental health and toxicology A review on completing arsenic biogeochemical cycle: Microbial volatilization of arsines in environment Peipei Wang, Guoxin Sun, Yan Jia, Andrew A Meharg, Yongguan Zhu 371 Alginate modifies the physiological impact of CeO 2 nanoparticles in corn seedlings cultivated in soil Lijuan Zhao, Jose R. Peralta-Videa, Bo Peng, Susmita Bandyopadhyay, Baltazar Corral-Diaz, Pedro Osuna-Avila, Milka O. Montes, Arturo A. Keller, Jorge L. Gardea-Torresdey 382 Humification characterization of biochar and its potential as a composting amendment Jining Zhang, Fan Lü, Chenghao Luo, Liming Shao, Pinjing He 390 Immigrant Pantoea agglomerans embedded within indigenous microbial aggregates: A novel spatial distribution of epiphytic bacteria Qing Yu, Anzhou Ma, Mengmeng Cui, Xuliang Zhuang, Guoqiang Zhuang 398 Remediation of nutrient-rich waters using the terrestrial plant, Pandanus amaryllifolius Roxb. Han Ping, Prakash Kumar, Bee-Lian Ong 404
Construction of a dual fluorescence whole-cell biosensor to detect N-acyl homoserine lactones Xuemei Deng, Guoqiang Zhuang, Anzhou Ma, Qing Yu, Xuliang Zhuang 415 Digestion performance and microbial community in full-scale methane fermentation of stillage from sweet potato-shochu production Tsutomu Kobayashi, Yueqin Tang, Toyoshi Urakami, Shigeru Morimura, Kenji Kida 423 Health risk assessment of dietary exposure to polycyclic aromatic hydrocarbons in Taiyuan, China Jing Nie, Jing Shi, Xiaoli Duan, Beibei Wang, Nan Huang, Xiuge Zhao 432 Acute toxicity formation potential of benzophenone-type UV filters in chlorination disinfection process Qi Liu, Zhenbin Chen, Dongbin Wei, Yuguo Du 440 Exposure measurement, risk assessment and source identification for exposure of traffic assistants to particle-bound PAHs in Tianjin, China Xiaodan Xue, Yan You, Jianhui Wu, Bin Han, Zhipeng Bai, Naijun Tang, Liwen Zhang 448 Environmental catalysis and materials Fabrication of Bi 2 O 3 /TiO 2 nanocomposites and their applications to the degradation of pollutants in air and water under visible-light Ashok Kumar Chakraborty, Md Emran Hossain, Md Masudur Rhaman, K M A Sobahan 458 Comparison of quartz sand, anthracite, shale and biological ceramsite for adsorptive removal of phosphorus from aqueous solution Cheng Jiang, Liyue Jia, Bo Zhang, Yiliang He, George Kirumba 466 Catalytic bubble-free hydrogenation reduction of azo dye by porous membranes loaded with palladium nanoparticles Zhiqian Jia, Huijie Sun, Zhenxia Du, Zhigang Lei 478 Debromination of decabromodiphenyl ether by organo-montmorillonite-supported nanoscale zero-valent iron: Preparation, characterization and influence factors Zhihua Pang, Mengyue Yan, Xiaoshan Jia, Zhenxing Wang, Jianyu Chen 483 Serial parameter: CN 11-2629/X*1989*m*261*en*P*30*2014-2
Journal of Environmental Sciences 26 (2014) 289 298 Available online at www.sciencedirect.com Journal of Environmental Sciences www. Spatial and temporal variations of two cyanobacteria in the mesotrophic Miyun reservoir, China Ming Su, Jianwei Yu, Shenling Pan, Wei An, Min Yang State Key Laboratory of Environmental Aquatic Chemistry, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China. E-mail: ming.su@live.com a r t i c l e i n f o Article history: Received 18 March 2013 revised 05 August 2013 accepted 16 August 2013 Keywords: phytoplankton community succession Microcystis sp. Oscillatoria sp. mesotrophic reservoir total dissolved phosphorus water transparency mixing process DOI: 10.1016/S1001-0742(13)60433-7 a b s t r a c t Spatial variations in phytoplankton community within a large mesotrophic reservoir (Miyun reservoir, North China) were investigated in relation to variations in physico-chemical properties, nutrient concentrations, temperature and light conditions over a 5 month period in 2009. The dynamics of phytoplankton community was represented by the dominance of cyanobacteria through summer and fall, following with a short term dominance of chlorophyta in late fall, and a relatively high abundance of diatom in October; on the other hand, maximum phytoplankton biomass was recorded in the north shallow region of Miyun reservoir with a higher nutrients level. Particular attention was paid to the impacts of environmental conditions on the growth of two cyanobacteria genera, the toxin-producing Microcystis and the taste & odor-producing Oscillatoria. Microcystis biomass was in general greatly affected by water temperature and mixing depth/local water depth ratio in this reservoir, while the Oscillatoria biomass in the surface and middle layers was greatly affected by total dissolved phosphorus, and that in the bottom layer was related with the Secchi depth/local water depth ratio. Abundant Oscillatoria biomass was observed only in late September when Microcystis biomass decreased and allowed sufficient light go through. Introduction Construction of reservoirs has become the main way in securing drinking water source in the world (Kwak and Russell, 1994). However, deterioration of water quality characterized with the abnormal growth of algae frequently occurs once the river-type source water is replaced by the reservoir-type water (Codd, 2000; Šimek et al., 2011; Zhao et al., 2011). Cyanobacterial blooms associated with the taste & odor (T&O) problems and algal toxins (cyanotoxins) have become one of the major issues for reservoir management and attracted intensive research concerns (Graham et al., 2010; Li et al., 2012a; Zamyadi et al., 2012). Until today, most of the previous studies have mainly focused on the occurrence of harmful algae Corresponding author. E-mail: anwei@rcees.ac.cn blooms (HAB) in the eutrophic reservoirs (Naselli-Flores, 2011; Paerl et al., 2011; O Neil et al., 2012). Regional algal blooms occurring in oligotrophic and mesotrophic drinking water reservoirs, which could become a threat to drinking water supply, has often been ignored. Miyun Reservoir, a large reservoir with an average depth of approximately 20 m, is the major surface-source of drinking water for Beijing City, and has been kept in the mesotrophic state through a set of strict environmental protection measures. However, two well-known cyanobacterial metabolites, 2-methylisoborneol (MIB) and microcystin-lr (MC-LR), have been detected in the source water taken from this reservoir in recent years, with the concentrations up to 150 ng/l (Yu et al., 2007) and 41 ng/l (Zheng et al., 2007), respectively. Twomethylisoborneol, a notorious T&O compound, is mainly produced by filamentous and coccoid cyanobacteria including Oscillatoria sp. (Izaguirre et al., 1999; Izaguirre
290 Journal of Environmental Sciences 26 (2014) 289 298 et al., 2007), Phormidium sp. (Izaguirre et al., 2007), Pseuadanabaena sp. (Izaguirre et al., 1999) and Synechococcus sp. (Izaguirre et al., 2007) etc. Although no evidence has shown that MIB is toxic to human health, occurrence of odor can make consumers to suspect the safety of drinking water. So the complaints from customers could significantly increase when a T&O episode occurs (Smith, 2002), which could not be neglected by water supply industries. The microcystin-producing genera that are of major importance in phytoplankton have been identified as Microcystis sp. (Tillett et al., 2000), Anabaena sp. (Rapala et al., 1997) and Planktothrix sp. (Christiansen et al., 2003). Among the suspected species, Oscillatoria sp. and Microcystis sp. account for the majority of T&O and microcystin events in Miyun Reservoir respectively, according to previous phytoplankton surveys (data not shown). Therefore, the occurrence and distributions of both genera in Miyun Reservoir could significantly impact the drinking water quality. As a benthic cyanobacteria, Oscillatoria sp. is commonly present on the shallow shore with a good transparency, while the bloom forming Microcystis sp. tends to occur at the surface of eutrophic water bodies (Wilhelm et al., 2011; Acu na et al., 2012). Thus, it is interesting why the two cyanobacteria with contradictory habitats grow in the deep Miyun Reservoir with a low nutrient level, and it is important to reveal the temporal and spatial variations of nutrients and phytoplankton community for establishing a strategy on controlling their growth. In the present work, continuous survey covering different regions of Miyun Reservoir was performed over a period from June to October in 2009, shows that the temporal and spatial variations of phytoplankton community and physico-chemical properties of the reservoir including water temperature, dissolved oxygen (DO), ph, water transparency and nutrient concentrations. This work attempted to identify the impacts of environmental conditions in Miyun Reservoir on the potential MIB and MC-LR producers; the result of the study could assist decision makers in managing water quality related issues in drinking water reservoirs. 1 Materials and methods 1.1 Study site Miyun Reservoir, located 100 km northeast of Beijing (40 30 N, 116 55 E), is the main drinking water storage for Beijing. The water level of the reservoir dropped from the highest record of 153.98 m (above sea level) in 1994 to 137 m (above sea level) in 2012, which is mainly due to continuous drought from 1999 to 2004 and overuse (Ma et al., 2010). The reservoir is characterized with a large area (total volume: 4.375 km 3 ; surface area: 188 km 2 ; maximum depth: 60 m) and complex bathymetry (a mountain valley reservoir). A bathymetry map was obtained from the interpolated depth data collected from an Acoustic Doppler Current Profiler instrument (ADCP, LAUREL, USA), as shown in Fig. S1. The reservoir can be divided into four parts according to the bathymetry characteristics: the west deep region and south deep region are relatively deep (maximum water depth, z max : 36 m; mean water depth, z ave > 20 m) compared to the north shallow region (z max : 10 m; z ave : 6 m) and northeast shallow region (z max : 14 m; z ave < 5 m). The northeast shallow region is characterized with a relatively high turbidity due to the inflow. As shown in Fig. 1, two main inflows, Bai River and Chao River, enter the reservoir via two large inlets and maintain the reservoir s water capacity; the main outflow is a channel located in south deep region flowing to drinking water plants, while the Bai Release Channel is normally closed. 1.2 Sampling Water survey was performed once a month during June 2 to October 26 in 2009, except in September when 3 campaigns were conducted because of the occurrence of high Oscillatoria density. According to the bathymetry, hydrological and geochemical characteristics of the reservoir, a total of 8 sampling sites (MY01 MY08) (Fig. 1). MY01, MY07 and MY08 are located in the deep region, close to Bai Dam and Chao Dam, respectively; MY02 and MY03 are close to the largest upstream Bai River; MY05 is in the north shallow region; MY04 is in the ship channel with frequent disturbance from boats; MY06 is in the edge of north shallow region with a depth around 10 m. Eleven extra sampling sites MY09 MY19 were used 40.58 N 40.56 N 40.54 N 40.52 N 40.50 N 40.48 N 40.46 N 40.44 N Bai River MY01 Bai Release Channel MY03 MY02WDR MY04 Chao River MY05 MY09 NSR MY10 MY12 MY11 NESR MY13 MY06 MY14 MY16 MY17 MY15 MY18 SDR MY19 MY07 MY08 116.80 E 116.85 E 116.90 E 116.95 E 117.00 E 117.05 E Fig. 1 Map of Miyun Reservoir and the sampling sites. MY01 MY08 are routine field sampling sites, while MY09 MY19 were used in September to get more information for Oscillatoria sp., where the detection of physico-chemical parameters and nutrients, as well as algal enumeration were performed. Bai River and Chao River are the two main inflow rivers, and Bai Release Channel is a manual controlled outflow for agriculture etc.; MY07 is water intake position to drinking water supply. WDR: west deep region; NSR: north shallow region; NESR: northeast shallow region; SDR: south deep region. N
Journal of Environmental Sciences 26 (2014) 289 298 291 during the 3 campaigns in September because the Oscillatoria sp. occurs mainly during this period according to previous investigation. Each sampling position (including extra sampling sites) was located with a GPS navigator (Garmin, Olathe, KS, USA). Water samples were collected from different depth at each site, the surface water samples were collected from the water column at 0.5 m depth in the mixed layer, the bottom samples were collected just above the sediment for the shallow sites or 15 m depth for the deep ones, and the middle layer samples were collected from 5 m depth for the shallow sites, and 8 m depth for the deep regions. Samples were initially stored in colored glass bottles and kept cool until processing, within 12 hr after collection. 1.3 Limnological characteristics Water temperature, DO, ph, conductivity, salinity and Chlorophyll-a profiles were measured in situ using a multiparameter probe (YSI-6600, USA). Water transparency was measured with a Secchi disk (diameter: 20 cm, black and white). Water samples were collected using a 5-L bottle sampler. Subsamples were filtered through a 0.45 µm ploycarbon filter (Millipore, USA) for the analyses of dissolved substances including nitrate-nitrogen (NO 3 -N), nitritenitrogen (NO 2 -N), ammonium-nitrogen (NH+ 4 -N), soluble reactive phosphorus (SRP), total dissolved nitrogen (TDN) and total dissolved phosphorus (TDP). The analyses were performed according to standard methods (Apha, 1995). 1.4 Algal identification and enumeration Phytoplankton samples for cell enumeration were preserved with Lugol s iodine at the final concentration of 5% (Sherr and Sherr, 1993) in settling chambers (100 ml), then kept at standstill for at least 48 hr and concentrated 10 fold by removing the top water. Species identification was carried out following previously introduced methods (Prescott, 1951; Bellinger, 1974; Ling and Tyler, 2000). The algal cell density was determined by the counting chamber method using Sedgewick-Rafter cell (50 mm 20 mm 1 mm) under a Olympus BX51 microscope with phase contrast and bright field illumination. A magnification of 400 and 200 was used to identify and enumerate the cells, respectively. For each sample, triplicate of 1 ml each concentrated solution (from the same bottle) was collected and counted separately (at least 400 algal cells or 10 rows of squares in counting chamber were counted). 1.5 Data analysis The water density was estimated from the profiles of water temperature according to the water density and temperature curve. The mixing depth (z mix ) was defined as the depth at which the potential density in the upper layer changes by 0.03 kg/m 3 relative to the surface density. Phytoplankton biomass were log transferred with the formula Y = log(x+1) when seasonal variation of biomass was considered. Spatial and seasonal variations of physico-chemical parameters were tested with t-test. Linear regression was performed to evaluate the correlations between phytoplankton biomass with physico-chemical parameters. All statistic analyses were carried out with R 2.15 and corresponding packages (R Core Team, 2012). 2 Results 2.1 Physico-chemical conditions The physico-chemical characteristics varied in different regions of Miyun Reservoir due to its complex bathymetry (Fig. S1). The comparison of some physico-chemical parameters measured by YSI6600 including water temperature, DO and ph was performed between MY08 (deep region) and MY05 (shallow region). The surface water temperature varied between 10 C (in winter) and 26 C (in summer), whereas the temperature in shallow region was higher than in deep region for approximately 2 weeks in July (Fig. 2a and b). From June to August, a very thick eplimnion zone (10 15 m, Fig. 2b) was observed in MY08, while a very thin hypolimnion zone (1 3 m, Fig. 2a) was observed in MY05. The thermal stratification disappeared in MY05 in September, but lasted till the end of October in MY08. Surface ph increased from 7.3 in June to near 10 in July, which should be attributed to the high photosynthetic activity of the Microcystis sp., and decreased slowly to less than 8 from August (Fig. S2). During the period between July and September, when the Microcystis biomass was high, the DO concentration in the water column varied between 1.0 mg/l in the bottom and 10 mg/l in the surface water in both shallow and deep regions (Fig. S2). The TDP concentration varied in the range of 5 and 50 µg/l in the reservoir, with the surface TDP level in the shallow region being 10 20 µg/l and that in the deep region being below 10 µg/l. The highest TDP concentration of 50 µg/l was detected in the bottom of the shallow region between September and October, while the highest concentration of 30 µg/l was detected in the deep region in a short period in the end of August. The relatively low TDP levels and the high mean N:P ratio of 73 ± 71 (by weight) suggest that phosphorus should be the limiting nutrient and of vital importance in this reservoir. No significant spatial variations of TDN and NO 3 -N were observed during the study period. TDN and NO 3 -N showed similar seasonal distribution pattern: the values of (865 ± 140) µg/l for TDN and (317 ± 95) µg/l for NO 3 -N observed in July decreased to the minimum concentrations of (567 ± 61) µg/l and (258 ± 85) µg/l in September, respectively. In addition, the concentrations of TDN and NO 3 -N in the bottom water were significantly higher than
292 Journal of Environmental Sciences 26 (2014) 289 298 Depth (m) Depth (m) Temperature ( C) 26 a 24 2 22 4 20 18 6 16 14 8 12 10 Jun Jul Aug Sep Oct 10 TDP (µg/l) 50 c 40 2 30 4 20 Depth (m) Depth (m) Temperature ( C) 26 2 b 4 6 8 24 22 20 10 12 14 16 18 16 14 18 20 22 Jun Jul Aug Sep Oct 12 10 TDP (µg/l) 50 d 2 40 4 6 30 8 20 10 10 12 10 6 Jul Aug Sep Oct 0 14 Jul Aug Sep Oct Fig. 2 Seasonal fluctuation (x-axis) and vertical distribution (y-axis) of water temperature (a: MY05; b: MY08) and total dissolved phosphorus (TDP, c: MY05; d: MY08) in Miyun Reservoir, as well as the comparison between north shallow region (MY05) and south deep region (MY08). The color bar represents the value of each parameter. 0 in surface water with a difference of 118 and 132 µg/l, respectively (Fig. S3). NH + 4 -N in surface water decreased from (245 ± 13) µg/l in July to (202 ± 54) µg/l in September when Microcystis was abundant and thermal stratification occurred, and increased to (306 ± 53) µg/l at the end of the study; furthermore, the mean NH + 4 -N concentration in the deep region was approximately 21 µg/l higher than in the shallow region (Fig. S3). During the study period, water transparency measured as Secchi depth (SD) varied between 1.0 and 3.0 m in shallow region (mean: 1.48 m) and between 1.5 and 4.0 m in deep region (mean: 2.29 m) (Fig. S4 ). Water transparency was significantly lower in the shallow region than in the deep region (p < 0.001). In both shallow and deep regions water transparency followed the same seasonal trend. The highest water transparency was recorded in the end of October (mean: 1.60 m for north and northeast shallow regions and 2.43 m for west and south deep regions), the lowest in September (mean: 1.34 m for north and northeast shallow regions and 2.04 m for west and south deep regions). 2.2 Mixing depth (z mix ) was estimated by water temperature profile. Mixing depth varied from 1.6 to 20.8 m in south deep regions and 3 to 11.2 m in north shallow regions. Mixing depth decreased from July to August, when the thermal stratification was formed in the deep regions and Microcystis was abundant. As the thermal stratification break down in September, the vertical mixing process in the water column was enhanced. 2.3 Phytoplankton community distribution and succession A total of 46 phytoplankton genera belonging to 6 phylum were identified (Table 1) in the reservoir from June to October 2009. The main taxonomic groups included Chlorophyta (16), Cyanophyta (13) and Bacillariophyta (12) followed by the less diverse Pyrrhophyta (2), Chrysophyta (1) and Euglenophyta (1). Phytoplankton in the reservoir was dominated by cyanobacteria in cell number from June to September, whereas Chlorophyta was dominant for a very short time in the end of September when the thermal stratification of water column started to break down, and diatoms gained the dominant position in October when the thermal stratification disappeared. The total cell number increased from 1750 cells/ml (average concentration of all sampling sites and layers) in June to the maximum concentration of 10,215 cells/ml (average concentration of all sampling sites and layers) in September and remained high concentration in October (Fig. S5). Microcystis sp. was the dominant species during most
Journal of Environmental Sciences 26 (2014) 289 298 293 Table 1 List of phytoplankton genera identified in water samples collected during the study period (June-October 2009) from Miyun Reservoir Phytoplankton Jun 02 Jul 14 Aug 04 Sep 08 Sep 22 Sep 28 Oct 26 Bacillariophyta (12) Cyclotella sp. ++ ++ + ++++ Cymbella sp. + Diatoma sp. + Diploneis sp. ++ ++ + + Eunotia sp. +++ Fragilaria sp. +++ ++ ++ ++ +++ +++ +++ Frustulia sp. + Melosira sp. +++ +++ +++ ++ +++ +++ ++ Navicula sp. ++ + Pinnularia sp. + + Rhizosolenia sp. ++ ++ Synedra sp. ++ ++ ++++ ++++ ++++ ++++ Chlorophyta (16) Ankistrodesmus sp. ++ +++ ++ +++ ++ ++ Chlorella sp. +++ ++ +++ +++ +++ ++++ +++ Closterium sp. + + Crucigenia sp. ++ Echinosphaerella sp. ++ Golenkinia sp. ++ + + Micractinium sp. ++ + + Oocystis sp. ++ Pediastrum sp. +++ +++ +++ +++ +++ +++ +++ Scenedesmus sp. +++ ++ +++ +++ +++ +++ +++ Selenastrum sp. ++ ++ ++ +++ +++ +++ Staurastrum sp. ++ ++ ++ ++ ++ ++ ++ Tetraedron sp. ++ ++ ++ ++ ++ ++ Treubaria sp. ++ + ++ + Trochiscia sp. + Volvox sp. + +++ Chrysophyta (1) Dinobryon sp. +++ +++ ++ + ++ ++ Cyanophyta (13) Anabaena sp. +++ +++ +++ Aphanizomenon sp. +++ +++ +++ +++ Aphanocapsa sp. +++ Chroococcus sp. ++ ++ ++ ++ ++ ++ Cylindrospermum sp. +++ ++ ++ ++ ++ Jaaginema sp. +++ +++ Limnothrix sp. ++++ +++ +++ +++ Merismopedia sp. +++ +++ +++ +++ +++ +++ Microcystis sp. ++++ ++++ ++++ ++++ ++++ +++ +++ Oscillatoria sp. + +++ +++ +++ ++ Phormidium sp. + ++ ++ + Pseudanabaena sp. +++ Synechocystis sp. +++ ++ +++ ++ ++ ++ Euglenophyta (1) Euglena sp. + + Pyrrhophyta (2) Ceratium sp. ++ ++ ++ + ++ Peridinium sp. ++ ++ ++ ++ ++ ++ +: [1-10), ++: [10, 100), +++: [100, 1000), ++++: [1000, 10000); unit: cells/ml.
294 Journal of Environmental Sciences 26 (2014) 289 298 of the time in this study. Several other species were present with considerable concentrations: Synedra sp. was present in low numbers (< 100 cells/ml) in June and July, and started increasing in September and was quite abundant (1000 2000 cells/ml) throughout the fall and winter. Besides, Chlorella sp., Pediastrum sp., Selenastrum sp., Fragilaria sp., and Melosira sp., exhibited relatively high concentrations (100 1000 cells/ml) during September and October; filamentous Oscillatoria sp., which could produce earthy-smelly MIB, exhibited relatively high concentration (100 1000 cells/ml) in September. Anabaena sp., which could produce earthy-smelly odorous compound geosmin, and Aphanizomenon sp. were present from July to September (100 700 cells/ml). However, odor event caused by geosmin in this reservoir has never been reported perhaps due to the limited Anabaena density. The Merismopedia sp. showed high numbers in cells, but with less importance considering the fact that the cell volume is small. The other species recorded in the reservoir, many of which were observed only once, did not form substantial amounts of biomass, including Cymbella sp., Diatoma sp., Eunotia sp., Frustulia sp., Pinnularia sp., Crucigenia sp., Echinosphaerella sp., Oocystis sp., Trochiscia sp., Aphanocapsa sp. and Pseudanabaena sp. The phytoplankton community was not evenly distributed in the reservoir, as shown in Fig. S6; generally, there was an increasing gradient of algal cell number from west and south deep regions to north and northeast shallow regions in the reservoir, ranging from the minimum 2500 cells/ml (average cell concentration of three layers) observed in west deep region (MY02) to the maximum 8700 cells/ml observed in north shallow region (MY10); Significant difference was shown between west and south deep regions and north shallow region (p < 0.05). Density (cells/ml) 14000 12000 10000 8000 6000 4000 2000 Microcystis Oscillatoria 0 Jun 02 Jul 14 Aug 04 Sep 08 Sep 22 Sep 28 Oct 26 Fig. 3 Seasonal variation of Microcystis sp. and Oscillatoria sp. in Miyun Reservoir. Data are average density of algal cells from all sampling sites, error bars present the standard deviation. Miyun Reservoir, as shown in Fig. 4 (data from September). Generally, the west deep region and northeast shallow region showed much lower concentration than that in north shallow region and south deep region for both species. Besides, higher spatial variations of Oscillatoria biomass both in vertical and horizontal directions were observed than that of Microcystis biomass: relatively higher proportion of Oscillatoria biomass distributed in north shallow region than other regions, while considerable Microcystis biomass distributed in south deep region as well. On the other hand, higher proportion of Microcystis biomass was distributed in the surface layer for most sampling sites; however, the benthic Oscillatoria biomass in the bottom layer was not significant higher than in the surface and middle layer. It should be noted that the bottom layer samples did not include sediments, which could be the reason for the relatively low Oscillatoria biomass in the bottom samples. 2.4 Microcystis sp. and Oscillatoria sp. The two cyanobacteria genera of Microcystis sp. and Oscillatoria sp. were notorious as they can produce algal toxin microcystin and odorous compound MIB, respectively (Sabart et al., 2010; Li et al., 2012b). As shown in Fig. 3, the dominance of Microcystis sp. started before the first sampling in the beginning of June with a high concentration (1012 ± 582 cells/ml), increased till August with the maximum concentration (7610 ± 5460 cells/ml) being observed, and then decreased in the following months. Oscillatoria exhibited a different seasonal distribution pattern: it was initially observed in 5 out of 20 samples with very low concentrations (1.9 ± 3.5 cells/ml) in July, and continuously increased as the density of Microcystis cells declined during September with the maximum concentration (662 ± 370 cells/ml) recorded in September 22, subsequently decreased till the last campaign in the end of October. Both Microcystis and Oscillatoria showed great spatial variations due to the large area and complex bathymetry of 2.5 Correlations between biomass and environmental factors The Microcystis biomass did not show significant correlation with phosphorus concentration in surface waters (r 2 = 0.228, p > 0.05), although phosphorus is critical to algal growth in such a P-limiting reservoir; the buoyant Microcystis absorb nutrient in the bottom layer by adjusting its vertical position, thus its growth was not limited by the low phosphorus concentration in surface waters. However, the biomass was significantly correlated to mixing depth/local water depth (z mix /z max ), as shown in Fig. 5. Oscillatoria sp. was one of the successful benthic cyanobacteria in Miyun Reservoir (Table 1). Phosphorus was of the same importance for Oscillatoria sp. as for Microcystis sp. in the P-limiting reservoir; besides, light availability was also of vital importance for benthic algae. Different traits were observed for Oscillatoria sp. in different layers. The Oscillatoria biomass showed significant correlation with TDP in the surface (r 2 = 0.640, p < 0.001, k = 0.1306, Fig. 6a) and middle water layers (r 2 = 0.505,
Journal of Environmental Sciences 26 (2014) 289 298 295 Surface Middle Bottom 40.58 N 40.56 N Bai River 40.58 N a Bai River 40.56 N b 40.54 N Chao River 40.54 N Chao River 40.52 N 40.52 N 40.50 N 40.50 N 40.48 N Algal cell No. (cells/ml) 40.48 N Algal cell No. (cells/ml) 40.46 N Bai Release Channel 6000 3000 1500 40.46 N Bai Release Channel 4500 1500 300 40.44 N 40.44 N 116.80 E 116.85 E 116.90 E 116.95 E 117.00 E 117.05 E 116.80 E 116.85 E 116.90 E 116.95 E 117.00 E 117.05 E Fig. 4 Spatial of Microcystis sp. (a) and Oscillatoria sp. (b) in Miyun Reservoir; the size of each pie chart represents the mean algal cell number of the reservoir in the sampling date, and the color represents the sampling vertical locations. Data are average value of three observations in September. logρ m (cells/ml) 3.4 3.2 3.0 2.8 Surface sample Regression 95% CI 0.4 0.5 0.6 0.7 0.8 0.9 1.0 z mix / z max Fig. 5 Significant correlations between Microcystis biomass (log transferred logρ m ) and mixing depth/local water depth (z mix /z max ) ratio. The data are from the surface sample a: in north zone during the study period, and b: in whole reservoir in September 08; the thick solid lines are the linear regressions, and the thin dashed lines are 95% confidence interval (CI) of corresponding regressions. p < 0.005, k = 0.0227, Fig. 6a), but not in the bottom layer. However, Oscillatoria biomass was significantly correlated with SD/z max ratio in bottom layer (r 2 = 0.575, p < 0.005, Fig. 6b). The different characteristics in three layers suggested that the limiting resource for Oscillatoria sp. was phosphorus in both the surface and middle layer, while the limiting resource in the bottom layer was light availability, which was affected by the water transparency (SD) and the local depth (z max ). 3 Discussion During most of the sampling period, the reservoir was dominated with cyanobacteria. Some members of the cyanobacteria are able to make vertical movements by regulating their buoyancy within the water column through intracellular gas vacuoles (Walsby, 1969). This mechanism gives this group the advantage of relocating themselves at the optimal depth within a stable water column to obtain solar radiation in surface water in daytime and absorb sufficient nutrients in bottom layer at night (Walsby and Booker, 1980; Reynolds et al., 1987; Xiao et al., 2012). Microcystis occurred throughout the Miyun Reservoir during the study period from June to the end of October in 2009. Microcystis dominance generally occurs at higher water column temperature (McQueen and Lean, 1987), and has been shown to succeed at temperatures in the range of 15 25 C (Robarts and Zohary, 1987). Water temperature can be regarded as a good indicator of light accumulation ( Solić and Krstulović, 1992); besides, temperature is not considered to be the primary cause for phytoplankton succession but may work in combination with other factors (Jacoby et al., 2000). The Microcystis biomass was significantly correlated with the water temperature in the range of 16 26 C (r 2 = 0.656, p < 0.001, Fig. S7), which was in accordance with an 11-year study of Microcystis in Lake Taihu (Liu et al., 2011). Although most of Microcystis blooms have been reported to occur at low N:P ratios (Nalewajko and Murphy, 2001; Ståhl- Delbanco et al., 2003), Microcystis dominance occurred in the reservoir with a very low phosphorus content (TDP, 5 50 µg/l) and high N:P ratio (73 ± 71, by weight). The absolute Microcystis biomass showed positive correlation with mixing depth, as shown in Fig. 5. It is well known that the thermal stratification is conducive to the dominance of buoyant population of Microcystis (Visser, 1996). When Microcystis became dominant on Sep 08, however, larger mixing depth could allow a better nutrient transportation from the bottom layer to the whole water body. At the same time, larger mixing depth will facilitate the Microcystis sp. to absorb nutrients in the bottom layer. So the Microcystis
296 Journal of Environmental Sciences 26 (2014) 289 298 3.0 a 3.0 b logρ o (cells/ml) 2.5 2.0 Surface sample Middle sample Bottom sample Surface regression Middle regression 95% CI for middle samples 10 20 30 40 TDP (μg/l) logρ o (cells/ml) 2.5 2.0 Surface sample Middle sample Bottom sample Bottom regression 95% CI for middle samples 0.10 0.15 0.20 0.25 0.30 0.35 0.40 SD/z max Fig. 6 Correlations between Oscillatoria biomass (log transferred logρ o ) and (a) total dissolved phosphorus concentration (TDP) as well as (b) Secchi depth/local depth (SD/z max ) ratio. As each parameter has missing values in different sampling date and/or sites, the data present in the plots were not in accordance with each other. sp. could also benefit from the increase of mixing depth. Significant correlation was observed between the increases in ph and Microcystis biomass in Miyun Reservoir (r 2 = 0.320, p < 0.05; Fig. S8a). At high rates of photosynthesis in summer, Microcystis depletes CO 2, which causes an increase in ph (Jacoby et al., 2000). At the same time, Microcystis biomass showed significant correlation with water transparency (r 2 = 0.574, p < 0.001; Fig. S8b). The presence of Microcystis cells in surface water could decrease the water transparency, which may inhibit the growth of benthic algae because of the decreasing light irradiation. Thereby like ph, low water transparency (SD) is an environmental condition that is partially caused by Microcystis to enhance their dominance. However, the continuous consumption of nutrients (Figs. 2c, 2d, S3) in the surface water associated with decreased light availability in September was unable to sustain more Microcystis biomass, hence, the Microcystis population started to decrease as a consequence of increased water transparency, which created the condition for the growth of benthic algae. Significant seasonal variation of Microcystis biomass, which was mainly determined by water temperature (or light availability accumulation) (Fig. S7), was observed with an obvious increase from June to August, and then a continuous decrease till the end of this study. On the other hand, the spatial variation of Microcystis biomass could be partially explained by the z mix /z max ratio (Fig. 5). According to the investigation of recent years, the thermal stratification occurred every summer and autumn in Miyun Reservoir, which was conducive to the dominance of Microcystis in the reservoir (Visser, 1996). With regard to Microcystis biomass distribution in the reservoir, the north shallow region with a relatively high z mix /z max ratio as well as the nutrient concentration had probably the highest risk for causing severe Microcystis blooms, while the other regions (west and south deep regions) were relatively safe due to high depth and low nutrient level. There is also a possibility of Microcystis occurrence in the south deep region due to the water flow along with Microcystis cells from the north shallow region. Oscillatoria showed different seasonal distribution compared to Microcystis: maximum concentration of Oscillatoria biomass was observed in September, when the decreasing Microcystis biomass in the surface layer allowed more light going through. At the same time, the nutrient in the water column enhanced by mixing process. Moreover, significant spatial variation of Oscillatoria was observed (Fig. 4b). Similar with the distribution of Microcystis, the north shallow region was also the favorable habitat for Oscillatoria owing to high nutrients (Fig. 2c) as well as low water depth. 4 Conclusions In conclusion, phytoplankton dynamics during June to October in Miyun Reservoir was characterized by shifts among Cyanophyta, Bacillariophyta and Chlorophyta. Two harmful cyanobacterial of Microcystis sp. and Oscillatoria sp. were observed in the mesotrophic reservoir with different temporal and spatial distribution patterns. Microcystis dominance occurred during most of the study period, with the maximum biomass observed in August; subsequently the Oscillatoria population increased due to the high water transparency as well as sufficient nutrient compensated by enhanced mixing process in September. Microcystis biomass was significantly correlated with water temperature as well as z mix /z max ratio; on the other hand, the Oscillatoria biomass in the surface and middle layers was significantly related with TDP, and that in the bottom layer with SD/z max ratio. Acknowledgments This work was supported by the National Natural Science Foundation of China (No. 50938007).
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Supporting materials Spatial and temporal variations of two cyanobacteria in the mesotrophic Miyun reservoir, China Ming Su, Jianwei Yu, Shenling Pan, Wei An *, Min Yang State Key Laboratory of Environmental Aquatic Chemistry, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China. E-mail: ming.su@live.com Received 18 March 2013; revised 05 August 2013; accepted 16 August 2013 Abstract: Spatial variations in phytoplankton community within a large mesotrophic reservoir (Miyun reservoir, North China) were investigated in relation to variations in physico-chemical properties, nutrient concentrations, temperature and light conditions over a 5 month period in 2009. The dynamics of phytoplankton community was represented by the dominance of cyanobacteria through summer and fall, following with a short term dominance of chlorophyta in late fall, and a relatively high abundance of diatom in October; on the other hand, maximum phytoplankton biomass was recorded in the north shallow region of Miyun reservoir with a higher nutrients level. Particular attention was paid to the impacts of environmental conditions on the growth of two cyanobacteria genera, the toxin-producing Microcystis and the taste & odor-producing Oscillatoria. Microcystis biomass was in general greatly affected by water temperature and mixing depth/local water depth ratio in this reservoir, while the Oscillatoria biomass in the surface and middle layers was greatly affected by total dissolved phosphorus, and that in the bottom layer was related with the Secchi depth/local water depth ratio. Abundant Oscillatoria biomass was observed only in late September when Microcystis biomass decreased and allowed sufficient light go through. Key words: phytoplankton community succession; Microcystis sp.; Oscillatoria sp.; mesotrophic reservoir; total dissolved phosphorus; water transparency; mixing process DOI: 10.1016/S1001-0742(13)60433-7 --------------------------------- * Corresponding author. E-mail: anwei@rcees.ac.cn
je sc.ac.cn Fig. S1 The bathymetry map of Miyun reservoir
Fig. S2 Seasonal fluctuation (x axis) and vertical distribution (y axis) of water temperature (A), chlorophyll α (B), dissolved oxygen (DO, C) and ph (D) in Miyun reservoir, as well as the comparison between north shallow zone (MY05) and south deep zone (MY08). The color bar represents the value of each parameter.
Fig. S3 Seasonal fluctuation (x-axis) and vertical distribution (y-axis) of TDN (A), TDP (B), NO 3 -N (C) and NH 4 -N (D) in Miyun reservoir, as well as the comparison between north shallow zone (MY05) and south deep zone (MY08). The color bar represents the value of each parameter.
Fig. S4 The spatial distribution of water transparency in Miyun reservoir in September. Jun 02 Jul 14 Aug 04 Sep 08 Sep 22 Sep 28 Oct 26 Bacillariophyta Chlorophyta Chrysophyta Cyanophyta Euglenophyta Pyrrhophyta Fig. S5 The phytoplankton community (phylum level, cells number) succession in Miyun reservoir in 2009. The size of each pie chart represent the density of algal cells.
Fig. S6 The spatial distribution of total phytoplankton in September in Miyun reservoir; the size of each pie chart represent the algal cell number, and the color represent the different depth (white: Surface water, gray: Middle layer, Black: Bottom layer).
Fig. S7 Significant correlations between Microcystis biomass (log transferred logρ m ) and water temperature. The data are from the surface sample in north zone during the study period; the thick solid lines are the linear regressions, and the thin dashed lines are 95% confidence interval (CI) of corresponding regressions. (As each parameter has missing values in different sampling date and/or sites, the data present in the figures were not in accordance with each other)
Fig. S8 Significant correlations between Microcystis biomass (log transferred logρ m ) and a. (top) ph as well as b. (bottom) water transparency (SD). The data are from the surface sample in whole reservoir in September 08; the thick solid lines are the linear regressions, and the thin dashed lines are 95% confidence interval (CI) of corresponding regressions. (As each parameter has missing values in different sampling date and/or sites, the data present in the plots were not in accordance with each other)
Editor-in-Chief Hongxiao Tang Associate Editors-in-Chief Jiuhui Qu Shu Tao Nigel Bell Po-Keung Wong Editorial Board of Journal of Environmental Sciences Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences China Research Center for Eco-Environmental Sciences, Peking University, China Imperial College London, United Kingdom The Chinese University of Hong Kong, Hong Kong, China Editorial Board Aquatic environment Baoyu Gao Shandong University, China Maohong Fan University of Wyoming, USA Chihpin Huang National Chiao Tung University Taiwan, China Ng Wun Jern Nanyang Environment & Water Research Institute, Singapore Clark C. K. Liu University of Hawaii at Manoa, USA Hokyong Shon University of Technology, Sydney, Australia Zijian Wang Research Center for Eco-Environmental Sciences, Zhiwu Wang The Ohio State University, USA Yuxiang Wang Queen s University, Canada Min Yang Research Center for Eco-Environmental Sciences, Zhifeng Yang Beijing Normal University, China Han-Qing Yu University of Science & Technology of China Terrestrial environment Christopher Anderson Massey University, New Zealand Zucong Cai Nanjing Normal University, China Xinbin Feng Institute of Geochemistry, Hongqing Hu Huazhong Agricultural University, China Kin-Che Lam The Chinese University of Hong Kong Hong Kong, China Erwin Klumpp Research Centre Juelich, Agrosphere Institute Germany Peijun Li Institute of Applied Ecology, Michael Schloter German Research Center for Environmental Health Germany Xuejun Wang Peking University, China Lizhong Zhu Zhejiang University, China Atomospheric environment Jianmin Chen Fudan University, China Abdelwahid Mellouki Centre National de la Recherche Scientifique France Yujing Mu Research Center for Eco-Environmental Sciences, Min Shao Peking University, China James Jay Schauer University of Wisconsin-Madison, USA Yuesi Wang Institute of Atmospheric Physics, Xin Yang University of Cambridge, UK Environmental biology Yong Cai Florida International University, USA Henner Hollert RWTH Aachen University, Germany Jae-Seong Lee Hanyang University, South Korea Christopher Rensing University of Copenhagen, Denmark Bojan Sedmak National Institute of Biology, Ljubljana Lirong Song Institute of Hydrobiology, the Chunxia Wang National Natural Science Foundation of China Gehong Wei Northwest A & F University, China Daqiang Yin Tongji University, China Zhongtang Yu The Ohio State University, USA Environmental toxicology and health Jingwen Chen Dalian University of Technology, China Jianying Hu Peking University, China Guibin Jiang Research Center for Eco-Environmental Sciences, Sijin Liu Research Center for Eco-Environmental Sciences, Tsuyoshi Nakanishi Gifu Pharmaceutical University, Japan Willie Peijnenburg University of Leiden, The Netherlands Bingsheng Zhou Institute of Hydrobiology, Environmental catalysis and materials Hong He Research Center for Eco-Environmental Sciences, Junhua Li Tsinghua University, China Wenfeng Shangguan Shanghai Jiao Tong University, China Yasutake Teraoka Kyushu University, Japan Ralph T. Yang University of Michigan, USA Environmental analysis and method Zongwei Cai Hong Kong Baptist University, Hong Kong, China Jiping Chen Dalian Institute of Chemical Physics, Minghui Zheng Research Center for Eco-Environmental Sciences, Municipal solid waste and green chemistry Pinjing He Tongji University, China Environmental ecology Rusong Wang Research Center for Eco-Environmental Sciences, Editorial office staff Managing editor Editors English editor Qingcai Feng Zixuan Wang Suqin Liu Zhengang Mao Catherine Rice (USA) Copyright Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences. Published by Elsevier B.V. and Science Press. All rights reserved.
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