Spatial and temporal assessment of the initial pattern of phytoplankton population in a newly built coastal reservoir

Xiangyu REN , Kai YANG , Yue CHE , Mingwei WANG , Lili ZHOU , Liqiao CHEN

Front. Earth Sci. ›› 2016, Vol. 10 ›› Issue (3) : 546 -559.

PDF (1389KB)
Front. Earth Sci. ›› 2016, Vol. 10 ›› Issue (3) : 546 -559. DOI: 10.1007/s11707-015-0543-2
RESEARCH ARTICLE
RESEARCH ARTICLE

Spatial and temporal assessment of the initial pattern of phytoplankton population in a newly built coastal reservoir

Author information +
History +
PDF (1389KB)

Abstract

For decades, the main threat to the water security of a metropolis, such as the city of Shanghai, has been the rapidly growing demand for water and at the same time, the decrease in water quality, including eutrophication. Therefore Shanghai shifted the preferred freshwater source to the Yangtze Estuary and constructed the Qingcaosha Reservoir, which is subject to less eutrophic water from the Yangtze River. To assess the population of phytoplankton for the first time in the newly built reservoir, this study improved an integrated method to assess the phytoplankton pattern in large-water-area reservoirs and lakes, using partial triadic analysis and Geographic Information Systems. Monthly sampling and monitoring from 10 stations in the reservoir from July 2010 to December 2011 were conducted. The study examined the common pattern of the phytoplankton population structure and determined the differences in the specific composition of the phytoplankton community during the transition period of the reservoir. The results suggest that in all but three sampling stations in the upper parts of Qingcaosha Reservoir, there was a strong common compromise in 2011. The two most important periods occurred from late summer to autumn and from winter to early spring. The former was characterized by the dominance of cyanobacteria, whereas the latter was characterized by the dominance of both chlorophyta and diatoms. Cyanobacteria (Microcystis spp. as the main genus) were the monopolistic dominant species in the summer after reservoir operation. The statistical analysis also indicated the necessity for regular monitoring to focus on the stations in the lower parts of the reservoir and on several limited species.

Keywords

phytoplankton dynamics / Partial Triadic Analysis / Geographic Information Systems / management / Qingcaosha Reservoir / Shanghai

Cite this article

Download citation ▾
Xiangyu REN, Kai YANG, Yue CHE, Mingwei WANG, Lili ZHOU, Liqiao CHEN. Spatial and temporal assessment of the initial pattern of phytoplankton population in a newly built coastal reservoir. Front. Earth Sci., 2016, 10(3): 546-559 DOI:10.1007/s11707-015-0543-2

登录浏览全文

4963

注册一个新账户 忘记密码

References

[1]

Bartram J, Carmichael W, Chorus I, Jones G, Skulberg O (1999). Toxic cyanobacteria and other water-related health problems. In: Chorus I, Bartram J, eds. Toxic Cyanobacteria in Water: A Guide to Their Public Health Consequences, Monitoring and Management. London: E&FN Spon, 17–20

[2]

Bertrand F, Maumy M (2010). Using partial triadic analysis for depicting the temporal evolution of spatial structures: assessing phytoplankton structure and succession in a water reservoir. Case Studies in Business, Industry& Government Statistics, 4(1): 23–43

[3]

Calijuri M C, Dos Santos A C A, Jati S (2002). Temporal changes in the phytoplankton community structure in a tropical and eutrophic reservoir (Barra Bonita, S.P.—Brazil). J Plankton Res, 24(7): 617–634

[4]

Carassou L, Ponton D (2006). Spatio-temporal structure of pelagic larval and juvenile fish assemblages in coastal areas of New Caledonia, southwest Pacific. Mar Biol, 150(4): 697–711

[5]

Carlson R (1977). A trophic state index for lakes. Limnol Oceanogr, 22(2): 361–369

[6]

Chau K, Muttil N (2007). Data mining and multivariate statistical analysis for ecological system in coastal waters. Journal of Hydroinformatics, 9(4): 305–317

[7]

Chen Y, Fan C, Teubner K, Dokulil M (2003a). Changes of nutrients and phytoplankton chlorophyll-a in a large shallow lake, Taihu, China: an 8-year investigation. Hydrobiologia, 506‒509(1‒3): 273–279

[8]

Chen Y, Fan C, Teubner K, Dokulil M (2003b). Long-term dynamics of phytoplankton assemblages: Microcystis-domination in Lake Taihu, a large shallow lake in China. J Plankton Res, 25(4): 445–453

[9]

Chen Y, Liu R, Sun C, Zhang P, Feng C, Shen Z (2012). Spatial and temporal variations in nitrogen and phosphorous nutrients in the Yangtze River Estuary. Mar Pollut Bull, 64(10): 2083–2089

[10]

Cornelisen C D, Thomas F I M (2006). Water flow enhances ammonium and nitrate uptake in a seagrass community. Mar Ecol Prog Ser, 312: 1–13

[11]

Dai Z, Du J, Zhang X, Su N, Li J (2011). Variation of riverine material loads and environmental consuquences on the Changjiang (Yangtze) Estuary in recent decades (1955‒2008). Environ Sci Technol, 45(1): 223–227

[12]

Dokulil M T, Teubner K (2000). Cyanobacterial dominance in lakes. Hydrobiologia, 438(1/3): 1–12

[13]

Downing J A, Watson S B, Mccauley E (2001). Predicting cyanobacteria dominance in lakes. Can J Fish Aquat Sci, 58(10): 1905–1908

[14]

Dudgeon D (2000). Large-scale hydrological alterations in tropical Asia: prospects for riverine biodiversity. Bioscience, 50(9): 793–806

[15]

Figueredo C C, Giani A (2009). Phytoplankton community in the tropical lake of Lagoa Santa (Brazil): conditions favoring a persistent bloom of Cylindrospermopsis raciborskii. Limnologica, 39(4): 264–272

[16]

Gaertner J C (2000). Seasonal organization patterns of demersal assemblages in the Gulf of Lions (north-western Mediterranean Sea). J Mar Biol Assoc U K, 80(5): 777–783

[17]

Garant D, Kruuk L E B, Wilkin T A, McCleery R H, Sheldon B C (2005). Evolution driven by differential dispersal within a wild bird population. Nature, 433(7021): 60–65

[18]

Havens K E, James R T, East T L, Smith V H (2003). N: P ratios, light limitation, and cyanobacterial dominance in a subtropical lake impacted by non-point source nutrient pollution. Environ Pollut, 122(3): 379–390

[19]

Hunt R J, Matveev V F (2005). The effects of nutrients and zooplankton community structure on phytoplankton growth in a subtropical Australian reservoir: an enclosure study. Limnologica, 35(1‒2): 90–101

[20]

Karadžić V, Subakov-Simić G, Krizmanić J, Natić D (2010). Phytoplankton and eutrophication development in the water supply reservoirs Garaši and Bukulja (Serbia). Desalination, 255(1‒3): 91–96

[21]

Kummu M (2009). Water management in Angkor: human impacts on hydrology and sediment transportation. J Environ Manage, 90(3): 1413–1421

[22]

Legendre P, Fortin M (1989). Spatial pattern and ecological analysis. Vegetatio, 80(2): 107–138

[23]

Maier G, Glegg G A, Tappin A D, Worsfold P J (2012). A high resolution temporal study of phytoplankton bloom dynamics in the eutrophic Taw Estuary (SW England). Sci Total Environ, 434: 228–239

[24]

Malone T C, Crocker L H, Pike S E, Wendler B W (1988). Influences of river flow on the dynamics of phytoplankton production in a partially stratified estuary. Mar Ecol Prog Ser, 48: 235–249

[25]

Muttil N, Chau K (2006). Neural network and genetic programming for modelling coastal algal blooms. Int J Environ Pollut, 28(3/4): 223–238

[26]

Muttil N, Chau K (2007). Machine learning paradigms for selecting ecologically significant input variables. Eng Appl Artif Intell, 20(6): 735–744

[27]

Pan G, Yang B, Wang D, Chen H, Tian B, Zhang M, Yuan X, Chen J (2011). In-lake algal bloom removal and submerged vegetation restoration using modified local soils. Ecol Eng, 37(2): 302–308

[28]

Pavoine S, Blondel J, Baguette M, Chessel D (2007). A new technique for ordering asymmetrical three-dimensional data sets in ecology. Ecology, 88: 512–523

[29]

Pinckney J L, Paerl H W, Tester P, Richardson T L (2001). The role of nutrient loading and eutrophication in estuarine ecology. Environ Health Perspect, 109(s5): 699–706

[30]

Pringle C M (2001). Hydrologic connectivity and the management of biological reserves: a global perspective. Ecol Appl, 11(4): 981–998

[31]

Quiblier C, Leboulanger C, Sané S, Dufour P (2008). Phytoplankton growth control and risk of cyanobacterial blooms in the lower Senegal River delta region. Water Res, 42(4‒5): 1023–1034

[32]

Ren H, Zhang P, Liu C, Xue Y, Lian B (2010). The potential use of bacterium strain R219 for controlling of the bloom-forming cyanobacteria in freshwater lake. World J Microbiol Biotechnol, 26(3): 465–472

[33]

Robarts R D, Zohary T (1987). Temperature effects on photosynthetic capacity, respiration, and growth rates of bloom-forming cyanobacteria. N Z J Mar Freshw Res, 21(3): 391–399

[34]

Robert P, Escoufier Y (1976). A unifying tool for linear multivariate statistical methods: the RV-coefficient. Appl Stat, 25(3): 257–265

[35]

Roberts J J, Best B D, Dunn D C, Treml E A, Halpin P N (2010). Marine geospatial ecology tools: an integrated framework for ecological geoprocessing with ArcGIS, Python, R, MATLAB, and C++. Environ Model Softw, 25(10): 1197–1207

[36]

Rolland A, Bertrand F, Maumy M, Jacquet S (2009). Assessing phytoplankton structure and spatio-temporal dynamics in a freshwater ecosystem using a powerful multiway statistical analysis. Water Res, 43(13): 3155–3168

[37]

Rossi J P (2003). The spatiotemporal pattern of a tropical earthworm species assemblage and its relationship with soil structure. Pedobiologia (Jena), 47: 497–503

[38]

Schindler D W (1977). Evolution of phosphorus limitation in lakes. Science, 195(4275): 260–262

[39]

Shanghai Water Authority (2009). Shanghai water resource bulletin, 2009. 2012, 10, 27

[40]

Smith V H (1983). Low nitrogen to phosphorus ratios favor dominance by blue-green algae in lake phytoplankton. Science, 221(4611): 669–671

[41]

Soares M C S, Marinho M M, Azevedo S M O F, Branco C W C, Huszar V L M (2012). Eutrophication and retention time affecting spatial heterogeneity in a tropical reservoir. Limnologica, 42(3): 197–203

[42]

Thomas L, Buckland S T, Rexstad E A, Laake J L, Stringberg S, Hedley S L, Bishop J R B, Marques T A, Burnham K P (2010). Distance software: design and analysis of distance sampling surveys for estimating population size. J Appl Ecol, 47(1): 5–14

[43]

van Liere L, Mur L R (1979). Growth Kinetics of Oscillatoria agardhii gomont in continuous culture, limited in its growth by the light energy supply. J Gen Microbiol, 115(1): 153–160

[44]

van Liere L, Walsby A E (1982). Interactions of cyanobacteria with light. In: Burnett J H, Baker H G, Beevers H, Whatley F R, eds. The Biology of Cyanobacteria. Oxford: Blackwell, 9–45

[45]

Wu C, Chau K (2006). Mathematical model of water quality rehabilitation with rainwater utilization — A case study at Haigang. Int J Environ Pollut, 28(3/4): 534–545

[46]

Xie J, Cheng C, Chau K, Pei Y (2006). A hybrid adaptive time-delay neural network model for multi-step-ahead prediction of sunspot activity. Int J Environ Pollut, 28(3/4): 364–381

[47]

Zeng H, Song L, Yu Z, Chen H (2007). Post-impoundment biomass and composition of phytoplankton in the Yangtze River. Int Rev Hydrobiol, 92(3): 267–280

[48]

Zhao M, Cheng C, Chau K, Li G (2006). Multiple criteria data envelopment analysis for full ranking units associated to environment impact assessment. Int J Environ Pollut, 28(3/4): 448–464

RIGHTS & PERMISSIONS

Higher Education Press and Springer-Verlag Berlin Heidelberg

AI Summary AI Mindmap
PDF (1389KB)

826

Accesses

0

Citation

Detail

Sections
Recommended

AI思维导图

/