Variation of phytoplankton community before an induced cyanobacterial (Arthrospira platensis) bloom

Journal of Environmental Sciences

Volumn 21, Issue 12, 2009, Pages 1632-1638

  WANG, Chong ^a   HUANG, Yingying ^a   HE, Shengbing ^a   LIN, Yan ^a   WANG, Xinze ^a   KONG, Hainan ^a  

^a SHANGHAI JIAO TONG UNIVERSITY   (China)

Author keywords

bloom; community; cyanobacteria; early warning; pigments

Indexed keywords

ARTHROSPIRA PLATENSIS; BLOOM COMMUNITY; COMMUNITY; COMMUNITY STRUCTURES; CORRELATION ANALYSIS; DIVERSITY INDEX; EARLY WARNING; IN-SITU; PHYTOPLANKTON COMMUNITY; WATER CHEMISTRY;

ALGAE CONTROL; PAINT; PHYTOPLANKTON; WATER ANALYSIS;

BLOOMS (METAL);

CHLOROPHYLL; WATER;

ALGAL BLOOM; COMMUNITY STRUCTURE; CORRELATION; CYANOBACTERIUM; DIVERSITY INDEX; GREEN ALGA; PHYTOPLANKTON; WATER CHEMISTRY;

ALGAL BLOOM; ARTICLE; CHEMISTRY; CYANOBACTERIUM; ECOSYSTEM; PHYTOPLANKTON;

CHLOROPHYLL; CYANOBACTERIA; ECOSYSTEM; HARMFUL ALGAL BLOOM; PHYTOPLANKTON; WATER;

ALGAE; ARTHROSPIRA PLATENSIS; CYANOBACTERIA;

EID: 72149103263     PISSN: 10010742     EISSN: None     Source Type: Journal    
DOI: 10.1016/S1001-0742(08)62466-3     Document Type: Article

References (42)

1. Ahn C.Y., Joung S.H., Yoon S.K., and Oh H.M. Alternative alert system for cyanobacterial bloom, using phycocyanin as a level determinant. Journal of Microbiology 45 2 (2007) 98-104
2. APHA (American Public Health Association), 1998. Standard Methods for the Examination of Water and Wastewater (20th ed.). Washington, DC.
3. Bartram J., Burch M., Falconer I.R., Jones G., and Kuiper-Goodman T. Situation assessment, planning and management. In: Chorus I., and Bartram J. (Eds). Toxic Cyanobacteria in Water (1999), E & FN Spon, London 179-209
4. Beutler M., Wiltshire K.H., Meyer B., Moldaenke C., Luring C., Meyerhofer M., et al. A fluorometric method for the differentiation of algal populations in vivo and in situ. Photosynthesis Research 72 1 (2002) 39-53
5. Carini S.A., and Joye S.B. Nitrification in Mono Lake, California: Activity and community composition during contrasting hydrological regimes. Limnology and Oceanography 53 6 (2008) 2546-2557
6. Carmichael W.W. Health effects of toxin-producing cyanobacteria: "The CyanoHABs". Human and Ecological Risk Assessment 7 5 (2001) 1393-1407
7. Chau K.W. Algal bloom prediction with particle swarm optimization algorithm. In: Hao Y., Liu J., Wang Y., et al. (Eds). Computational Intelligence and Security (2005), Springer, Berlin 645-650
8. Cremen M., Martinez-Goss M., Corre V., and Azanza R. Phytoplankton bloom in commercial shrimp ponds using green-water technology. Journal of Applied Phycology 19 6 (2007) 615-624
9. Elliott J.A., Thackeray S.J., Huntingford C., and Jones R.G. Combining a regional climate model with a phytoplankton community model to predict future changes in phytoplankton in lakes. Freshwater Biology 50 8 (2005) 1404-1411
10. Ferber L.R., Levine S.N., Lini A., and Livingston G.P. Do cyanobacteria dominate in eutrophic lakes because they fix atmospheric nitrogen?. Freshwater Biology 49 6 (2004) 690-708
11. Greisberger S., and Teubner K. Does pigment composition reflect phytoplankton community structure in differing temperature and light conditions in a deep alpine lake? An approach using HPLC and delayed fluorescence techniques. Journal of Phycology 43 6 (2007) 1108-1119
12. Guven B., and Howard A. Modelling the growth and movement of cyanobacteria in river systems. Science of the Total Environment 368 2-3 (2006) 898-908
13. Hillebrand H., Durselen C.D., Kirschtel D., Pollingher U., and Zohary T. Biovolume calculation for pelagic and benthic microalgae. Journal of Phycology 35 2 (1999) 403-424
14. Inamori Y., Sugiura N., Iwami N., Matsumura M., Hiroki M., and Watanabe M.M. Degradation of the toxic cyanobacterium Microcystis viridis using predaceous micro-animals combined with bacteria. Phycological Research 46 Suppl. (1998) 37-44
15. Jewett E B, Lopez C B, Dortch Q, Etheridge S M, 2007. National assessment of efforts to predict and respond to harmful algal blooms in U.S. Waters. Interim Report. Interagency. Washington, DC.
16. Jin X.C., Li Z.C., Zheng S.F., Yang S.W., Hu X.Z., and Chu Z.S. Studies on the growth characteristics of Microcystis aeruginosa. Research of Environmental Sciences 17 Suppl. (2004) 52-54 61.
17. Jin X.C., Xu Q.J., and Huang C.Z. Current status and future tendency of lake eutrophication in China. Science in China Series C-Life Sciences 48 (2005) 948-954
18. Kneale P.E., and Howard A. Statistical analysis of algal and water quality data. Hydrobiologia 349 (1997) 59-63
19. Levine S.N., and Schindler D.W. Influence of nitrogen to phosphorus supply ratios and physicochemical conditions on cyanobacteria and phytoplankton species composition in the experimental lakes area, Canada. Canadian Journal of Fisheries and Aquatic Sciences 56 3 (1999) 451-466
20. Oberholster P.J., Botha A.M., and Cloete T.E. Toxic cyanobacterial blooms in a shallow, artificially mixed urban lake in Colorado, USA. Lakes and Reservoirs: Research and Management 11 2 (2006) 111-123
21. Paerl H.W., Fulton III R.S., Moisander P.H., and Dyble J. Harmful freshwater algal blooms, with an emphasis on cyanobacteria. The Scientific World 1 (2001) 76-113
22. Quirós R, 2002. The nitrogen to phosphorus ratio for lakes: A cause or a consequence of aquatic biology? In: Water in Ibero-America: From Limnology to Management in South America. CYTED XVII (Fernandez Cirelli A, Chalar Marquisa G, eds.). Madrid, Spain. 11-26.
23. Recknagel F., French M., Harkonen P., and Yabunaka K. Artificial neural network approach for modelling and prediction of algal blooms. Ecological Modelling 96 1-3 (1997) 11-28
24. Reynolds C.S. Non-determinism to probability, or N:P in the community ecology of phytoplankton. Archiv fur Hydrobiologie 146 1 (1999) 23-35
25. Reynolds C.S., Irish A.E., and Elliott J.A. The ecological basis for simulating phytoplankton responses to environmental change (PROTECH). Ecological Modelling 140 3 (2001) 271-291
26. Roelke D., and Buyukates Y. The diversity of harmful algal bloom-triggering mechanisms and the complexity of bloom initiation. Human and Ecological Risk Assessment 7 5 (2001) 1347-1362
27. Sanchez-Luna L.D., Bezerra R.P., Matsudo M.C., Sato S., Converti A., and de Carvalho J.C.M. Influence of pH, temperature, and urea molar flowrate on Arthrospira platensis fedbatch cultivation: A kinetic and thermodynamic approach. Biotechnology and Bioengineering 96 4 (2007) 702-711
28. Sarmento H., and Descy J.P. Use of marker pigments and functional groups for assessing the status of phytoplankton assemblages in lakes. Journal of Applied Phycology 20 6 (2008) 1001-1011
29. Sellner K.G., Doucette G.J., and Kirkpatrick G.J. Harmful algal blooms: causes, impacts and detection. Journal of Industrial Microbiology & Biotechnology 30 7 (2003) 383-406
30. Seppälä J., and Balode M. The use of spectral fluorescence methods to detect changes in the phytoplankton community. Hydrobiologia 363 1 (1997) 207-217
31. Shapiro J. The role of carbon dioxide in the initiation and maintenance of blue-green dominance in lakes. Freshwater Biology 37 2 (1997) 307-323
32. Smith V.H. Low nitrogen to phosphorus ratios favor dominance by blue-green algae in lake phytoplankton. Science 221 4611 (1983) 669-671
33. Smith V.H. Phytoplankton response to eutrophication in inland waters. Introduction to Applied Phycology (1990), Academic Publishers, Hague 231-249
34. Smith V.H., and Bennett S.J. Nitrogen:phosphorus supply ratios and phytoplankton community structure in lakes. Archiv fur Hydrobiologie 146 1 (1999) 37-53
35. Sollie S., and Verhoeven J. Nutrient cycling and retention along a littoral gradient in a Dutch shallow lake in relation to water level regime. Water, Air, and Soil Pollution 193 1-4 (2008) 107-121
36. Sthapit E., Ochs C., and Zimba P. Spatial and temporal variation in phytoplankton community structure in a southeastern U.S. reservoir determined by HPLC and light microscopy. Hydrobiologia 600 1 (2008) 215-228
37. Sun J., and Liu D. Geometric models for calculating cell biovolume and surface area for phytoplankton. Journal of Plankton Research 25 11 (2003) 1331-1346
38. 2 and Pheopigments in Marine and Freshwater Algae by Visible Spectrophotometry. USEPA Method 446.0, Revision 1.2. Cincinnati, OH: U.S. Environmental Protection Agency.
39. Wei B., Sugiura N., and Maekawa T. Use of artificial neural network in the prediction of algal blooms. Water Research 35 8 (2001) 2022-2028
40. Wever A.D., Muylaert K., Langlet D., Alleman L., Descy J.P., Andre L., et al. Differential response of phytoplankton to additions of nitrogen, phosphorus and iron in Lake Tanganyika. Freshwater Biology 53 2 (2008) 264-277
41. Xie L.Q., Xie P., Li S.X., Tang H.J., and Liu H. The low TN:TP ratio, a cause or a result of Microcystis blooms?. Water Research 37 9 (2003) 2073-2080
42. Yabunaka K.I., Hosomi M., and Murakami A. Novel application of a back-propagation artificial neural network model formulated to predict algal bloom. Water Science and Technology 36 5 (1997) 89-97