Evaluation of a modified monod model for predicting algal dynamics in Lake Tai

Water (Switzerland)

Volumn 7, Issue 7, 2015, Pages 3626-3642

  Huang, Jian ^a,b   Xu, Qiujin ^c   Wang, Xixi ^b   Xi, Beidou ^c   Jia, Keli ^d   Huo, Shouliang ^c   Liu, Hongliang ^c   Li, Changyou ^d   Xu, Bingbing ^c  

^a BEIJING NORMAL UNIVERSITY   (China)

^b Old Dominion University   (United States)

^c CHINESE RESEARCH ACADEMY OF ENVIRONMENTAL SCIENCES   (China)

^d INNER MONGOLIA AGRICULTURAL UNIVERSITY   (China)

Author keywords

Chlorophyll a; Eutrophication; Lake modeling; Monod model; Parameterization; Time series analysis

Indexed keywords

CHLOROPHYLL; DYNAMICS; EUTROPHICATION; LAKES; NUTRIENTS; PARAMETERIZATION; TIME MEASUREMENT;

CHLOROPHYLL A; HARMFUL ALGAL BLOOMS; INDEPENDENT VARIABLES; LAKE MODEL; MONOD MODEL; MULTIPLE TIME SERIES; NUTRIENT INTERACTIONS; TEMPORAL FLUCTUATION;

TIME SERIES ANALYSIS;

AIR TEMPERATURE; CHLOROPHYLL A; CYANOBACTERIUM; EUTROPHICATION; GROWTH RATE; HYDROLOGICAL MODELING; LACUSTRINE ENVIRONMENT; NITROGEN; PARAMETERIZATION; PERFORMANCE ASSESSMENT; PHOSPHORUS; SHALLOW WATER; TIME SERIES ANALYSIS; WATER TEMPERATURE;

CHINA; TAIHU LAKE;

ALGAE; CYANOBACTERIA;

EID: 84940434913     PISSN: None     EISSN: 20734441     Source Type: Journal    
DOI: 10.3390/w7073626     Document Type: Article

References (34)

1. Hudnell, H.K. The state of U.S. freshwater harmful algal blooms assessments, policy and legislation. Toxicon 2010, 55, 1024-1034.
2. Carey, C.C.; Ibelings, B.W.; Hoffmann, E.P.; Hamilton, D.P.; Brookes, J.D. Eco-Physiological adaptations that favour freshwater cyanobacteria in a changing climate. Water Res. 2012, 46, 1394-1407.
3. Davis, T.W.; Berry, D.B.; Boyer, G.L.; Gobler, C.J. The effects of temperature and nutrients on the growth and dynamics of toxic and non-toxic strains of Microcystis during cyanobacteria blooms. Harmful Algae 2009, 8, 715-725.
4. Jones, M.L.; Shuter, B.J.; Zhao, Y.M.; Stockwell, J.D. Forecasting effects of climate change on Great Lakes fisheries: Models that link habitat supply to population dynamics can help. Can. J. Fish. Aquat. Sci. 2006, 63, 457-468.
5. Bergström, A. The use of TN:TP and DIN:TP ratios as indicators for phytoplankton nutrient limitation in oligotrophic lakes affected by N deposition. Aquat. Sci. 2010, 72, 277-281.
6. Carlson, R.E. A trophic state index for lakes. Limnol. Oceanogr. 1977, 22, 361-369.
7. Søndergaard, M.; Jeppesen, E.; Lauridsen, T.L.; Skov, C.; Van Nes, E.H.; Roijackers, R.; Lammens, E.; Portielje, R.O.B. Lake restoration: Successes, failures and long-term effects. J. Appl. Ecol. 2007, 44, 1095-1105.
8. Huang, J.; Gao, J.; Hörmann, G. Hydrodynamic-phytoplankton model for short-term forecasts of phytoplankton in Lake Taihu, China. Limnol. Ecol. Manag. Inland Waters 2012, 42, 7-18.
9. Hamilton, D.P.; Schladow, S.G. Prediction of water quality in lakes and reservoirs. Part I. Model description. Ecol. Model. 1997, 96, 91-110.
10. Arhonditsis, G.B.; Brett, M.T. Eutrophication model for Lake Washington (USA): Part I. Model description and sensitivity analysis. Ecol. Model. 2005, 187, 140-178.
11. Jørgensen, S.E. A review of recent developments in lake modeling. Ecol. Model. 2010, 221, 689-692.
12. Kayombo, S.; Mbwette, T.S.A.; Katima, J.H.Y.; Jorgensen, S.E. Effects of substrate concentrations on the growth of heterotrophic bacteria and algae in secondary facultative ponds. Water Res. 2003, 37, 2937-2943.
13. Pei, H.; Ma, J. Study on the algal dynamic model for West Lake, Hangzhou. Ecol. Model. 2002, 148, 67-77.
14. Ye, C.; Shen, Z.; Zhang, T.; Fan, M.; Lei, Y.; Zhang, J. Long-Term joint effect of nutrients and temperature increase on algal growth in Lake Taihu, China. J. Environ. Sci. 2011, 23, 222-227.
15. Siswanto, E.; Ishizaka, J.; Tripathy, S.C.; Miyamura, K. Detection of harmful algal blooms of Karenia mikimotoi using MODIS measurements: A case study of Seto-Inland Sea, Japan. Remote Sens. Environ. 2013, 129, 185-196.
16. Paerl, H.W.; Xu, H.; McCarthy, M.J.; Zhu, G.; Qin, B.; Li, Y.; Gardner, W.S. Controlling harmful cyanobacterial blooms in a hyper-eutrophic lake (Lake Taihu, China): The need for a dual nutrient (N&P) management strategy. Water Res. 2011, 45, 1973-1983.
17. Wilhelm, S.W.; Farnsley, S.E.; LeCleir, G.R.; Layton, A.C.; Satchwell, M.F.; DeBruyn, J.M.; Boyer, G.L.; Zhu, G.; Paerl, H.W. The relationships between nutrients, cyanobacterial toxins and the microbial community in Taihu (Lake Tai), China. Harmful Algae 2011, 10, 207-215.
18. Qin, B.; Zhu, G.; Gao, G.; Zhang, Y.; Li, W.; Paerl, H.W.; Carmichael, W.W. A drinking water crisis in Lake Taihu, China: Linkage to climatic variability and lake management. Environ. Manag. 2010, 45, 105-112.
19. Huang, C.; Li, Y.; Yang, H.; Sun, D.; Yu, Z.; Zhang, Z.; Chen, X.; Xu, L. Detection of algal bloom and factors influencing its formation in Taihu Lake from 2000 to 2011 by MODIS. Environ. Earth Sci. 2014, 71, 3705-3714.
20. Xie, L.; Xie, P.; Tang, H. Enhancement of dissolved phosphorus release from sediment to lake water by Microcystis blooms: An enclosure experiment in a hyper-eutrophic, subtropical Chinese lake. Environ. Pollut. 2003, 122, 391-399.
21. SEPA (State Environmental Protection Administration). Water and Wastewater Monitoring and Analysis Methods, 4th ed.; Environmental Science Press: Beijing, China, 2002.
22. Wang, X.; Yang, X.; Liu, T.; Li, F.; Gao, R.; Duan, L.; Luo, Y. Trend and extreme occurrence of precipitation in a mid-latitude Eurasian steppe watershed at various time scales. Hydrol. Process. 2013, 28, 5547-5560.
23. Goldman, J.C.; Carpenter, E.J. A kinetic approach to the effect of temperature on algal growth. Limnol. Oceanogr. 1974, 19, 756-766.
24. Akaike, H. A new look at the statistical model identification. IEEE Trans. Autom. Contrl. 1974, 19, 716-723, doi:10.1109/TAC.1974.1100705.
25. Cross, W.; Hood, J.; Benstead, J.P.; Huryn, A.D.; Nelson, D. Interactions between temperature and nutrients across levels of ecological organization. Glob. Chang. Biol. 2015, 21, 1025-1040, doi:10.1111/gcb.12809.
26. Capblancq, J. Nutrient dynamics and pelagic food web interactions in oligotrophic and eutrophic environments: An overview. Hydrobiologia 1990, 207, 1-14.
27. Dokulil, M.; Chen, W.; Cai, Q. Anthropogenic impacts to large lakes in China: The Tai Hu example. Aquat. Ecosyst. Health Manag. 2000, 3, 81-94.
28. Chen, Y.; Fan, C.; Teubner, K.; Dokulil, M. Changes of nutrients and phytoplankton chlorophyll-a in a large shallow lake, Taihu, China: An 8-year investigation. Hydrobiologia 2003, 506-509, 273-279.
29. Huang, J.; Xu, Q.; Xi, B.; Wang, X.; Jia, K.; Huo, S.; Su, J.; Zhang, T.; Li, C. Effects of lake-basin morphological and hydrological characteristics on the eutrophication of shallow lakes in east China. J. Gt. Lakes Res. 2014, 40, 666-674, doi:10.1016/j.jglr.2014.04.016.
30. Xu, H.; Paerl, H.W.; Qin, B.; Zhu, G.; Hall, N.S.; Wu, Y. Determining critical nutrient thresholds needed to control harmful cyanobacterial blooms in eutrophic Lake Taihu, China. Environ. Sci. Technol. 2015, 49, 1051-1059.
31. Orihel, D.M.; Schindler, D.W.; Ballard, N.C.; Graham, M.D.; O'Connell, D.W.; Wilson, L.R.; Vinebrooke, R.D. The "nutrient pump:" Iron-poor sediments fuel low nitrogen-to-phosphorus ratios and cyanobacterial blooms in polymictic lakes. Limnol. Oceanogr. 2015, 60, 856-871.
32. Molot, L.A.; Watson, S.B.; Creed, I.F.; Trick, C.G.; McCabe, S.K.; Verschoor, M.J.; Sorichetti, R.J.; Powe, C.; Venkiteswaran, J.J.; Schiff, S.L. A novel model for cyanobacteria bloom formation: The critical role of anoxia and ferrous iron. Freshw. Biol. 2014, 59, 1323-1340.
33. Beaulieu, M.; Pick, F.; Palmer, M.; Watson, S.; Winter, J.; Zurawell, R.; Gregory-Eaves, I. Comparing predictive cyanobacterial models from temperate regions. Can. J. Fish. Aquat. Sci. 2014, 71, 1830-1839.
34. Taranu, Z.E.; Gregory-Eaves, I.; Leavitt, P.R.; Bunting, L.; Buchaca, T.; Catalan, J.; Domaizon, I.; Guilizzoni, P.; Lami, A.; McGowan, S.; et al. Acceleration of cyanobacterial dominance in north temperate-subarctic lakes during the Anthropocene. Ecol. Lett. 2015, 18, 375-384.