ANNA - Artificial Neural Network model for predicting species abundance and succession of blue-green algae

Hydrobiologia

Volumn 349, Issue 1-3, 1997, Pages 47-57

  Recknagel, Friedrich ^a  

^a UNIVERSITY OF ADELAIDE   (Australia)

Author keywords

Artificial neural networks; Blue green algae; Harmful blooms; Operational control; Predictive modelling; Scenario analysis; Species succession

Indexed keywords

ANNA; BLUE-GREEN ALGAE; COMMUNITY COMPOSITION; CYANOBACTERIA; NEURAL NETWORK; PREDICTIVE MODEL; SUCCESSION;

EID: 0030809170     PISSN: 00188158     EISSN: None     Source Type: Journal    
DOI: 10.1023/a:1003041427672     Document Type: Article

References (14)

1. Bierman, V. J., 1976. Mathematical model of the selective enhancement of blue-green algae by nutrient enrichment. In Canale, R. P. (ed.), Modeling Biochemical Processes in Aquatic Ecosystems. Ann Arbour Science Publishers Inc., Ann Arbour: 1-32.
2. Chapra, S. C. & P. R. Canale, 1991. Long-term phenomenological model of phosphorus and oxygen for stratified lakes. Wat. Res. 25: 707-715.
3. Dillon, P. J. & F. H. Rigler, 1975. The phosphorus-chlorophyll relationship in lakes. Limnol. Oceanogr. 19: 767-773.
4. Okada, M. & S. Aiba, 1983. Simulation of water blooms in a eutrophic lake. Modeling the vertical migration in a population of Microcystis aeruginosa. Wat. Res. 20: 485-490.
5. Recknagel, F., M. Hosomi, T. Fukushima & D.-S. Kong, 1995. Short- and long-term control of external and internal phosphorus loads in lakes - a scenario analysis. Wat. Res. 29: 1767-1779.
6. Recknagel, F., T. Petzoldt, O. Jaeke & F. Krusche, 1994. Hybrid expert system DELAQUA - a toolkit for water quality control of lakes and reservoirs. Ecol. Modell. 71: 17-36.
7. Recknagel, F., M. French, P. Harkonen & K.-I. Yabunaka, 1997a. Artificial neural network approach for modelling and prediction of algal blooms. Ecol. Modell., 96: 11-28.
8. Recknagel, F., T. Fukushima, T. Hanazato, N. Takamura & H. Wilson, 1997b. Modelling and prediction of phyto- and zooplankton dynamics in Lake Kasumigaura by artificial neural networks. Lakes & Reservoirs (in press).
9. Reynolds, C. S., 1984. The Ecology of Freshwater Phytoplankton. Cambridge University Press, Cambridge, 384 pp.
10. Rigler, F. H. & R. H. Peters, 1995. Science and Limnology. In Kinne, O. (ed.), Excellence in Ecology 6, Ecological Institute, Oldendorf, 239 pp.
11. Sakamoto, M., 1966. Primary production by phytoplankton community in some Japanese lakes and its dependence on lake depth. Arch. Hydrobiol. 62: 1-28.
12. Takamura, N., A. Otsuki, M. Aizaki & Y. Nojiri, 1992. Phytoplankton species shift accompanied by transition from nitrogen dependence to phosphorus dependence of primary production in Lake Kasumigaura, Japan. Arch. Hydrobiol. 124: 129-148.
13. Vollenweider, R., 1976. Advances in defining critical loading levels for phosphorus in lake eutrophication. Mem. Ist. ital. Idrobiol. 33: 53-83.
14. Whitehead, P. & G. Hornberger, 1984. Modelling algal behaviour in the River Thames. Wat. Res. 18: 945-953.