A dynamic simulation model for the blooming of Oscillatoria agardhii in a monomictic lake
The occurrence of phytoplankton blooms is a common problem in water bodies. The quantitative description of the algal population growth is of primary importance to understand the mechanisms which lead to these phytoplankton blooms, hence also for the development of a successful water-quality managem...
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Veröffentlicht in: | Ecological modelling 1995, Vol.78 (1), p.17-24 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | The occurrence of phytoplankton blooms is a common problem in water bodies. The quantitative description of the algal population growth is of primary importance to understand the mechanisms which lead to these phytoplankton blooms, hence also for the development of a successful water-quality management. Due to the high degree of complexity of phytoplankton blooms, dynamic simulation models may be a powerful tool to study and elucidate the mechanisms leading to these blooms.
In the present study, a simulation model for the blooming of a natural population of
Oscillatoria agardhii in Lake Vechten (lat. 52°04′N, long. 5°05′E, the Netherlands) using measured temperature, filament length and nutrient concentrations as external drives, is presented. The lake was sampled weekly from January to the middle of May, 1992. Temperature, nutrient concentration (nitrate and phosphate in the water) and filament length were recorded. Because cell size was constant, filament length could be converted to number of cells per litre to estimate algal biomass. To implement the model additional information, e.g. some algal growth parameters, was obtained from the literature.
The model simulated well the growth of the
Oscillatoria agardhii population in the lake during the research period. According to the model, temperature was the most important rate-limitating factor for growth at the beginning of the year. Nutrient limitation became increasingly important while the importance of temperature limitation decreased during the season. During the whole period, light was strongly limiting and became the most important rate-limiting factor in the second week of April.
Via sensitivity analysis, the model showed to be highly affected by temperature-related factors, and it was useful in the identification of research needs. |
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ISSN: | 0304-3800 1872-7026 |
DOI: | 10.1016/0304-3800(94)00114-W |