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Modelling and prediction of phyto- and zooplankton dynamics in Lake Kasumigaura by artificial neural networks |
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| Authors: | Friedrich Recknagel Takehiko Fukushima Takayuki Hanazato Noriko Takamura Hugh Wilson |
| Affiliation: | University of Adelaide, Department of Environmental Science, Roseworthy, South Australia 5371, Australia;Hiroshima University, Department of Civil and Environmental Engineering, Hiroshima 739, Japan;National Institute for Environmental Studies, PO Onogawa, Tsukuba, Ibaraki 305, Japan |
| Abstract: | An artificial neural network model was developed for Lake Kasumigaura to predict timing and magnitudes for chlorophyll a, five species of blue-green algae and three zooplankton groups. The model was trained by 8 years of limnological time series and validated by two independent years. The validation showed the potential of neural networks as predictive tools for highly non-linear phenomena such as blue-green algal blooms in freshwater lakes. |
| Keywords: | artificial neural networks Lake Kasumigaura plankton dynamics predictive modelling |