Abstract
Long-term time-series of the eutrophic Dutch lakes Veluwemeer and Wolderwijd were subject to ordination and clustering by means of non-supervised artificial neural networks (ANN). A combination of bottom-up and top-down eutrophication control measures has been implemented in both lakes since 1979. Dividing time-series data from 1976 to 1993 into three distinctive management periods has facilitated a comparative analysis of the two lakes regarding both the seasonal and long-term dynamics in response to eutrophication control. Results of the study have demonstrated that non-supervised ANN are an alternative technique: (1) to elucidate causal relationships of complex ecological processes, and (2) to reveal long-term behaviours of ecosystems in response to different management approaches. It has been shown that external nutrient control combined with food web manipulation have turned both lakes from nitrogen to phosphorus limitation, and from blue-green algae to diatom and green algae dominance.
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