Assessment of the Eutrophication-Related Environmental Parameters in Two Mediterranean Lakes by Integrating Statistical Techniques and Self-Organizing Maps.

摘要: During the last decades, Mediterranean freshwater ecosystems, especially lakes, have been under severe pressure due to increasing eutrophication and water quality deterioration. In this article, we compared effectiveness of different data analysis methods by assessing contribution environmental parameters processes. For purpose, principal components (PCA), cluster analysis, a self-organizing map (SOM) were applied, using from two transboundary lakes North Greece. SOM is considered as an advanced powerful tool because its ability represent complex nonlinear relationships among multivariate sets. The results PCA agreed with results, although latter provided more information visualization abilities regarding parameters’ relationships. Besides nutrients that found be key factor for controlling chlorophyll-a (Chl-a), temperature was related positively algal production, while Secchi disk depth parameter highly important negatively toeutrophic conditions. general, specific allowed direct associations between variables. Our work showed SOMs can used effectively in limnological studies produce robust interpretable aiding scientists managers cope problems such eutrophication.