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This study aims at bridging the gap between freshwater and marine eutrophication studies by presenting (1) a cross-system analysis of the relationship between chlorophyll and the total nitrogen (TN) to total phosphorus (TP) ratio (2) a general model to predict concentrations of cyanobacteria from data on TP, the TN/TP-ratio, salinity and temperature, and (3) a general trophic level classification for aquatic systems based on chlorophyll classes (for oligo-, meso-, eu-and hypertrophic systems). The data compiled in this study concerns more than 500 lakes and coastal areas covering a very wide domain in terms of nutrient concentrations and salinity. There was no simple relationship between the TN/TP-ratio and empirical chlorophyll concentrations or concentrations of cyanobacteria. Variations in TP rather than TN generally seem to be more important to predict variations among systems in chlorophyll-a and cyanobacteria. Different "bioavailable" forms of the nutrients (DIN, DIP, phosphate, nitrate, etc.) have been shown to have very high coefficients of variation (CV), which means that many samples are needed to obtain reliable empirical data which are necessary in models aiming for high predictive power and practical usefulness.

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This work introduces an interpretational key to quantify and understand how much of variations among lakes in fundamental ecosystem characteristics that may be related to lake morphometry, catchment area features, measurement uncertainties and other factors (mostly climate). The size and form of lakes regulate many general transport processes, such as sedimentation, internal loading and outflow, which in turn regulate many abiotic state variables, such as concentrations of phosphorus, colour, water chemical variables and water clarity, which regulate primary production, which regulate secondary production. This paper discusses relationships between key abiotic state variables, lake morphometry and catchment area characteristics using empirical/statistical analyses based on data from 95 lakes. It has been shown that of the studied variables Secchi depth depends most on morphometry (34%); 31% of the variations among the lakes in Secchi depth may be related to catchment area characteristics, 1% to uncertainties in empirical data and 34% to ''other'' (climatological) factors. The corresponding figures for alkalinity, which depends least on lake morphometry are, 0% related to morphometry, 34% to catchment conditions, 1% to empirical uncertainty and 58% to other causes. For all other studied variables, i.e., conductivity, hardness (CaMg), calcium, iron, colour, pH and phosphorus the corresponding figures vary between these values. The interpretational key helps to explain the mechanistic reasons for these statistical/empirical results. Introduction and aim

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