Ecological classification of lakes: Uncertainty and the influence of year-to-year variability

Regular monitoring of lakes is important to determine their ecological state and development and of key significance when deciding whether action should be taken to improve their quality, for instance by reducing the external loading of nutrients. Imprecise or inadequate knowledge of the ecological state increases the risk of misclassification and of wrong management decisions. Based on Danish lake data, we aimed to determine temporal variations, in particular natural year-to-year differences, and to describe the uncertainty in assessing the ecological state of lakes. We analysed environmental data from ca. 350 Danish lakes (1100 lake years), including three case studies, with long-term data series (up to 24 years), with no significant changes in external nutrient loading. We used summer means of selected water chemical variables, phytoplankton and submerged macrophytes as indicators of ecological state and found considerable variations in all indicators, which could not be ascribed alone to meteorological variation. In shallow lakes, chlorophyll a concentrations exhibited large year-to-year variations, especially at TP ranging between 0.05 and 0.15 mg L⁻¹ where the lakes may shift between a macrophyte- and a phytoplankton-dominated state. For example, chlorophyll a varied by a factor 5–10 between years and was particularly low when submerged macrophyte coverage exceeded 20% compared with lakes without macrophytes. Use of a multimetric index including four phytoplankton indicators reduced the coefficient of variation. Generally, the 95% confidence interval of ecological classification was approximately 50% lower when the assessment of ecological state was based on 4–5 years’ measurements than if based on only one year's measurements. Knowledge and awareness of the uncertainty of indicators used in ecological classification are highly relevant for lake managers and policy makers when defining efficient monitoring and restoration strategies.