Recent studies have highlighted the impact of the winter North Atlantic Oscillation (NAO) on water temperature, ice conditions, and spring plankton phenology in specific lakes and regions in Europe. Here, we use meta-analysis techniques to test whether 18 lakes in northern, western, and central Europe respond coherently to winter climate forcing, and to assess the persistence of the winter climate signal in physical, chemical, and biological variables during the year. A meta-analysis approach was chosen because we wished to emphasize the overall coherence pattern rather than individual lake responses. A particular strength of our approach is that time-series from each of the 18 lakes were subjected to the same robust statistical analysis covering the same 23-year period. Although the strongest overall coherence in response to the winter NAO was exhibited by lake water temperatures, a strong, coherent response was also exhibited by concentrations of soluble reactive phosphorus and soluble reactive silicate, most likely as a result of the coherent response exhibited by the spring phytoplankton bloom. Lake nitrate concentrations showed significant coherence in winter. With the exception of the cyanobacterial biomass in summer, phytoplankton biomass in all seasons was unrelated to the winter NAO. A strong coherence in the abundance of daphnids during spring can most likely be attributed to coherence in daphnid phenology. A strong coherence in the summer abundance of the cyclopoid copepods may have been related to a coherent change in their emergence from resting stages. We discuss the complex nature of the potential mechanisms that drive the observed changes.

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1. The lakes in the Windermere catchment are all deep, glacial lakes but they differ in size, shape and general productivity. Here, we examine the extent to which year‐to‐year variations in the physical, chemical and biological characteristics of these lakes varied synchronously over a 30–40‐year period. 2. Coherence was estimated by correlating time‐series of the spring, summer, autumn and winter characteristics of five lakes: Esthwaite Water, Blelham Tarn, Grasmere and the North and South Basins of Windermere. Three physical, four chemical and two biological time‐series were analysed and related to year‐to‐year variations in a number of key driving variables. 3. The highest levels of coherence were recorded for the physical and chemical variables where the average coherence was 0.81. The average coherence for the biological variables was 0.11 and there were a number of significant negative relationships. The average coherence between all possible lake pairs was 0.59 and average values ranged from 0.50 to 0.74. A graphical analysis of these results demonstrated that the coherence between individual lake pairs was influenced by the relative size of the basins as well as their trophic status. 4. A series of examples is presented to demonstrate how a small number of driving variables influenced the observed levels of coherence. These range from a simple example where the winter temperature of the lakes was correlated with the climatic index known as the North Atlantic Oscillation, to a more complex example where the summer abundance of zooplankton was correlated with wind‐mixing. 5. The implications of these findings are discussed and a conceptual model developed to illustrate the principal factors influencing temporal coherence in lake systems. The model suggests that our ability to detect temporal coherence depends on the relative magnitude of three factors: (a) the amplitude of the year‐to‐year variations; (b) the spatial heterogeneity of the driving variables and (c) the error terms associated with any particular measurement.

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The Protein Identification Resource, which provides the scientific community with an efficient on-line computer system designed for the identification and analysis of protein sequences and their corresponding coding sequences, has been established. The resource consists of an integrated computer system composed of a number of protein and nucleic acid sequence databases and the software necessary to analyze this information effectively.