Summary 1. Species assemblages of diatoms, rotifers, chydorids, planktonic crustaceans and chironomids were studied in 235 alpine lakes in the Alps, Pyrenees, Tatras (Western Carpathians), Retezat (Southern Carpathians) and Rila Mountains (Balkans). 2. For all taxonomic groups we found a hierarchical structure in the community assemblage using distinct scales of lake clustering (number of k‐means groups) based on species composition similarity (Hellinger distance). We determined the optimal partition in assemblage types (i.e. number of lake clusters) for each taxonomic group by maximising the sum of the taxon indicative value (IndVal) and performed discriminant analyses, using environmental variables not conditioned by geographical patterns. Relevant environmental variables differed among and within taxonomic groups. Therefore the assemblages respond to a complex environmental mosaic, with the exception of diatom assemblages, which followed an acid–base gradient. 3. The significant environmental variables could be grouped into four general factors: lake size, tropho‐dynamic status, acid–base balance and ice‐cover duration (i.e., altitudinal gradient). Lake size was significant for the highest number of assemblage types; however, the most significant factor differed among taxonomic groups: acid–base balance for diatoms, lake size for rotifers, ice‐cover duration for chydorids and planktonic crustaceans and tropho‐dynamic status for chironomids. No single environmental typology accounted for the assemblage structure of all taxonomic groups. 4. However, defining ecological thresholds as values within environmental gradients at which the rate of change in assemblages is accelerated relative to points distant from that threshold, we were able to find specific threshold values for each of the four main general environmental factors identified, which were relevant across several taxonomic groups: 3 ha for lake area; 0.6 mg L−1 for dissolved organic carbon; 190 days for ice‐cover duration and 200 μeq L−1 for acid neutralising capacity. Above and below these values ecosystem organisation change substantially. They have direct applications in establishing lake typologies for environmental quality and biodiversity conservation programmes, and in improving predictions about global change impacts.

1. We carried out a coordinated survey of mountain lakes covering the main ranges across Europe (including Greenland), sampling 379 lakes above the local tree line in 2000. The objectives were to identify the main sources of chemical variability in mountain lakes, define a chemical classification of lakes, and develop tools to extrapolate our results to regional lake populations through an empirical regionalisation or upscaling of chemical properties. 2. We investigated the main causes of chemical variability using factor analysis (FA) and empirical relationships between chemistry and several environmental variables. Weathering, sea salt inputs, atmospheric deposition of N and S, and biological activity in soils of the catchment were identified as the major drivers of lake chemistry. 3. We tested discriminant analysis (DA) to predict the lake chemistry. It was possible to use the lithology of the catchments to predict the range of Ca 2+ and SO 4 2) into which a lake of unknown chemistry will decrease. Lakes with lower SO 4 2) concentrations have little geologically derived S, and better reflect the variations in atmospheric S loading. The influence of marine aerosols on lakewater chemistry could also be predicted from the minimum distance to the sea and altitude of the lakes. 4. The most remarkable result of FA was to reveal a factor correlated to DOC (positively) and NO 3 ) (negatively). This inverse relationship might be the result either of independent processes active in the catchment soils and acting in an opposite sense, or a direct interaction, e.g. limitation of denitrification by DOC availability. Such a relationship has been reported in the recent literature in many sites and at all scales, appearing to be a global pattern that could reflect the link between the C and N cycles. 5. The concentration of NO 3 ) is determined by both atmospheric N deposition and the processing capacity of the catchments (i.e. N uptake by plants and soil microbes). The fraction of the variability in NO 3 ) because of atmospheric deposition is captured by an independent factor in the FA. This is the only factor showing a clear pattern when mapped over Europe, indicating lower N deposition in the northernmost areas. 6. A classification has been derived which takes into account all the major chemical features of the mountain lakes in Europe. FA provided the criteria to establish the most important factors influencing lake water chemistry, define classes within them, and classify the surveyed lakes into each class. DA can be used as a tool to scale up the classification to unsurveyed lakes, regarding sensitivity to acidification, marine influence and sources of S.

1. We surveyed the distribution of several trace elements in contemporary and preindustrial sediment s in 275 lakes in alpine and arctic lake districts across Europe including the Pyrenees, Alps, the Rila Mountains, Retezat, Julian Alps, Tatras, Scottish mountains, Central Norway and Greenland. 2. Sediment cores were collected at the deepest part of each lake and analysed at two depths (surface sediment and at 15-17 cm depth) for Ti, Pb, Cd, Zn, Cu, As, Hg and Se. 3. The concentrations of trace elements found in the lakes included in the survey are comparable to those reported in aquatic sediments receiving higher contamination loads. With the exception of Greenland, a large percentage of lakes showed enrichment factors for most elements well above 1.5, indicating atmospheric contamination. The influence of contamination has increased the co-distribution of trace elements in sediments, with the exception of As. 4. Pb is the element that shows the highest contamination level at the European scale, followed by Hg and As. Zn, Cd, Cu and Se contamination is detectable to a lower degree. 5. The Tatra Mountains and Scotland seem to be most affected. Natural mechanisms leading to the formation of highly organic, metal-binding sediments may be the cause of the high levels in Scotland, whereas those in the Tatras appear to be due to elevated deposition. 6. The Retezat and Central Norway appear to be least polluted. 7. In the Alps, enrichments in Pb, Hg and Zn are higher in southern than in central areas suggesting a flux of these pollutants from the south. In the Pyrenees, the high natural levels of As are remarkable. Metal enrichments in the Rila Mountains are comparable to those in the Tatras, but concentrations are much lower. 8. In general terms, the increase in trace elements in modern with respect to pre-industrial sediments reflects the history of a long range contamination affecting the remotest locations in Europe.

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