Improved prediction of vegetation composition in NW European softwater lakes by combining location, water and sediment chemistry

Research paper by Cristina Pulido, Kaj Sand-Jensen, Esther C. H. E. T. Lucassen, Jan G. M. Roelofs, Klaus P. Brodersen, Ole Pedersen

Indexed on: 19 Aug '11Published on: 19 Aug '11Published in: Aquatic Sciences


Isoetids, as indicators of near-pristine softwater lakes, have a high priority in national and international (European Water Directive Framework) assessments of ecological lake quality. Our main goal was to identify the most important environmental factors that influence the composition of plant communities and specifically determine the presence and abundance of the isoetid Lobelia dortmanna in NW European softwater lakes. Geographical position and composition of surface water, porewater, sediment and plant communities were examined in 39 lakes in four regions (The Netherlands, Denmark, West Norway and East Norway) distributed over a 1,200-km long distance. We confirmed that lake location was accompanied by significant changes in environmental variables between NW European lakes. Lake location was the single most important determinant of vegetation composition and it had significant individual contributions independent of the coupling to environmental variables. This influence of location was supported by a significant decline of community similarity with geographical distance between pairs of lakes at regional, inter-regional and international scales. Combining the geographical position with environmental variables for surface water, porewater and sediment significantly improved prediction of vegetation composition. Specifically, the combination of latitude, surface water alkalinity, porewater phosphate and redox potential offered the highest correlation (BIO ENV correlation 0.66) to vegetation composition. This complex analysis can also account for high sediment variability in the littoral zone of individual lakes, by using site-specific physico-chemical sediment factors, and offer better predictions of vegetation composition when lake water chemistry is relatively homogeneous among lakes within regions.