Stream and Wetland Ecology


Photo: Bjarne Moeslund

The Section for Stream and Wetland Ecology undertakes research on the ecology of the streams and wetlands. Most of our research is holistically focused on elucidating the impact of local and regional processes on biological communities at both individual organism and ecosystem level. We have a particular focus on elucidating the importance of climate-related changes in temperature and flow conditions and the interaction between these and a number of specific influences (multiple stressors). The specific influences include, among other things, hydromorphological changes in the streams (digging, deepening), weed cutting, land use changes, nutrients, pesticides and other environmentally hazardous substances. We address both basic scientific and application-oriented issues and use both experimental studies and descriptive analysis of large datasets, from previous projects and from the Danish nation-wide aquatic monitoring programme NOVANA, to illuminate our research themes. We also research the effects of various tools, including stream restoration, on biological communities and the dynamics of these.

An important element of the section's work is research-based advisory services to authorities and society, and our research therefore contributes directly to ensuring that management in and along the streams rests on a knowledge-based basis. Significant synergy exists between our research and advisory services, and many of our projects contain both research and advisory issues of relevance both nationally and internationally. We are also actively involved in the education of new biologists and agroecologists at Bachelor, Master and PhD level at Aarhus University as well as at the Sino-Danish University of in Beijing. In addition, we actively participate in the training of nature managers, advisers and high school teachers.

The section uses the latest statistical methods for both research and advisory services. Both existing statistical methods are used and new methods are developed for analysis of, for instance, hydrological environmental data. The focus is on analysis of time series and quality control through the use of both univariate and multivariate analysis.