Modelling Ecological Interrelations in Running Water Ecosystems with Artificial Neural Networks

Abstract

The assessment of properties and processes in running water ecosystems is a major issue in basic and applied aquatic science and has consequences for environmental management. However, knowledge of the system functions, e.g. temporal and spatial dynamics of physical, chemical, hydro-morphological and biological processes, and species-habitat interrelations are still insufficient. An integrative and prognostic ecological assessment of running waters thus is presently not available (e.g. Bayerisches Landesamt fur Wasserwirtschaft 1998; Resh et al. 1994; Statzner et al. 1994; Townsend and Hildrew 1994; Townsend 1989; Vannote et al. 1980).