"Aquatic Habitat Simulation Tools: Univariate Preference Functions versus Multivariate Fuzzy-Logic "Man-made influences on morphological and hydrological processes in the last decades have lead to substantial changes in river characteristics. The hydrologly, morphological heterogeneity, water quality, substrate characteristics and in some cases the entire river continuum were completely modified leading to the impacts on river ecology which we have today. Thus, in river management models are reqiored which are able to quantify the species-environment relationships within aquatic habitats. Aquatic habitat simulation models (AHSMs) allow for such quantification because they predict species distributions based on data which describes the abiotic environment. This article presents a comparison between a univariate approach based on preference functions and a knowledge-based multivariate fuzzy-logical approach in the River Aare, Switzerland. In particular, the different methods used to link abiotic environmental parameters to biological responses are considered. Given the results, the approach based on preference functions lacks a proper weighting and combination of the separate habitat suitabilities. As two preference functions were necessary to describe the study site, the transferability of habitat requirements for preference functions is very limited due to the crisp boundaries for the definition of habitat requirements. As ecological transitions are more gradual, the fuzzy-logical approach may serve to be a more appropriate modeling technique to deal with these ecological gradients by using imprecise or qualitative information numerically in form of overlapping fuzzy-sets. Given to these advantages the multivariate fuzzy-logical approach is found to be the more robust approach when compared to univariate preference functions.
Keywords: Physical Habitat Modelling, Fuzzy-Logic, Preference Functions, Fish, Abiotic and Biotic