Modelling Ecological Processes with Fuzzy Logic Approaches
The development of an ecological model may involve problems of uncertainty. Ecologists have to deal with imprecise data, ecosystem variability, complex interactions, qualitative aspects, and expert knowledge expressed in linguistic terms. In all these cases, fuzzy logic could provide a suitable solution. Fuzzy logic allows to: use uncertain information such as individual knowledge and experience; to combine quantitative and qualitative data; to avoid artificial precision and to produce results that are found more often in the real world. Developed in the late sixties as a method to create control systems when using imprecise data, fuzzy logic has been used for a very large number of engineering applications, and more recently to develop models of air, water and soil ecosystems.The following sections of this chapter introduce the basic structure of a fuzzy model, describing the variety of options that exist at each stage. An example of fuzzy model is also outlined: the knowledge-driven development of an index of water quality having five qualitative output classes. Finally, possible future developments of fuzzy modelling in ecology are suggested.