Modelling Ecological Processes with Fuzzy Logic Approaches

  • Agnese MarchiniEmail author


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.


Membership Function Fuzzy Logic Fuzzy System Fuzzy Rule Fuzzy Model 
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Further Readings

  1. Adriaenssens V, De Baets B, Goethals PLM, De Pauw N (2004) Fuzzy rule-based models for decision support in ecosystem management. Sci Total Env 319:1–12CrossRefGoogle Scholar
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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  1. 1.DET – Dipartimento di Ecologia del TerritorioUniversity of PaviaPaviaItaly

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