Ecological informatics : scope, techniques, and applications

Ecological Informatics promotes interdisciplinary research between ecology and computer science on elucidation of principles of information processing in ecosystems, ecological sustainability by informed decision making, and bio-inspired computation. The 2nd edition of the book consolidates the scope, concepts, and techniques of this newly emerging discipline by a new preface and additional chapters on cellular automata, qualitative reasoning, hybrid evolutionary algorithms and artificial neural networks. It illustrates numerous applications of Ecological Informatics for aquatic and terrestrial ecosystems, image recognition at micro- and macro-scale as well as computer hardware design. Case studies focus on applications of artificial neural networks, evolutionary computation, cellular automata, adaptive agents, fuzzy logic as well as qualitative reasoning. The 2nd edition of the book includes an index and a CD with novel evolutionary algorithms for the discovery of multiple nonlinear functions and rule sets as well as parameter optimisation in complex ecological data. Ecological Informatics is defined as the design and application of computational techniques for ecological analysis, synthesis, forecasting and management. The book provides an introduction to the scope, concepts and techniques of this newly emerging discipline. It illustrates numerous applications of Ecological Informatics for stream systems, river systems, freshwater lakes and marine systems as well as image recognition at micro and macro scale. Case studies focus on applications of artificial neural networks, genetic algorithms, fuzzy logic and adaptive agents to current ecological management issues such as toxic algal blooms, eutrophication, habitat degradation, conservation of biodiversity and sustainable fishery The Fuzzy Set Theory developed by L. Zadeh (Zadeh 1965) as a possible way to handle uncertainty is particularly useful for the representation of vague expert knowledge and processing uncertain or imprecise information.