Details zur Publikation

Referenztyp Bücher
Titel (primär) Individual-based modeling and ecology
Autor Grimm, V.; Railsback, S.F.;
Journal / Serie Princeton Series in Theoretical and Computational Biology
Erscheinungsjahr 2005
Department OESA;
Sprache englisch;
UFZ Bestand Leipzig, Hauptlesesaal, 00159081, 05-1168, DK: 574.3 Gri
Abstract Individual-based models are an exciting and widely used new tool for ecology. These models provide ecologists with an effective way to explore the mechanisms through which population and ecosystem ecology arises from how individuals interact with each other and their environment. This book is the first major reference on individual-based modeling and its use to develop theoretical understanding of how ecological systems work, an approach the authors call "individual-based ecology". The book first provides a general primer on modeling: how to design models that are as simple as possible while still allowing us to address the problems we need to study, and how to move efficiently through a cycle of model design, implementation, and analysis. Next, the general problems of theory and conceptual framework for individual-based ecology are addressed: What is "theory"-how do we develop general, re-usable models of how system dynamics arise from characteristics of individuals? What conceptual framework do we use when the classical framework of differential calculus no longer applies? A review of over 30 studies illustrates the wide variety of ecological problems that have already been addressed with individual-based models. The authors then identify the many ways in which the mechanics of building and using individual-based models differ from those of traditional science and provide extensive guidance on formulating, programming, and analyzing models. This book should be very helpful to any ecologist interested in modeling, and to any scientist interested in agent-based modeling.
ID 3365
dauerhafte UFZ-Verlinkung
Grimm, V., Railsback, S.F. (2005):
Individual-based modeling and ecology
Princeton Series in Theoretical and Computational Biology
Princeton University Press, Princeton, NJ, 428 pp.