Individual-based models are an exciting and widely used new tool for ecology. These computational models allow scientists to explore the mechanisms through which population and ecosystem ecology arises from how individuals interact with each other and their environment. This book provides the first in-depth treatment of individual-based modeling and its use to develop theoretical understanding of how ecological systems work, an approach the authors call "individual-based ecology.? Grimm and Railsback start with a general primer on modeling: how to design models that are as simple as possible while still allowing specific problems to be solved, and how to move efficiently through a cycle of pattern-oriented model design, implementation, and analysis. Next, they address the problems of theory and conceptual framework for individual-based ecology: What is "theory"? That is, how do we develop reusable models of how system dynamics arise from characteristics of individuals? What conceptual framework do we use when the classical differential equation framework no longer applies? An extensive review illustrates the ecological problems that have been addressed with individual-based models. The authors then identify how the mechanics of building and using individual-based models differ from those of traditional science, and provide guidance on formulating, programming, and analyzing models. This book will be helpful to ecologists interested in modeling, and to other scientists interested in agent-based modeling.

Mathematical modelling is an essential tool in present-day ecological research. Yet for many ecologists it is still problematic to apply modelling in their research. In our experience, the major problem is at the conceptual level: proper understanding of what a model is, how ecological relations can be translated consistently into mathematical equations, how models are solved, steady states calculated and interpreted. Many textbooks jump over these conceptual hurdles to dive into detailed formulations or the mathematics of solution. This book attempts to fill that gap. It introduces essential concepts for mathematical modelling, explains the mathematics behind the methods, and helps readers to implement models and obtain hands-on experience. Throughout the book, emphasis is laid on how to translate ecological questions into interpretable models in a practical way. The book aims to be an introductory textbook at the undergraduate-graduate level, but will also be useful to seduce experienced ecologists into the world of modelling. The range of ecological models treated is wide, from Lotka-Volterra type of principle-seeking models to environmental or ecosystem models, and including matrix models, lattice models and sequential decision models. All chapters contain a concise introduction into the theory, worked-out examples and exercises. All examples are implemented in the open-source package R, thus taking away problems of software availability for use of the book. All code used in the book is available on a dedicated website.

Cover -- Contents -- Preface -- Acknowledgements -- Chapter 1. Introduction -- 1.1 Physical and Mathematical Models -- 1.2 Models as a Management Tool -- 1.3 Models as a Scientific Tool -- 1.4 Models and Holism -- 1.5 The Ecosystem as an Object for Research -- 1.6 Outline of the Book -- 1.7 The Development of Ecological and Environmental Models -- 1.8 State of the Art in the Application of Models -- Chapter 2. Concepts of Modelling -- 2.1 Introduction -- 2.2 Modelling Elements -- 2.3 The Modelling Procedure -- 2.4 Types of Model -- 2.5 Selection of Model Type -- 2.6 Selection of Model Complexity and Structure -- 2.7 Verification -- 2.8 Sensitivity Analysis -- 2.9 Parameter Estimation -- 2.10 Validation -- 2.11 Ecological Modelling and Quantum Theory -- 2.12 Modelling Constraints -- Problems -- Chapter 3. Ecological Processes -- 3A.1 Space and Time Resolution -- 3A.2 Mass Transport -- 3A.3 Mass Balance -- 3A.4 Energetic Factors -- 3A.5 Settling and Resuspension -- 3B.1 Chemical Reaction ...

Computer simulations are a powerful tool for understanding ecological and evolutionary systems. Simulating Ecological and Evolutionary Systems in C models a diverse range of biological processes and systems, including competition, foraging, predation, mating systems, and life-history optimization, by simulating large collections of interacting individuals. Using the programming language C, the book starts with elementary programs modeling stochastic birth-death processes, with programming complexity increasing as the chapters progress. Wilson covers all the important features of C: arrays, files, pointers, and structures, within biologically motivated simulations. Although computer simulations of extremely complicated biological processes are released from rigid mathematical constraints, he places each of the simulations in the context of a mathematical formulation examined either analytically or numerically.

This book constitutes the refereed proceedings of the 9th International Conference on Simulation of Adaptive Behavior, SAB 2006. The 35 revised full papers and 35 revised poster papers presented are organized in topical sections on the animat approach to adaptive behaviour, perception and motor control, action selection and behavioral sequences, navigation and internal world models, learning and adaptation, evolution, collective and social behaviours, applied adaptive behavior and more.

This is a thoroughly revised and updated edition of an authoritative introduction to ecological modelling. Sven Erik Jørgensen, Editor-in-Chief of the journal Ecological Modelling, and Giuseppe Bendoricchio, Professor of Environmental Modelling at the University of Padova, Italy, offer compelling insights into the subject. This volume explains the concepts and processes involved in ecological modelling, presents the latest developments in the field and provides readers with the tools to construct their own models. The Third Edition features: . A detailed discussion and step-by-step outline of the modelling procedure. . An account of different model types including overview tables, examples and illustrations. . A comprehensive presentation of the submodels and unit processes used in modelling. . In-depth descriptions of the latest modelling techniques. . Structured exercises at the end of each chapter. . Three mathematical appendices and a subject index. This practical and proven book very effectively combines the theory, methodology and applications of ecological modelling. The new edition is an essential, up-to-date guide to a rapidly growing field.

Systems Analysis and Simulation in Ecology, Volume IV continues the organization begun in Volume III to document a meeting, Modeling and Analysis of Ecosystems, held at the University of Georgia on 1-3 March 1973. Several chapters are considerably expanded over their original concept, and several others are included which were not part of the symposium. The book is organized into five parts. Part I contains chapters on estuarine-marine ecosystems. Part II presents models of several terrestrial ecosystems. Part III has chapters devoted to human aspects of ecology. Part IV considers special problems of ecosystem modeling, namely linear versus nonlinear models, aggregation, and validation. Part V, the most extensive section, describes theory in ecosystem analysis. The book's chapters demonstrate the current scope of systems ecology—its past and present emphasis on parts and mechanisms in simulation modeling, and its movement toward systems analysis and new, more formal consideration of wholes in theory. They make clear that although the systems approach is young in ecology, it has substantially enriched the science both methodologically and conceptually.