A Practical Guide To Ecological Modelling

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.

Ecological Modeling:A Commonsense Approach to Theory and Practice explores how simulation modeling and its new ecological applications can offer solutions to complex natural resource management problems. This is a practical guide for students, teachers, and professional ecologists. Examines four phases of the modeling process: conceptual model formulation, quantitative model specification, model evaluation, and model use Provides useful building blocks for constructing systems simulation models Includes a format for reporting the development and use of simulation models Offers an integrated systems perspective for students, faculty, and professionals Features helpful insights from the author, gained over 30 years of university teaching "I can strongly recommend the book as textbook for all courses in population dynamic modeling particularly when the course is planned for the second or third year of a bachelor study in ecology, environmental science or ecological engineering. It uncovers very clearly for the readers the scientific idea and thinking behind modeling and all the necessary steps in the development of models." Ecological Modeling Journal, 2009

At present, most books on ecological modelling rely on very complex mathematics, resulting in students and researchers shying away from investigating the potential uses of ecological models and their methods of construction. This new book aims to open up this exciting area to a much wider audience. Assuming only basic mathematical knowledge, the text uses case studies to show how a relatively small set of techniques of model construction can be used in a wide range of important applications. Researchers will find it an invaluable guide to using ecological models in their work. Uses case studies to clearly demonstrate the applications of ecological models. Avoids complex mathematics. A practical how-to guide for ecological researchers. Sample ecological models available via this web site.

Introduction and background; Exploratory data analysis and graphics; Deterministic functions for ecological modeling; Probability and stochastic distributions for ecological modeling; Stochatsic simulation and power analysis; Likelihood and all that; Optimization and all that; Likelihood examples; Standar statistics revisited; Modeling variance; Dynamic models.

The book gives a comprehensive overview of all available types of ecological models. It is the first book of its kind that gives an overview of different model types and will be of interest to all those involved in ecological and environmental modelling and ecological informatics.

Fundamentals of Ecological Modelling: Applications in Environmental Management and Research, Fourth Edition, provides a comprehensive discussion of the fundamental principles of ecological modeling. The first two editions of this book (published in 1986 and 1994) focused on the roots of the discipline the four main model types that dominated the field 30-40 years ago: (1) dynamic biogeochemical models; (2) population dynamic models; (3) ecotoxicological models; and (4) steady-state biogeochemical and energy models. The third edition focused on the mathematical formulations of ecological processes that are included in ecological models. This fourth edition uses the four model types previously listed as the foundation and expands the latest model developments in spatial models, structural dynamic models, and individual-based models. As these seven types of models are very different and require different considerations in the model development phase, a separate chapter is devoted to the development of each of the model types. Throughout the text, the examples given from the literature emphasize the application of models for environmental management and research. Presents the most commonly used model types with a step-by-step outline of the modeling procedure used for each Shows readers through an illustrated example of how to use each model in research and management settings New edition is revised to include only essential theory with a focus on applications Includes case studies, illustrations, and exercises (case study of an ecological problem with full illustration on how to solve the problem)

Thirty years ago, biologists could get by with a rudimentary grasp of mathematics and modeling. Not so today. In seeking to answer fundamental questions about how biological systems function and change over time, the modern biologist is as likely to rely on sophisticated mathematical and computer-based models as traditional fieldwork. In this book, Sarah Otto and Troy Day provide biology students with the tools necessary to both interpret models and to build their own. The book starts at an elementary level of mathematical modeling, assuming that the reader has had high school mathematics and first-year calculus. Otto and Day then gradually build in depth and complexity, from classic models in ecology and evolution to more intricate class-structured and probabilistic models. The authors provide primers with instructive exercises to introduce readers to the more advanced subjects of linear algebra and probability theory. Through examples, they describe how models have been used to understand such topics as the spread of HIV, chaos, the age structure of a country, speciation, and extinction. Ecologists and evolutionary biologists today need enough mathematical training to be able to assess the power and limits of biological models and to develop theories and models themselves. This innovative book will be an indispensable guide to the world of mathematical models for the next generation of biologists. A how-to guide for developing new mathematical models in biology Provides step-by-step recipes for constructing and analyzing models Interesting biological applications Explores classical models in ecology and evolution Questions at the end of every chapter Primers cover important mathematical topics Exercises with answers Appendixes summarize useful rules Labs and advanced material available

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 ...