Given the importance of interdisciplinary work in sustainability, Simulation of Ecological and Environmental Models introduces the theory and practice of modeling and simulation as applied in a variety of disciplines that deal with earth systems, the environment, ecology, and human-nature interactions. Based on the author's many years of teaching g
The environmental sciences are undergoing a revolution in the use of models and data. Facing ecological data sets of unprecedented size and complexity, environmental scientists are struggling to understand and exploit powerful new statistical tools for making sense of ecological processes. In Models for Ecological Data, James Clark introduces ecologists to these modern methods in modeling and computation. Assuming only basic courses in calculus and statistics, the text introduces readers to basic maximum likelihood and then works up to more advanced topics in Bayesian modeling and computation. Clark covers both classical statistical approaches and powerful new computational tools and describes how complexity can motivate a shift from classical to Bayesian methods. Through an available lab manual, the book introduces readers to the practical work of data modeling and computation in the language R. Based on a successful course at Duke University and National Science Foundation-funded institutes on hierarchical modeling, Models for Ecological Data will enable ecologists and other environmental scientists to develop useful models that make sense of ecological data. Consistent treatment from classical to modern Bayes Underlying distribution theory to algorithm development Many examples and applications Does not assume statistical background Extensive supporting appendixes Lab manual in R is available separately
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.
This book focuses on use-inspired basic science by connecting theoretical methods and mathematical developments in ecology with practical real-world problems, either in production or conservation.
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.
Ecological Model Types brings an understanding on how to quantitatively analyze complex and dynamic ecosystems with the tools available today. Ecosystem studies widely use the notions of order, complexity, randomness, and organization, and are used interchangeably in literature, which causes much confusion. Better models synthesize our knowledge on ecosystems and their environmental problems, in contrast to statistical analysis, which only reveal the relationships between the data. This book brings together experts on ecological models to create a definitive work on how to understand our complex Earth. - Bridges the gap between statistical analysis and synthesis of data, enhancing our understanding about ecosystems and their environmental problems - Helps readers understand complex ecosystems by walking through the best modeling options to analyze and predict environmental effects - Provides a detailed review of 14 model types, covering the breadth of options available for analysis at this time
Ecological Modeling: An Introduction to the Art and Science of Modeling Ecological Systems, Volume 31, presents the skills needed to appropriately evaluate and use ecological models. Illustrated throughout with practical examples, the book discusses ecological modeling as both an art and a science, balancing the qualitative (artistic) side, with its foundations in common sense and modeling practice, against the quantitative (scientific) aspects of the modeling process. This book draws on the authors’ extensive experience in both teaching and using these techniques to provide readers with a practical, user-friendly guide that supports and encourages the appropriate, effective use of these tools. Provides readers with a commonsense understanding of the systems perspective and its foundations in general system theory Highlights the importance of a solid understanding of the qualitative aspects of the modeling process Facilitates the ability to appropriately evaluate and use ecological models Supports learning with a variety of simple examples to instill the desire and confidence to embark upon the modeling experience
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
Model development is of vital importance for understanding and management of ecological processes. Identifying the complex relationships between ecological patterns and processes is a crucial task. Ecological modelling—both qualitatively and quantitatively—plays a vital role in analysing ecological phenomena and for ecological theory. This textbook provides a unique overview of modelling approaches. Representing the state-of-the-art in modern ecology, it shows how to construct and work with various different model types. It introduces the background of each approach and its application in ecology. Differential equations, matrix approaches, individual-based models and many other relevant modelling techniques are explained and demonstrated with their use. The authors provide links to software tools and course materials. With chapters written by leading specialists, “Modelling Complex Ecological Dynamics” is an essential contribution to expand the qualification of students, teachers and scientists alike.
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)
