Individual-based Modeling and Ecology:

Individual-based Modeling and Ecology:

Volker Grimm
Steven F. Railsback
Copyright Date: 2005
Edition: STU - Student edition
Pages: 448
https://www.jstor.org/stable/j.ctt5hhnk8
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  • Book Info
    Individual-based Modeling and Ecology:
    Book Description:

    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.

    eISBN: 978-1-4008-5062-4
    Subjects: Ecology & Evolutionary Biology, Technology

Table of Contents

  1. Front Matter
    (pp. i-vi)
  2. Table of Contents
    (pp. vii-x)
  3. Preface
    (pp. xi-xiv)
  4. Acknowledgments
    (pp. xv-xvi)
  5. PART 1. MODELING
    • Chapter One Introduction
      (pp. 3-21)

      Modeling attempts to capture the essence of a system well enough to address specific questions about the system. If the systems we deal with in ecology are populations, communities, and ecosystems, then why should ecological models be based on individuals? One obvious reason is that individuals are the building blocks of ecological systems. The properties and behavior of individuals determine the properties of the systems they compose. But this reason is not sufficient by itself. In physics, the properties of atoms and the way they interact with each other determine the properties of matter, yet most physics questions can be...

    • Chapter Two A Primer to Modeling
      (pp. 22-37)

      Individual-based modeling is, above all, modeling. If we want to make individual-based modeling effective and coherent, we must understand what modeling really is and how it works. Therefore, in this chapter we introduce general guidelines for developing models, referring readers to other authors (especially Starfield, Smith, and Bleloch 1990; Starfield and Bleloch 1986; and Haefner 1996) for more detailed introduction to the principles of modeling. These guidelines also set the stage for the remainder of the book: subsequent chapters address the modeling tasks introduced here.

      Intuitively, we know a model is some sort of simplified representation of a real system....

    • Chapter Three Pattern-oriented Modeling
      (pp. 38-50)

      Models of complex systems should be neither too simple nor too complex if they are to be useful. Complexity in a model causes many difficulties, yet models that are too simple cannot explain much. To find the right level of complexity, we rely on the principle of parsimony, or “Occam’s razor”: if we have two models that both explain a phenomenon, we should stick to the simpler one. However, we must be careful to use Occam’s razor appropriately: the simpler model should be chosen only if it really explains the phenomenon! With IBMs the phenomenon we want to explain is...

  6. PART 2. INDIVIDUAL-BASED ECOLOGY
    • Chapter Four Theory in Individual-based Ecology
      (pp. 53-70)

      In chapter 1 we identified the complexity of IBMs as a major challenge to their efficient and coherent use. Therefore, in chapters 2 and 3 we presented general modeling guidelines and pattern-oriented modeling as ways to help modelers end up in the “Medawar zone” of complexity that provides a high payoff (figure 3.1). However, these techniques are not sufficient to providecoherenceto the use of IBMs. By coherence we mean that different IBMs are consistent with each other in some important, general, ways. Without coherence, it is difficult to compare the structure of different IBMs and to integrate the...

    • Chapter Five A Conceptual Framework for Designing Individual-based Models
      (pp. 71-121)

      The modeling guidelines of chapters 2 and 3 and the process of theory development described in chapter 4 address the strategic level of individual-based modeling: they provide efficient strategies for designing IBMs to address specific problems and for developing theory of how individual traits determine system dynamics. Now, however, we turn to the process of actually designing an IBM: how do we represent those processes that we determined, at the strategic level, must be in the IBM?

      At this point, modelers in most fields turn to an established conceptual framework: well-known and widely used classical concepts that provide away to...

    • Chapter Six Examples
      (pp. 122-244)

      In the preceding chapters we deal with concepts and strategies for developing IBMs and conducting IBE, but now it is time to look at some IBMs in action. So many IBMs have been developed in recent years that we were easily able to assemble a mosaic of case studies that illustrate our ideas of how IBE is done and the kinds of things to be learned by doing IBE. By presenting examples of IBMs that have already been developed and used, this chapter also shows us what the future should look like (Table 6.1). The example IBMs address a broad...

  7. PART 3. THE ENGINE ROOM
    • Chapter Seven Formulating Individual-based Models
      (pp. 247-269)

      This chapter begins our descent into the “engine room” of individual-based modeling. According to the statement by biomathematician E. C. Zeeman, part 2 of this book focused on the creative phases of individual-based ecology: approaches for reproducing and explaining ecosystem complexity using relatively simple concepts and theories. Now, in part 3 we address the technical skills needed to master the complexity we create when we implement an IBM, execute it, and start to conduct science with it. A major theme of part 3 is that many of the technical skills needed for IBE are different from those typically used in...

    • Chapter Eight Software for Individual-based Models
      (pp. 270-311)

      This is by far the most difficult chapter in the book, certainly for the authors and probably also for the readers. Developing the software for an IBM is a major step, yet this topic easily takes on a negative tone. For an unfortunate number of early IBMs, the modeling cycle was not propelled forward by the software development phase; instead, the cycle ground to a halt. Many IBMs were implemented in home-made software that contributed to common, yet avoidable, problems: (1) far too much of the researcher’s time and budget was spent on programming instead of on science; (2) much...

    • Chapter Nine Analyzing Individual-based Models
      (pp. 312-348)

      Analyzing a computer model means studying the model, once it executes, to understand and improve its performance and then to solve the problems the model was designed to explain. One consequence of IBMs being less simple than classical models is that IBMs are not as easy to understand and learn from. In fact, some ecologists believe simulation models and IBMs are so hard to understand that they are not useful: if a model is just as complex as nature itself, why not just study nature instead? Avoiding just this problem was our primary goal in part 1: readers of chapters...

    • Chapter Ten Communicating Individual-based Models and Research
      (pp. 349-362)

      As we progress through the cycle of building and analyzing an IBM, we finally feel like we have learned important things that need to be communicated to the “clients” of our research: the scientific community, our sponsors, the agencies that manage the ecosystems we study. Along the way we discover many differences between IBE and traditional ecology—we often address different problems, employ a different kind of theory and a different conceptual framework, and use many kinds of information in our IBMs instead of relying only on classical models or field studies. Now it is time to look at one...

  8. PART 4. CONCLUSIONS AND OUTLOOK
    • Chapter Eleven Using Analytical Models in Individual-based Ecology
      (pp. 365-379)

      This book is about individual-based modeling and how it can be used, within the framework of individual-based ecology, to address ecological problems. Of course, other modeling approaches are widely used in ecology. In particular, analytical models that use mathematical formulations are the backbone of classical ecology. Individual-based and analytical approaches are both important tools for ecology, each designed for specific purposes and each having specific strengths and weaknesses. Too often, modelers see alternative approaches as competing or mutually exclusive and get caught up in unproductive debates over which approach is right or wrong. Instead, in this chapter we explore the...

    • Chapter Twelve Conclusions and Outlook for Individual-based Ecology
      (pp. 380-390)

      In the preface and chapter 1 we explained why we wrote this book: to establish an effective and coherent framework for using individual-based modeling, a new approach to ecology that we refer to as individual-based ecology (IBE). The strategic elements of IBE include fundamentals of good modeling (chapter 2), “pattern-oriented” modeling (chapter 3), an approach to theory (chapter 4), and a conceptual framework for modeling systems from an individual-based perspective (chapter 5). In chapter 6 we illustrated, with more than thirty IBMs, how we can conduct IBE and what we have already learned from the approach. Then, in chapters 7...

  9. Glossary
    (pp. 391-394)
  10. References
    (pp. 395-420)
  11. Index
    (pp. 421-428)