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Individual-based Modeling and Ecology.
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...
| Clasificación: | Libro Electrónico |
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| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Princeton University Press,
2013.
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| Temas: | |
| Acceso en línea: | Texto completo |
MARC
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| 100 | 1 | |a Grimm, Volker. | |
| 245 | 1 | 0 | |a Individual-based Modeling and Ecology. |
| 260 | |b Princeton University Press, |c 2013. | ||
| 300 | |a 1 online resource | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
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| 505 | 0 | |a Cover; Title; Copyright; Contents; Preface; Acknowledgments; PART 1. MODELING; Chapter 1. Introduction; 1.1 Why Individual-based Modeling and Ecology?; 1.2 Linking Individual Traits and System Complexity: Three Examples; 1.3 Individual-based Ecology; 1.4 Early IBMs and Their Research Programs; 1.5 What Makes a Model an IBM?; 1.6 Status and Challenges of the Individual-based Approach; 1.7 Conclusions and Outlook; Chapter 2. A Primer to Modeling; 2.1 Introduction; 2.2 Heuristics for Modeling; 2.3 The Modeling Cycle; 2.4 Summary and Discussion; Chapter 3. Pattern-oriented Modeling. | |
| 505 | 8 | |a 3.1 Introduction3.2 Why Patterns, and What Are Patterns?; 3.3 The Tasks of Pattern-oriented Modeling; 3.4 Discussion; PART 2. INDIVIDUAL-BASED ECOLOGY; Chapter 4. Theory in Individual-based Ecology; 4.1 Introduction; 4.2 Basis for Theory in IBE; 4.3 Goals of IBE Theory; 4.4 Theory Structure; 4.5 Theory Development Cycle; 4.6 Example: Development of Habitat Selection Theory for Trout; 4.7 Summary and Discussion; Chapter 5. A Conceptual Framework for Designing Individual-based Models; 5.1 Introduction; 5.2 Emergence; 5.3 Adaptive Traits and Behavior; 5.4 Fitness; 5.5 Prediction; 5.6 Interaction. | |
| 505 | 8 | |a 5.7 Sensing5.8 Stochasticity; 5.9 Collectives; 5.10 Scheduling; 5.11 Observation; 5.12 Summary and Conclusions; 5.13 Conceptual Design Checklist; Chapter 6. Examples; 6.1 Introduction; 6.2 Group and Social Behavior; 6.3 Population Dynamics of Social Animals; 6.4 Movement: Dispersal and Habitat Selection; 6.5 Regulation of Hypothetical Populations; 6.6 Comparison with Classical Models; 6.7 Dynamics of Plant Populations and Communities; 6.8 Structure of Communities and Ecosystems; 6.9 Artificially Evolved Traits; 6.10 Summary and Conclusions; PART 3. THE ENGINE ROOM. | |
| 505 | 8 | |a Chapter 7. Formulating Individual-based Models7.1 Introduction; 7.2 Contents of an IBM Formulation; 7.3 Formulating an IBM's Spatial Elements; 7.4 Formulating Logical and Probabilistic Rules; 7.5 Formulating Adaptive Traits; 7.6 Controlling Uncertainty; 7.7 Using Object-oriented Design and Description; 7.8 Using Mechanistic and Discrete Mathematics; 7.9 Designing Superindividuals; 7.10 Summary and Conclusions; Chapter 8. Software for Individual-based Models; 8.1 Introduction; 8.2 The Importance of Software Design for IBMs; 8.3 Software Terminology and Concepts; 8.4 Software Platforms. | |
| 505 | 8 | |a 8.5 Software Testing8.6 Moving Software Development Forward; 8.7 Important Implementation Techniques; 8.8 Some Favorite Software Myths; 8.9 Summary and Conclusions; Chapter 9. Analyzing Individual-based Models; 9.1 Introduction; 9.2 Steps in Analyzing an IBM; 9.3 General Strategies for Analyzing IBMs; 9.4 Techniques for Analyzing IBMs; 9.5 Statistical Analysis; 9.6 Sensitivity and Uncertainty Analysis; 9.7 Robustness Analysis; 9.8 Parameterization; 9.9 Independent Predictions; 9.10 Summary and Conclusions; Chapter 10. Communicating Individual-based Models and Research; 10.1 Introduction. | |
| 520 | |a 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 poss. | ||
| 588 | 0 | |a Print version record. | |
| 590 | |a ProQuest Ebook Central |b Ebook Central Academic Complete | ||
| 650 | 0 | |a Population biology |x Mathematical models. | |
| 650 | 0 | |a Biotic communities |x Mathematical models. | |
| 650 | 6 | |a Biologie des populations |x Modèles mathématiques. | |
| 650 | 7 | |a Biotic communities |x Mathematical models |2 fast | |
| 650 | 7 | |a Population biology |x Mathematical models |2 fast | |
| 776 | 0 | 8 | |i Print version: |z 9781306142748 |
| 856 | 4 | 0 | |u https://ebookcentral.uam.elogim.com/lib/uam-ebooks/detail.action?docID=1520764 |z Texto completo |
| 938 | |a EBL - Ebook Library |b EBLB |n EBL1520764 | ||
| 938 | |a ProQuest MyiLibrary Digital eBook Collection |b IDEB |n cis26792762 | ||
| 994 | |a 92 |b IZTAP | ||