Data-Driven Modelling of Structured Populations: A Practical Guide to the Integral Projection Model
In: Lecture Notes on Mathematical Modelling in the Life Sciences Ser.
Intro -- Preface -- Contents -- 1 Introduction -- 1.1 Linking individuals, traits, and population dynamics -- 1.2 Survey of research applications -- 1.3 About this book -- 1.3.1 Mathematical prerequisites -- 1.3.2 Statistical prerequisites and data requirements -- 1.3.3 Programming prerequisites -- 1.4 Notation and nomenclature -- 2 Simple Deterministic IPM -- 2.1 The individual-level state variable -- 2.2 Key assumptions and model structure -- 2.3 From life cycle to model: specifying a simple IPM -- 2.3.1 Changes -- 2.4 Numerical implementation -- 2.5 Case study 1A: A monocarpic perennial -- 2.5.1 Summary of the demography -- 2.5.2 Individual-based model (IBM) -- 2.5.3 Demographic analysis using lm and glm -- 2.5.4 Implementing the IPM -- 2.5.5 Basic analysis: projection and asymptotic behavior -- 2.5.6 Always quantify your uncertainty! -- 2.6 Case study 2A: Ungulate -- 2.6.1 Summary of the demography -- 2.6.2 Individual-based model -- 2.6.3 Demographic analysis -- 2.6.4 Implementing the IPM -- 2.6.5 Basic analysis -- 2.7 Model diagnostics -- 2.7.1 Model structure -- 2.7.2 Demographic rate models -- 2.7.3 Implementation: choosing the size range -- 2.7.4 Implementation: the number of mesh points -- 2.8 Looking ahead -- 2.9 Appendix: Probability Densities and the Change of Variables Formula -- 2.10 Appendix: Constructing IPMs when more than one census per time year is available -- 3 Basic Analyses 1: Demographic Measures and Eventsin the Life Cycle -- 3.1 Demographic quantities -- 3.1.1 Population growth -- 3.1.2 Age-specific vital rates -- 3.1.3 Generation time -- 3.2 Life cycle properties and events -- 3.2.1 Mortality: age and size at death -- 3.2.2 Reproduction: who, when, and how much? -- 3.2.3 And next… -- 3.3 Case study 1B: Monocarp life cycle properties and events -- 3.3.1 Population growth.