Spatial simulation: exploring pattern and process

A ground-up approach to explaining dynamic spatial modelling for an interdisciplinary audience. Across broad areas of the environmental and social sciences, simulation models are an important way to study systems inaccessible to scientific experimental and observational methods, and also an essential complement to those more conventional approaches. The contemporary research literature is teeming with abstract simulation models whose presentation is mathematically demanding and requires a high level of knowledge of quantitative and computational methods and approaches. Furth.

Cover; Title Page; Copyright; Contents; Foreword; Preface; Acknowledgements; Introduction; About the Companion Website; Chapter 1 Spatial Simulation Models: What? Why? How?; 1.1 What are simulation models?; 1.1.1 Conceptual models; 1.1.2 Physical models; 1.1.3 Mathematical models; 1.1.4 Empirical models; 1.1.5 Simulation models; 1.2 How do we use simulation models?; 1.2.1 Using models for prediction; 1.2.2 Models as guides to data collection; 1.2.3 Models as `tools to think with'; 1.3 Why do we use simulation models?; 1.3.1 When experimental science is difficult (or impossible)

1.3.2 Complexity and nonlinear dynamics1.4 Why dynamic and spatial models?; 1.4.1 The strengths and weaknesses of highly general models; 1.4.2 From abstract to more realistic models: controlling the cost; Chapter 2 Pattern, Process and Scale; 2.1 Thinking about spatiotemporal patterns and processes; 2.1.1 What is a pattern?; 2.1.2 What is a process?; 2.1.3 Scale; 2.2 Using models to explore spatial patterns and processes; 2.2.1 Reciprocal links between pattern and process: a spatial model of forest structure; 2.2.2 Characterising patterns: first- and second-order structure

2.2.3 Using null models to evalu…