Review: Models are the basic stock-in-trade of the ecologist. They have been used from the simplest ideas to some of the most pressing and complex situations such as global warming. It must be considered essential that people understand the modeling process and yet that is very clearly not the case. One of the main problems is that models are seen to be complex 'black box' operations, too complex for the ordinary person to understand. A simple input-output diagram is seen as understandable but all of a sudden, put four or five of these together and it becomes an issue! There is a need for a text that puts modeling into perspective which is where this book comes in.

We start with a very brief overview of the book and are introduced to the three scenarios that form the basis of the study: hunter-gatherers, population levels and resource management (broadly speaking). Each represents a different level of complexity in model making and yet each retains enough simplicity to make the process of modeling the focus. Chapter two describes the scenarios in more detail and suggests ways in which a 'solution' can be worked out. The aim here is to discuss the parameters of the model and gain some idea of where the results might lie. From this point, the text starts to work through a model-making procedure. The outline of this procedure was first seen in chapter two in parallel with their initial 'common sense' approach. The aim is to produce a model based on careful logical steps. Chapter three starts the process with an analysis of the conceptual model i.e. the key features, flows and constraints. Here is where the processes are laid out and connected. Limits and boundaries are drawn to show which components work. Chapter four adds the data which includes the rates of change and initial parameters. The next stage is to check the model, to see if it actually answers the questions put to it. In other words the aim here is to validate the model or, as the authors suggest, invalidate it in ways similar to hypothesis testing. A brief chapter six outlines how the model, now tested, can be applied to a range of situations. At this stage, the modeling system is complete and it remains to study some of the issues generated. Chapter 7 looks at some of the common problems faced. Chapter 8 takes the modeling process further and shows how these ideas can be applied in other areas. The final two chapters take a look at the initial problems posed and how the modeling process can be extended.

This is a very useful book. Models should be easy but the complexity of natural systems will mean that, invariably, there are issues that need to be resolved. This text provides us with a way of making and understanding models using principles that scale up from the smallest system to something global. After all, even the most complex global climate model is just a large number of simple ones put together (although many climate scientists would argue otherwise!). What this book tries to do is de-mystify the process, to show us that we can make good models that are valid. More importantly, it starts to give the reader a sense of confidence, that models can be read and understood. After all, if we are going to use them it is crucial that we actually understand them. We need some sort of model-literacy and this book starts the process.