This book is timely. Difficult decisions concerning the planet's future environment and ecology rely on predictions from a wide range of models from climate change to the molecules. What is a model? How reliable is it? How do I interpret its predictions? These are critical questions that decision-makers as well as model developers need to understand. The book addresses these questions in a well-structured way. It takes the newcomer through the nature of models, choosing and developing models, to their validation and application. Each chapter has self-check questions, key summaries and problems with solutions appended. There is also a valuable online resource service both for students and lecturers.
I enjoyed reading the book and following the trials and tribulations of modelling Life on Mars – an effective technique employed by the authors to get the reader to think outside their personal space. It turns out the models are being used in earnest on planet Earth! While the book is aimed at the novice, it is a valuable prompt for established modellers.
On a slightly pernickety note, the story about the evolution of the analysis of coincidence is fictional. The square root of the square of a number is simply its absolute value and for ancients like myself, when you needed a square root, there were logarithmic tables and slide rules. Gauss contributed the famous ‘Bell’ curve in the late 18th century – he was not put off by lack of a computer. A section on the non-linear behaviour of some models might have been included: predictions can be affected by the choice of either temporal or spatial time scales over which to average inputs. I nevertheless recommend the book.
