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Contents:

1 - Models in Ecosystem Science; Part 1 - The status and role of modeling in ecosystem science; Part 2 - Evaluating ecosystem models; Part 3 - The role of models in environmental policy and management; Part 4 - The future of modeling in ecosystem science; Part 5 - Concluding comments.

Review:

This volume grew out of a conference held in 2001 on the issues of quantitative modelling. The aim was to discuss the uses to which models could be put and their limitations as a way of critically highlighting their potential. The contributors to this book have produced 26 chapters divided into 5 parts with a first chapter acting as an overview of the enterprise. Part 1 introduces us to the 3 main areas of modelling: synthesis, experimentation and prediction. Although we can agree that these are the basics of models that doesn't mean to say that the issue is resolved. As the 7 chapters illustrate here, there are a range of aspects which must be addressed of which the most important are: the role of uncertainty, acceptance of models, the debate between simple and complex models and the way in which models must be designed to fit specific situations. Clearly there are far more issues that are raised in this first section but one is struck by the rigour and breadth that these discussions show. A similar perspective carries over to part 2 which deals with the evaluation of models. Again, there is a broad discussion which highlights a series of key ideas: the role of uncertainty, model limitations, publication of parameters to aid discussion, the use of the correct equations and impact of scale. Part three turns away from the scientific discussion and moves into the public use of models. Here, the key point is not some aspect of design semantics but getting policy makers and others to understand exactly what they have been given. We are shown that models can package information usefully and that they are suited to a range of key problems such as risk analysis and invading species but less good in complex settings or where the parameters are less well known (e.g. climate change). Part 4 changes tack again to look at the future of modelling. Here, the focus is not on the model as one might expect but on the users. We are told that undergraduates need more exposure to models (as do some ecologists!) and that models need to be more ubiquitous. This brings us to the final part which sums up much of the preceeding debate. Models need to be faster, more widely used and get a better communications profile (as well as all the theoretical ideas set out in parts 1 and 2!). In short, models have a great future but this is not assured.

This is a very interesting text in the right context. It's no beginner's guide to modelling but it is far more wide-ranging in its discussion than many modelling texts. It's particularly fine to see such an interesting, deep analysis not just of models but of the human action surrounding them. As such, this text would be extremely valuable to anyone studying models or public policy. It also provides a wealth of detail for those wanting to help students learn more about the use and misuse of these aids to understanding.