Measurement, scale, and prediction: caveat emptor.(Scaling and Uncertainty Analysis in Ecology.)(Book review)

Scaling and Uncertainty Analysis in Ecology. Jianguo Wu, K. Bruce Jones, Harbin Li, and Orie L. Loucks. Springer, Dordrecht, The Netherlands, 2006. 351 pp., illus. $119.00 (ISBN 9781402046629 cloth).

To understand, manage, and assess the effects of change on the Earths ecosystems requires a troika of measurement, translation, and prediction of patterns with changes in scale. This problem is familiar to ecologists: Pielou (1969) discussed issues of spatial sampling and data analysis nearly 40 years ago; O'Neill (1979) explored the transmutation of information across levels of complexity; Allen and Starr (1982) provided new perspectives from hierarchy theory; and Levin (1992) galvanized interest with his 1989 Robert H. MacArthur Award Lecture to the Ecological Society of America. The unresolved issues revolve around the complex response of ecosystems to change; the insufficiency of measurements in time and space; and the diversity of approaches now being employed by geographers, geologists, atmospheric scientists, and ecologists.

Scaling and Uncertainty Analysis in Ecology, an edited volume resulting from a workshop specifically designed to address these issues, has been ably produced by Jianguo Wu, Bruce Jones, Harbin Li, and Orie Loucks. These four editors have a broad range of backgrounds and experience in the relevant theory and practice. Their stated goals were to review and make sense of the many approaches to scale transformation and prediction; to address the effects of uncertainties on this process; and to provide a synthesis useful for management, planning, and decisionmaking. The text achieves the first two objectives with a thorough review and careful definition of terms, but the final objective--to make theory and methods useful and accessible to a broad audience--remains tantalizingly out of reach.

The 18 chapters of this book are arranged into three sections. The first section reviews concepts and defines terms. Chapters 1 and 2, by Wu and Li, are well-constructed overviews with clear expositions of issues concerning extrapolation across scale. Those unfamiliar with this subject will appreciate these chapters and the perspective they provide. The third chapter, also by Li and Wu, reviews the history and methods employed in the analysis of uncertainties of model predictions. There has been a recent resurgence of interest in uncertainty analysis, making this review timely and useful. Because complex systems often have many variables with high uncertainties, this chapter leaves the reader with the pessimistic view that reliable predictions may be beyond current capabilities. In fact, a central point of earlier work revolved around the fact that only a few variables are usually responsible for most of the uncertainties associated with predictions. The importance of this result is that it focuses future studies on measuring specific processes that will most increase our confidence in predictions. This feedback between prediction and measurement should be an organic component of all ecological studies.

The remaining chapters of this section provide a diverse set of approaches to scale-dependent analysis and prediction. The discussion of multilevel statistical models by Richard A. Berk and Jan de Leeuw provides access to these methods for the ecological community; the contrasting requirements of nonspatial, spatially implicit, and spatially explicit methods, reviewed by Debra P. C. Peters and colleagues, are fundamental to the problems of spatial prediction; and the discussion ...