Design and Analysis of Ecological Experiments

The goal of this volume is to encourage the correct use of some of the more well known statistical techniques and to make some of the less well known but potentially very useful techniques available. Chapters from the first edition have been substantially revised and new chapters have been added. Readers are introduced to statistical techniques that may be unfamiliar to many ecologists, including power analysis, logistic regression, randomization tests and empirical Bayesian analysis. In addition, a strong foundation is laid in more established statistical techniques in ecology including exploratory data analysis, spatial statistics, path analysis and meta-analysis. Each technique is presented in the context of resolving an ecological issue. Anyone from graduate students to established research ecologists will find a great deal of new practical and useful information in this current edition.

The goal of this book is to make some underutilized but potentially very useful methods in experimental design and analysis available to ecologists, and to encourage better use of standard statistical techniques. Ecology has become more and more an experimental science in both basic and applied work,but experiments in the field and in the laboratory often present formidable statistical difficulties. Organized around providing solutions to ecological problems, this book offers ways to improve the statistical aspects of conducting manipulative ecological experiments, from setting them up to interpreting and reporting the results. An abundance of tools, including advanced approaches, are made available to ecologists in step-by-step examples, with computer code provided for common statistical packages. This is an essential how-to guide for the working ecologist and for graduate students preparing for research and teaching careers in the field of ecology.

Booknews

The 18 chapters in this graduate textbook on advanced statistical techniques for ecologists describe such methods as power analysis, logistic regression, randomization tests, and empirical Bayesian analysis. The second edition reflects changes in statistical theory, and computer software and hardware capabilities. Annotation c. Book News, Inc., Portland, OR (booknews.com)

National Science Foundation

SUNY at Stony Brook