Ecological research and the way that ecologists use statistics continues to change rapidly. This second edition of the best-selling Design and Analysis of Ecological Experiments leads these trends with an update of this now-standard reference book, with a discussion of the latest developments in experimental ecology and statistical practice. 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.

Ecological Experiments stresses the importance to ecology of field experiments, where variables are manipulated in order to collect data on specific hypotheses, as opposed to the more passive observational method. The book begins by introducing a series of ecological questions that can be addressed experimentally for example, what is the significance of competition among species? The minimal requirements of experimental design that must be met are then introduced, together with examples of good and poor experiments from the ecological literature and a consideration of the trade-offs that may be forced on the experimenter by field conditions. All ecologists, and especially students beginning their careers in field study, will find in this text a good introduction to the experimental foundation of ecology.

Ecological theories and hypotheses are usually complex because of natural variability in space and time, which often makes the design of experiments difficult. The statistical tests we use require data to be collected carefully and with proper regard to the needs of these tests. This book, first published in 1996, describes how to design ecological experiments from a statistical basis using analysis of variance, so that we can draw reliable conclusions. The logical procedures that lead to a need for experiments are described, followed by an introduction to simple statistical tests. This leads to a detailed account of analysis of variance, looking at procedures, assumptions and problems. One-factor analysis is extended to nested (hierarchical) designs and factorial analysis. Finally, some regression methods for examining relationships between variables are covered. Examples of ecological experiments are used throughout to illustrate the procedures and examine problems. This book will be invaluable to practising ecologists as well as advanced students involved in experimental design.

First published in 1996, this book is a logical and consistent approach to experimental design using statistical principles.