Multivariate Analysis of Ecological Data

Michael Greenacre, Raul Primicerio

Basic Sciences > Mathematics

Data sets used in the book, R scripts for the computations, glossary of terms, and additional material, such as video presentations of some of the analyses, are available at www.multivariatestatistics.org.

Biological diversity is the product of the interaction between many species, be they marine, plant or animal life, and of the many limiting factors that characterize the environment in which the species live. Multivariate analysis uses relationships between variables to order the objects of study according to their collective properties, and to classify the objects of study, that is to group species or ecosystems in distinct classes each containing entities with similar properties. The ultimate objective is to relate the observed biological variation to the accompanying environmental characteristics.

Multivariate Analysis of Ecological Data is a comprehensive and structured explanation of how to analyse and interpret ecological data observed on many variables, both biological and environmental. After a general introduction to multivariate ecological data and statistical methodology, specific chapters focus on methods such as clustering, regression, biplots, multidimensional scaling, correspondence analysis (both simple and canonical) and log-ratio analysis, as well as issues of modelling and the inferential aspects of these methods.

The book includes a variety of applications to real data from ecological research, as well as two detailed case studies where the reader can appreciate the challenge for analysis, interpretation and communication when dealing with large studies and complex designs.

Chapters in PDF Format
Chapter 1
Chapter 2
Chapter 3
Chapter 4
Chapter 5
Chapter 6
Chapter 7
Chapter 8
Chapter 9
Chapter 10
Chapter 11
Chapter 12
Chapter 13
Chapter 14
Chapter 15
Chapter 16
Chapter 17
Chapter 18
Chapter 19
Chapter 20
Appendix A
Appendix B
Appendix C


Book in PDF format