Description
The 3rd edition of this popular textbook introduces the reader to the investigation of vegetation systems with an emphasis on data analysis. The book succinctly illustrates the various paths leading to high quality data suitable for pattern recognition, pattern testing, static and dynamic modelling and model testing including spatial and temporal aspects of ecosystems.
Step-by-step introductions using small examples lead to more demanding approaches illustrated by real world examples aimed at explaining interpretations. All data sets and examples described in the book are available online and are written using the freely available statistical package R.
This book will be of particular value to beginning graduate students and postdoctoral researchers of vegetation ecology, ecological data analysis, and ecological modelling, and experienced researchers needing a guide to new methods.
A completely revised and updated edition of this popular introduction to data analysis in vegetation ecology. Includes practical step-by-step examples using the freely available statistical package R. Complex concepts and operations are explained using clear illustrations and case studies relating to real world phenomena. Emphasizes method selection rather than just giving a set of recipes.
Table of contents
- 1: Introduction
- 2: Patterns in vegetation ecology
- 3: Transformation
- 4: Multivariate comparison
- 5: Classification
- 6: Ordination
- 7: Ecological patterns
- 8: Traits and Indicators
- 9: Static predictive modelling
- 10: Vegetation change in time
- 11: Dynamic modelling
- 12: Revising classifications
- 13: Swiss forests: a case study
- 14: Back to the roots?
Readership
Suitable for graduate students of vegetation ecology, ecological data analysis, and ecological modelling, and practicing researchers needing a guide to new methods or a refresher course.
Reviews
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