Multivariate Analysis of Ecological Data using CANOCO / Edition 1

Multivariate Analysis of Ecological Data using CANOCO / Edition 1

by Jan Leps, Petr Smilauer
     
 

ISBN-10: 0521891086

ISBN-13: 9780521891080

Pub. Date: 06/01/2003

Publisher: Cambridge University Press

Multivariate statistical methods are described in this study and advice is given on how best to apply these methods using CANOCO software. Data sets and program files for the case studies are provided on a supporting website. The book is useful to anyone studying complex ecological problems, such as the variation of biotic communities with environmental conditions

Overview

Multivariate statistical methods are described in this study and advice is given on how best to apply these methods using CANOCO software. Data sets and program files for the case studies are provided on a supporting website. The book is useful to anyone studying complex ecological problems, such as the variation of biotic communities with environmental conditions or their response to experimental manipulations. It is primarily targeted at ecologists who need to analyze data resulting from field observations and experiments.

Product Details

ISBN-13:
9780521891080
Publisher:
Cambridge University Press
Publication date:
06/01/2003
Edition description:
New Edition
Pages:
284
Product dimensions:
6.85(w) x 9.72(h) x 0.59(d)

Table of Contents

1. Introduction and data manipulation; 2. Experimental design; 3. Basics of gradient analysis; 4. Using Canoco; 5. Constrained ordination and permutation tests; 6. Similarity measures; 7. Classification methods; 8. Regression methods; 9. Advanced use of ordination; 10. Visualising multivariate data; 11. Case study 1: variation in forest bird assemblages; 12. Case study 2: search for community composition patterns and their environmental correlates: vegetation of spring meadows; 13. Case study 3: separating the effects of explanatory variables; 14. Case study 4: evaluation of experiments in randomised complete blocks; 15. Case study 5: analysis of repeated observations of species composition from factorial experiment; 16. Case study 6: hierarchical analysis of crayfish community variation; 17. Case study 7: differentiating two species and their hybrids with discriminant analysis.

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