CiNii 図書 - Multivariate analysis of ecological data using Canoco 5

This revised and updated edition focuses on constrained ordination (RDA, CCA), variation partitioning and the use of permutation tests of statistical hypotheses about multivariate data. Both classification and modern regression methods (GLM, GAM, loess) are reviewed and species functional traits and spatial structures analysed. Nine case studies of varying difficulty help to illustrate the suggested analytical methods, using the latest version of Canoco 5. All studies utilise descriptive and manipulative approaches, and are supported by data sets and project files available from the book website: http://regent.prf.jcu.cz/maed2/. Written primarily for community ecologists needing to analyse data resulting from field observations and experiments, this book is a valuable resource to students and researchers dealing with both simple and complex ecological problems, such as the variation of biotic communities with environmental conditions or their response to experimental manipulation.

Preface
1. Introduction and data types
2. Using Canoco 5
3. Experimental design
4. Basics of gradient analysis
5. Permutation tests and variation partitioning
6. Similarity measures and similarity-based methods
7. Classification methods
8. Regression methods
9. Interpreting community composition with functional traits
10. Advanced use of ordination
11. Visualising multivariate data
12. Case study 1: variation in forest bird assemblages
13. Case study 2: search for community composition patterns and their environmental correlates: vegetation of spring meadows
14. Case study 3: separating the effects of explanatory variables
15. Case study 4: evaluation of experiments in randomised complete blocks
16. Case study 5: analysis of repeated observations of species composition from a factorial experiment
17. Case study 6: hierarchical analysis of crayfish community variation
18. Case study 7: analysis of taxonomic data with linear discriminant analysis and distance-based ordination methods
19. Case study 8: separating effects of space and environment on oribatid community with PCNM
20. Case study 9: performing linear regression with redundancy analysis
Appendix A. Glossary
Appendix B. Sample data sets and projects
Appendix C. Access to Canoco and overview of other software
Appendix D. Working with R
References
Index to useful tasks in Canoco 5
Index.

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Multivariate analysis of ecological data using Canoco 5

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