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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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