Multivariate Analysis of Ecological Data using CANOCO 5: Case study 3: Separating the effects of explanatory variables

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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