An accessible introduction to the theory and practice of multivariate analysis for graduates, researchers and professionals dealing with ecological problems.
An accessible introduction to the theory and practice of multivariate analysis for graduates, researchers and professionals dealing with ecological problems.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Petr milauer is Associate Professor of Ecology in the Department of Ecosystem Biology at the University of South Bohemia. His main research interests are: multivariate statistical analysis, modern regression methods, as well as the role of arbuscular mycorrhizal symbiosis in plant communities. He is co-author of the multivariate analysis software Canoco 5, CANOCO for Windows 4.5, CanoDraw, and TWINSPAN for Windows.
Inhaltsangabe
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.
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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