Computer assisted vegetation analysis

I.- 1. The properties and interpretation of observations in vegetation study.- Sampling.- 2. Computerized sampling in vegetation studies.- 3. Sampling with multiple objectives and the role of spatial autocorrelation.- 4. On sample size optimality in ecosystem survey.- 5. Statistics in ecosystem survey: computer support for process-based sample stability tests and entropy/information inference.- 6. Computer simulation and sampling efficiency.- Databases.- 7. The relational model for data bases in community studies.- Characters and Character Selection.- 8. On character-based plant community analysis: choice, arrangement, comparison.- 9. Fuzzy components in community level comparisons.- 10. Fuzzy linguistics concept in redescription of vegetation data.- 11. A comparison of some methods of selecting species in vegetation analysis.- Similarity Measures.- 12. Mutational and nonmutational similarity measures: a preliminary examination.- 13. Application of probabilistic methods in the analysis of phytosociological data.- Classification.- 14. Knowing when to stop: cluster concept-concept cluster.- 15. Fuzzy clustering of ecological data.- 16. A method for generating consensus partitions and its application to community classification.- 17. A general strategy for the simultaneous classification of variables and observations in ecological data tables.- Evaluation of Classification.- 18. Locality theory: the phenomenon and its significance.- 19. Permutation techniques based on euclidean analysis spaces: a new and powerful statistical method for ecological research.- 20. Comparison of fuzzy classifications.- Ordination.- 21. Flexible gradient analysis: a note on ideas and an application.- 22. Ordination based on classification: yet another solution?.- 23. Syntaxonomy: a source of useful fuzzy sets for environmental analysis?.- 24. Community niche, an effective concept to measure diversity of gradients and hyperspaces.- 25. On niche separation and its measurement.- 26.