Community Ecology

, Volume 7, Issue 1, pp 99–108 | Cite as

Validation of phytosociological classifications based on a fuzzy set approach

  • E. FeoliEmail author
  • G. Ferro
  • P. Ganis


We propose a simple method to validate vegetation types in phytosociological tables obtained with the Braun-Blanquet approach. The method is based on fuzzy set theory and it measures the sharpness of a classification of relevés based on degrees of belonging calculated by similarity functions. The idea animating this work is that the validated vegetation types offer non-random species combinations that can be used to model environmental changes taking biodiversity into account. Phytosociological tables are widely available today and the information they contain can be very useful in studying environmental changes at different scales, from local to global.


Fuzzy sets Similarity Syntaxonomy Vegetation types 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Anand, M. and L. Orlóci. 1997. Chaotic dynamics in a multispecies community. Environmental and Ecological Statistics 4:337–344.CrossRefGoogle Scholar
  2. Andreucci, F., E. Biondi, E. Feoli and V. Zuccarello. 2000. Modeling environmental responses of plant associations by fuzzy set theory. Community Ecology 1:73–80.Google Scholar
  3. Austin, M.P. 1985. Continuum concept, ordination methods, and niche theory. Ann. Rev. Ecol. Syst. 16:39–61.Google Scholar
  4. Austin, M.P. 2004. Vegetation and environment: discontinuities and continuities. In: E. van der Maarel (ed.), Vegetation Ecology. Blackwell, Oxford. pp. 52–84.Google Scholar
  5. Austin, M.P. and T.M. Smith. 1989. A new model for the continuum concept. Vegetatio 83:35–47.Google Scholar
  6. Biondi, E., E. Feoli and V. Zuccarello. 2004. Modelling environmental responses of plant associations: a review of some critical concepts in vegetation study. Critical Review in Plant Sciences 23:149–156.Google Scholar
  7. Blasi, C., M.L. Carranza., R. Frondoni and L. Rosati. 2000. Ecosystem classification and mapping for Italian landscapes. Appl. Veg. Sci. 3:233–242.Google Scholar
  8. Braun-Blanquet, J. 1964. Pflanzensoziologie.Grundzüge der Vegetationskunde. Ed. 3. Springer Verlag, Wien. pp. 865.Google Scholar
  9. Burnaby, T.P. 1970. On a method for character weighting a similarity coefficient, employing the concept of information. J. Int. Ass. Math. Geol. 2:25–38.Google Scholar
  10. Carranza, L., E. Feoli and P. Ganis. 1998. Analysis of vegetation structural diversity by Burnaby’s similarity index. Plant Ecology 138:77–87.Google Scholar
  11. Cox, E. 1994. The Fuzzy Systems Handbook. Academic Press Inc., London.Google Scholar
  12. Dale, M. 1988. Mutational and non-mutational similarity measures: a preliminary examination. Coenoses 3:121–133.Google Scholar
  13. Dale, M.B. 1994. Do ecological communities exist? J. Veg. Sci. 5:285–286.Google Scholar
  14. Feoli, E. 1984. Some aspects of classification and ordination of vegetation data in perspective. Studia Geobotanica 4:7–21.Google Scholar
  15. Feoli, E. and M. Lagonegro. 1983. A resemblance function based on probability: Applications to field and simulated data. Vegetatio 53:3–9.Google Scholar
  16. Feoli, E. and L. Orlóci. 1979. Analysis of concentration and detection of underlying factors in structured tables. Vegetatio 40:49–54.Google Scholar
  17. Feoli, E. and L. Orlóci. (eds). 1991. Computer Assisted Vegetation Analysis. Kluwer, Dordrecht.Google Scholar
  18. Feoli, E. and V. Zuccarello. 1986. Ordination based on classification: yet another solution? Abstracta Botanica 10:203–219.Google Scholar
  19. Ferro G., F. Lucchese and B. Scammacca. 1997. Studio fitosociologico sulla vegetazione segetale del Molise (Italia centrale). Studia Bot. 16:91–133.Google Scholar
  20. Hannah, L., G.F. Midgley and D. Millar. 2002. Climate change-integrated conservation strategies. Global Ecology and Biogeography 11:485–495.Google Scholar
  21. Goodall, D.W. 1964. A probabilistic similarity index. Nature 203:1098.Google Scholar
  22. Goodall, D.W. 1966. A new similarity index based on probability. Biometrics 22:882–907.Google Scholar
  23. Goodall, D.W. 1993. Probabilistic indices for classification - Some extensions. Abstracta Botanica 17:125–132.Google Scholar
  24. Goodall, D.W. and E. Feoli. 1988. Application of probabilistic methods in the analysis of phytosociological data. Coenoses 3:1–12.Google Scholar
  25. Goodall, D.W., P. Ganis and E. Feoli. 1987. Probabilistic methods in classification: a manual for seven computer programs. GEADQ 7, Universita’ degli Studi di Trieste, pp. 50.Google Scholar
  26. Goodall, D.W., P. Ganis and E. Feoli. 1991. Probabilistic methods in classification: a manual for seven computer programs. In: Feoli, E. and L. Orlóci. (eds). Computer Assisted Vegetation Analysis. Kluwer, Dordrecht, pp. 453–467.Google Scholar
  27. Jongman, R.H.G., C.J.F. ter Braak and O.F.R. van Tongeren. 1995. Data Analysis in Community and Landscape Ecology. Cambridge Univ. Press, Cambridge.Google Scholar
  28. Küchler, A.W. and I.S. Zonneveld (eds). 1988. Vegetation Mapping. Kluwer, Dordrecht.Google Scholar
  29. Legendre, P. and L. Legendre. 1998. Numerical Ecology. Second English edition. Elsevier, Amsterdam.Google Scholar
  30. Mirkin, B.M. 1987. Paradigm change and vegetation classification in Soviet phytocoenology. Vegetatio 68:131–138.Google Scholar
  31. Mirkin, B.M. 1994. Which plant communities do exist? J. Veg. Sci. 5:283–284.Google Scholar
  32. Mucina, L. 1997. Classification of vegetation: past present and future. J. Veg. Sci. 8:751–760.Google Scholar
  33. Mucina, L. and M.B. Dale (eds). 1989. Numerical Syntaxonomy. Kluwer, Dordrecht.Google Scholar
  34. Mucina, L. and E. van der Maarel. 1989. Twenty years of numerical syntaxonomy. Vegetatio 81:1–15.Google Scholar
  35. Mueller-Dombois, D. and H. Ellenberg. 1974. Aims and methods of vegetation ecology. J. Wiley, New York.Google Scholar
  36. Orlóci, L. 1978. Multivariate Analysis in Vegetation Research. Dr. W. Junk, The Hague.Google Scholar
  37. Orlóci, L. 2001a. Pattern dynamics: an essay concerning principles, techniques, and applications. Community Ecology 2:1–15.Google Scholar
  38. Orlóci, L. 2001b. Prospects and expectations: reflections on a science in change. Community Ecology 2:187–196.Google Scholar
  39. Orlóci, L., M. Anand and V.D. Pillar. 2002a. Biodiversity analysis: issues, concepts, techniques. Community Ecology 3:217–236.Google Scholar
  40. Orlóci, L., V.D. Pillar, M. Anand and H. Behling. 2002b. Some interesting characteristics of the vegetation process. Community Ecology 3:125–146.Google Scholar
  41. Palmer, M.W. and P.S. White. 1994. On the existence of ecological communities. J. Veg. Sci. 5:279–282.Google Scholar
  42. Pausas, J.C. and E. Feoli. 1996. Environment-vegetation relationships in the understorey of Pyrenean Pinus sylvestris forest. II. A classification approach. Coenoses 11:45–51.Google Scholar
  43. Pignatti, S. 1990. Towards a prodrome of plant communities. J. Veg. Sci. 1:425–426.Google Scholar
  44. Pillar, V.D. 1999. How sharp are classifications? Ecology 80:2508–2516.Google Scholar
  45. Pillar, V.D. and L. Orlóci. 1996. On randomization testing in vegetation science: multifactor comparisons of relevé groups. J. Veg. Sci. 7:585–592.Google Scholar
  46. Podani, J. 1995. Multivariate Data Analysis in Ecology and Systematics. A Methodological Guide to the SYN-TAX 5.0 package. SPB Academic Publishing bv., The Hague.Google Scholar
  47. Podani, J. 2000. Introduction to the Exploration of Multivariate Biological Data. Backhuys, Leiden.Google Scholar
  48. Podani, J. 2005. Multivariate exploratory analysis of ordinal data in ecology: Pitfalls, problems and solutions. J. Veg. Sci. 16:497–510.Google Scholar
  49. Rivas-Martínez, S., F. Fernandez-Gonzalez, J. Loidi, M. Lousa and A. Penas. 2001. Syntaxonomical check list of vascular plant communities of Spain and Portugal to association level. Itin. Geob. 14:5–341.Google Scholar
  50. Rivas-Martínez, S., F. Fernandez-Gonzalez, J. Loidi, M. Lousa and A. Penas. 2002. Vascular plant communities of Spain and Portugal. Addenda to the syntaxonomical check list of 2001. Itin. Geob. 15:5–922.Google Scholar
  51. Roberts, D.W. 1986. Ordination on the basis of fuzzy set theory. Vegetatio 66:123–131.Google Scholar
  52. Rodwell, J.S., S. Pignatti, L. Mucina and J.H.J. Schaminée. 1995. European vegetation survey: update on progress. J. Veg. Sci. 6:579–662.Google Scholar
  53. Roy, K., J.W. Valentine, D. Jablonski and S.M. Kidwell. 1996. Scales of climatic variability and time averaging in Pleistocene biotas: implications for ecology and evolution. Trends in Ecology and Evolution 11:458–463.PubMedGoogle Scholar
  54. Sneath, P.H.A. and R.R. Sokal. 1973. Numerical Taxonomy. W.H.Freeman and Company, San Francisco.Google Scholar
  55. Solomeshch, A.I and B.M. Mirkin. 1999. The innovation period of vegetation classification in the former USSR: a complement to the paper by L. Mucina. J .Veg. Sci. 10:295–296.Google Scholar
  56. Stafford, T.W., H.A. Semkem, R.W Graham, W.F. Klippel, A. Markova, N.G. Smirnov and J. Souton. 1999. First accelerator mass spectrometry 14C dates documenting contemporaneity of nonanalog species in late Pleistocene mammal communities. Geology 27:903–906.Google Scholar
  57. Tobisch, T. and Standovár T. 2005. A comparison of vegetation patterns in the tree and herbs layers of a hardwood forest. Community Ecology 6:29–37.Google Scholar
  58. van der Maarel, E. 1975. The Braun-Blanquet approach in perspective. Vegetatio 30:213–219.Google Scholar
  59. van der Maarel, E. 1981. Some perspectives of numerical methods in syntaxonomy. In: H. Dierschke (ed.) Syntaxonomie. J. Cramer, Vaduz, pp 77–93.Google Scholar
  60. van der Maarel, E. (ed). 2004. Vegetation Ecology. Blackwell Publishers, Oxford.Google Scholar
  61. Wallace, C.S. and M.B. Dale. 2005. Hierarchical clusters of vegetation types. Community Ecology 6:57–74.Google Scholar
  62. Westhoff, V. and E. van der Maarel. 1978. The Braun-Blanquet approach. In: R.H. Whittaker (ed.), Classification of Plant Communities. 2nd ed. Junk, The Hague. pp. 287–399.Google Scholar
  63. Wilson, J.B. 1994. Who makes the assembly rules? J. Veg. Sci. 5:275–278.Google Scholar
  64. Wilson, J.B., R.K. Peet and M.T. Sykes. 1995. What constitutes evidence of community structure? A reply to van der Maarel, Noest and Palmer. J. Veg. Sci. 6:753–758.Google Scholar
  65. Zimmerman, H. 1996. Fuzzy Set Theory and its Applications. 3rd ed.. Kluwer, Dordrecht.Google Scholar

Copyright information

© Akadémiai Kiadó, Budapest 2006

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (, which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Authors and Affiliations

  1. 1.Department of BiologyUniversity of TriesteTriesteItaly
  2. 2.Department of BotanyUniversity of CataniaCataniaItaly

Personalised recommendations