Skip to main content

A new dissimilarity measure and a new optimality criterion in phytosociological classification

  • Chapter
Book cover Progress in theoretical vegetation science

Part of the book series: Advances in vegetation science ((AIVS,volume 11))

  • 278 Accesses

Abstract

A new dissimilarity measure, Uppsala dissimilarity, is proposed. It is a Manhattan-type measure in between the Canberra and Gower measures, based on the differences between scores in relevés compared, but it also takes both the sums of scores and the difference between maximum and minimum score into account. The measure is considered realistic for phytosociological material.

A new optimality criterion has been developed after unsatisfactory results had been obtained with the DOL criterion (Popma et al. 1983) which was developed previously by our group. Problems with DOL were especially met when the criterion was applied to the distribution of only one species over the cluster array obtained. The new criterion takes both internal cluster homogeneity and between-cluster dissimilarity into account. Between-cluster dissimilarity is calculated for all other clusters and not only for the nearest neighbour, as in DOL. The new criterion has both an unweighted form: SOM, and a form with weighting for cluster size: SWOM.

This new criterion was successfully applied to the evaluation of the sharpness of distribution of individual species over cluster arrays, under the name of SIM: species indication measure and SWIM, species weighted indication measure.

The measures were applied to some test data. Differences between the unweighted and weighted forms were found which could not be easily interpreted.

Some remarks are made on the coherence of d-SAHN and h-SAHN approaches in agglomerative clustering within the new strategy proposed.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Abbreviations

DOL:

Detection of Optimal Level

S(W)IM:

Species (Weighted) Indication Measure

S(W)OM:

Standardized (Weighted) Optimality Measure

UD:

Uppsala Dissimilarity measure

WPGMA:

Weighted Pair-Group Method Average linking clustering

SAHN:

Sequential Agglomerative Hierarchical Non-overlapping clustering

References

  • Beals, E. W. 1984. Bray Curtis ordination: an effective strategy for analysis of multivariate ecological data. Adv. Ecol. Res. 14: 1–55.

    Article  Google Scholar 

  • Digby, P. G. N. & Kempton, R. A. 1987. Multivariate analysis of ecological communities. Chapman and Hall, London.

    Google Scholar 

  • Faith, D. P. 1984. Patterns of sensitivity of association measures in numerical taxonomy. Math. Biosci. 69: 199–207.

    Article  Google Scholar 

  • Faith, D. P., Minchin, P. R. & Beibin, L. 1987. Compositional dissimilarity as a robust measure of ecological distance. Vegetatio 69: 57–68.

    Article  Google Scholar 

  • Feoli, E. & Lausi, D. 1980. Hierarchical levels in syntaxonomy based on information functions. Vegetatio 42: 113–115.

    Article  Google Scholar 

  • Gauch Jr, H. G. 1982. Multivariate analysis in community ecology. Cambridge University Press, Cambridge.

    Google Scholar 

  • Gower, J. C. 1971. A general coefficient of similarity and some of its properties. Biometrics 23: 623–637.

    Article  Google Scholar 

  • Greig-Smith, P. 1983. Quantitative plant ecology. 3rd. ed. Blackwell, Oxford.

    Google Scholar 

  • Hill, M. O., Bunce, R. G. H. & Shaw, M. W. 1975. Indicator species analysis, a divisive polythetic method of classification, and its application to a survey of native pinewoods in Scotland. J. Ecol. 63: 597–613.

    Article  Google Scholar 

  • Hogeweg, P. 1976. Iterative character weighting in numerical taxonomy. Comp. Biol. Med. 6: 199–211.

    Article  CAS  Google Scholar 

  • Jongman, R. H. G., ter Braak, C. J. F. & van Tongeren, O. F. R. 1987. Data analysis in community and landscape ecology. Pudoc, Wageningen.

    Google Scholar 

  • Legendre, L. & Legendre, P. 1983. Numerical ecology. Elsevier, Amsterdam.

    Google Scholar 

  • Ludwig, J. A. & Reynolds, J. F. 1988. Statistical ecology. Wiley, New York.

    Google Scholar 

  • Noest, V., van der Maarel, E., van der Meulen, F. & van der Laan, D. 1989. Optimum-transformation of plant species cover-abundance values. Vegetatio 83: 167–178.

    Article  Google Scholar 

  • Pielou, E. C. 1984. The interpretation of ecological data. A primer on classification and ordination. Wiley, New York.

    Google Scholar 

  • Podani, J. 1989. New combinatorial cluster methods. Vegetatio 81: 61–77.

    Article  Google Scholar 

  • Popma, J., Mucina, L., van Tongeren, O. F. R. & van der Maarel, E. 1983. On the determination of optimal levels in phytosociological classification. Vegetatio 52: 65–75.

    Article  Google Scholar 

  • Ratliff, D. & Pieper, R. D. 1981. Deciding final clusters: An approach using intra- and intercluster distances. Vegetatio 48: 83–86.

    Article  Google Scholar 

  • Sneath, P. H. A. & Sokal, R. R. 1973. Numerical taxonomy. Freeman, San Francisco.

    Google Scholar 

  • van der Maarel, E. 1979a. Transformation of cover-abundance values in phyto sociology and its effects on community similarity. Vegetatio 39: 97–114.

    Article  Google Scholar 

  • van der Maarel, E. 1979b. Multivariate methods in phytosociology, with reference to the Netherlands. In: Werger, M. J. A. (ed.), The study of vegetation, pp. 163–225. Junk, The Hague.

    Google Scholar 

  • van der Maarel, E., Janssen, J. G. M. & Louppen, J. M. W. 1978. TABORD, a program for structuring phytosociological tables. Vegetado 38: 143–156.

    Article  Google Scholar 

  • Ward, J. H. 1963. Hierarchical grouping to optimize an objective function. J. Amer. Statist. Ass. 58: 236–244.

    Article  Google Scholar 

  • Wishart, D. 1978. Clustan users manual, 3rd ed. Edinburgh University, Edinburgh.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

G. Grabherr L. Mucina M. B. Dale C. J. F. Ter Braak

Rights and permissions

Reprints and permissions

Copyright information

© 1990 Kluwer Academic Publishers

About this chapter

Cite this chapter

Noest, V., van der Maarel, E. (1990). A new dissimilarity measure and a new optimality criterion in phytosociological classification. In: Grabherr, G., Mucina, L., Dale, M.B., Ter Braak, C.J.F. (eds) Progress in theoretical vegetation science. Advances in vegetation science, vol 11. Springer, Dordrecht. https://doi.org/10.1007/978-94-009-1934-1_13

Download citation

  • DOI: https://doi.org/10.1007/978-94-009-1934-1_13

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-94-010-7363-9

  • Online ISBN: 978-94-009-1934-1

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics