, Volume 42, Issue 1–3, pp 47–58 | Cite as

Detrended correspondence analysis: An improved ordination technique

  • M. O. Hill
  • H. G. GauchJr.


Detrended correspondence analysis (DCA) is an improvement upon the reciprocal averaging (RA) ordination technique. RA has two main faults: the second axis is often an ‘arch’ or ‘horseshoe’ distortion of the first axis, and distances in the ordination space do not have a consistent meaning in terms of compositional change (in particular, distances at the ends of the first RA axis are compressed relative to the middle). DCA corrects these two faults. Tests with simulated and field data show DCA superior to RA and to nonmetric multidimensional sealing in giving clear, interpretable results. DCA has several advantages. (a) Its performance is the best of the ordination techniques tested, and both species and sample ordinations are produced simultaneously. (b) The axes are scaled in standard deviation units with a definite meaning, (c) As implemented in a FORTRAN program called DECORANA, computing time rises only linearly with the amount of data analyzed, and only positive entries in the data matrix are stored in memory, so very large data sets present no difficulty. However, DCA has limitations, making it best to remove extreme outliers and discontinuities prior to analysis. DCA consistently gives the most interpretable ordination results, but as always the interpretation of results remains a matter of ecological insight and is improved by field experience and by integration of supplementary environmental data for the vegetation sample sites.


Correspondence analysis Multivariate technique Nonmetric multidimensional scaling Ordination Reeiprocal averaging 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Austin, M.P. 1976a. On non-linear species response models in ordination. Vegetatio 33: 33–41.Google Scholar
  2. Austin, M.P. 1976b. Performance of four ordination techniques assuming three different non-linear species response models. Vegetatio 33: 43–49.Google Scholar
  3. Austin, M.P. & I., Noy-Meir. 1972. The problem of non-linearity in ordination: experiments with two-gradient models. J. Ecol. 59: 763–773.Google Scholar
  4. Beals, E.W. 1973. Ordination: mathematical elegance and ecological naïveté. J. Ecol. 61: 23–35.Google Scholar
  5. Benzécri, J.P. 1973. L'Analyse des données (vol. 2: L'analyse des Correspondances). Dunod, Paris, 619 pp.Google Scholar
  6. Curtis, J.T. 1959. The Vegetation of Wisconsin: An Ordination of Plant Communities. Chiversity of Wisconsin, Madison, 657 pp.Google Scholar
  7. Dale, M.B. 1975. On objectives of ordination. Vegetatio 30: 15–32.Google Scholar
  8. Ellenberg, H. 1956. Aufgaben und Methoden der Vegetationskunde. Ulmer, Stuttgart, 136 pp.Google Scholar
  9. Fasham, M.J.R. 1977. A comparison of nonmetric multidimensional scaling, principal components and reciprocal averaging for the ordination of simulated coenoclines, and coenoplanes. Ecology 58: 551–561.Google Scholar
  10. Gauch, H.G. 1973. The relationship between sample similarity and ecological distance. Ecology 54: 618–622.Google Scholar
  11. Gauch, H.G. 1977. ORDIFLEX — A flexible computer program for four ordination techniques: weighted averages, polar ordination, principal components analysis, and reciprocal averaging. Release B. Ecology and Systematics, Cornell University, Ithaca, New York 14850, 185 pp.Google Scholar
  12. Gauch, H.G. 1980. Rapid initial clustering of large data sets. In: E. van der Maarel (ed.) Advances in vegetation science: Classification and ordination. Vegetatio 42: 103–111.Google Scholar
  13. Gauch, H.G. & W.M., Scruggs. 1980. Variants of Bray-Curtis polar ordination. Vegetatio 40: 147–153.Google Scholar
  14. Gauch, H.G. & R.H., Whittaker. 1972. Comparison of ordination techniques. Ecology 53: 868–875.Google Scholar
  15. Gauch, H.G., G.B., Chase & R.H., Whittaker. 1974. Ordination of vegetation samples by Gaussian species distributions. Ecology 55: 1382–1390.Google Scholar
  16. Gauch, H.G., R.H. Whittaker & S.B. Singer. 1979. Acomparative study of nonmetric ordinations. J. Ecol. (in press).Google Scholar
  17. Gauch, H.G., R.H., Whittaker & T.R., Wentworth. 1977. A comparative study of reciprocal averaging and other ordination techniques. J. Ecol. 65: 157–174.Google Scholar
  18. Hill, M.O. 1973. Reciprocal averaging: an eigenvector method of ordination. J. Ecol. 61: 237–249.Google Scholar
  19. Hill, M.O. 1974. Correspondence analysis: a neglected multivariate method. J. Roy. Stat. Soc., Ser. C 23: 340–354.Google Scholar
  20. Hill, M.O. 1979. DECORANA—A FORTRAN program for detrended correspondence analysis and reciprocal averaging. Ecology and Systematics, Cornell University, Ithaca, New York 14850, 52 pp.Google Scholar
  21. Ihm, P. & H.van, Groenewoud. 1975. A multivariate ordering of vegetation data based on Gaussian type gradient response curves. J. Ecol. 63: 767–777.Google Scholar
  22. Kendall, D.G. 1971. Seriation from abundance matrices. In: F.R. Hodson, D.G. Kendall & P. Tautu (eds.). Mathematics in the archeological and historical sciences, p. 215–252. Edinburgh University Press.Google Scholar
  23. Kessell, S.R. & R.H., Whittaker. 1976. Comparisons of three ordination techniques. Vegetatio 32: 21–29.Google Scholar
  24. Maarel, E.van der. 1979. Transformation of cover-abundance values in phytosociology and its effects on community similarity. Vegetatio 39: 97–114.Google Scholar
  25. Maarel, E.van der, J.G.M., Janssen & J.M.W., Louppen. 1978. TABORD, A program for structuring phytosociological tables. Vegetatio 38: 143–156.Google Scholar
  26. Mueller-Dombois, D. & H., Ellenberg. 1974. Aims and methods of vegetation ecology. John Wiley & Sons, New York, 547 pp.Google Scholar
  27. Noy-Meir, I. 1974. Catenation: quantitative methods for the definition of coenoclines. Vagetatio 29: 89–99.Google Scholar
  28. Noy-Meir, I. & R.H., Whittaker, 1977. Continuous multivariate methods in community analysis: some problems and developments. Vegetatio 33: 79–98.Google Scholar
  29. Noy-Meir, I. & R.H., Whittaker. 1978. Recent developments in continuous multivariate techniques. In: R.H., Whittaker (ed.). Ordination of plant communities, p. 337–378. Junk, The Hague.Google Scholar
  30. Orlóci, L. 1978. Multivariate analysis in vegetation research. Junk, The Hague, 451 pp.Google Scholar
  31. Prentice, I.C. 1977. Non-metric ordination methods in ecology. J. Ecol. 65: 85–94.Google Scholar
  32. Sabo, S.R. 1979. Niche and habitat relations of birds in subalpine forests, New Hampshire, Ecology (in press).Google Scholar
  33. Swan, J.M.A. 1970. An examination of some ordination problems by use of simulated vegetational data. Ecology 51: 89–102.Google Scholar
  34. Whittaker, R.H. 1954. The ecology of serpentine soils. IV. The vegetational response to serpentine soils. Ecology 35: 275–288.Google Scholar
  35. Whittaker, R.H. 1956. Vegetation of the Great Smoky Mountains. Ecol. Monogr. 26: 1–80.Google Scholar
  36. Whittaker, R.H. 1960. Vegetation of the Siskiyou Mountains, Oregon and California. Ecol. Monogr. 30: 279–338.Google Scholar
  37. Whittaker, R.H. & H.G., Gauch. 1978. Evaluation of ordination techniques. In: R.H., Whittaker (ed.). Ordination of plant communities, p. 277–336, Junk, The Hague.Google Scholar

Copyright information

© Dr. W. Junk b.v. Publishers 1980

Authors and Affiliations

  • M. O. Hill
    • 1
  • H. G. GauchJr.
    • 1
  1. 1.Section of Ecology and SystematicsCornell UniversityIthacaUSA

Personalised recommendations