Abstract
The development of non-linear ordination techniques has stemmed in part from work suggesting that species behave non-linearly to changing environmental factors or gradients. Developments in this area can be seen in two related phases: new algorithms, and the incorporation of new resemblance measures. Emphasis in this paper is placed on resemblance measures incorporated into a method of multi-dimensional scaling. The results show that a resemblance measure which reflects the non-linearities of the data can produce significant improvement in ordination, if the standardizations have not been too ‘severe’.
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One of the authors (L. Orlóci) was a recipient of an N.S.E.R.C. grant during the tenure of this project. The authors with to thank C. Brambilla and G. Salzano for the use of their computer program. A copy of a modified version used here may be obtained from the first author at no charge.
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Fewster, P.H., Orlóci, L. On choosing a resemblance measure for non-linear predictive ordination. Vegetatio 54, 27–35 (1983). https://doi.org/10.1007/BF00036078
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DOI: https://doi.org/10.1007/BF00036078