Co-ordinating Editor: M. Chytrý.
A new algorithm for the determination of differential taxa
Article first published online: 25 MAR 2009
© 2009 International Association for Vegetation Science
Journal of Vegetation Science
Volume 20, Issue 2, pages 233–240, April 2009
How to Cite
Tsiripidis, I., Bergmeier, E., Fotiadis, G. and Dimopoulos, P. (2009), A new algorithm for the determination of differential taxa. Journal of Vegetation Science, 20: 233–240. doi: 10.1111/j.1654-1103.2009.05273.x
- Issue published online: 25 MAR 2009
- Article first published online: 25 MAR 2009
- Received 4 April 2007;Accepted 9 March 2008.
- Community ecology;
- Diagnostic taxa;
- Floristic gradients;
Question: How can we determine differential taxa in a vegetation data set?
Methods: The new algorithm presented here uses an intuitive fidelity threshold based on relative constancy differences. It is tested on a simulated and a real data set. The results of the proposed algorithm are discussed in comparison with other methods used for the determination of differential taxa.
Results: The new algorithm defines each taxon in each group of relevés as: (1) positively differentiating, (2) positively-negatively differentiating, (3) negatively differentiating, or (4) non-differentiating. Each taxon in a data set may be: (1) positively, positively-negatively or negatively differentiating for each group in the data set, (2) differentiating for some groups and non-differentiating for the remaining groups, or (3) non-differentiating for all groups in the data set.
Conclusions: The new algorithm finds the relevé groups that are positively differentiated against other groups that are negatively differentiated. It reveals differentiating structures in the data set and thus makes quantification of the relations among and between different syntaxonomic ranks conceivable. As it distinguishes between different types of differential taxa, it might improve standards of typification in vegetation classification.