Data manipulation and gradient length estimation in DCA ordination

The effects of different kinds of data manipulation on gradient length estimation by non‐linear rescal‐ing (as in DCA ordination) are evaluated by considering the first axis inDCA ordinations of 11 field data sets from four investigations. Gradient length estimates are dependent on the range of the abundance scale; the more the scale favours the quantitative aspect (abundance) of the data over the qualitative aspect (presence), the longer the DCA axes. The gradient length estimate decreases when infrequent species are deleted. A new formula is proposed to replace the option for downweighting of rare species in DCA, as the option presently available has some undesirable properties. Some implications for interpretation of gradient length estimates by non‐linear rescaling in general (and in DCA in particular) and for comparison of gradient length estimates between studies, are discussed. The potential of non‐linear rescaling of gradients for estimation of β diversity is emphasized.