Does Ordinal Cover Estimation Offer Reliable Quality Data Structures in Vegetation Ecological Studies?

Using visual estimation of species cover in ordinal interval classes may reduce costs in vegetation studies. In phytosociology, species cover within plots is usually estimated according to the well-known Braun-Blanquet scale and ordinal data from this scale are usually treated using common exploratory analysis tools that are adequate for ratio-scale variables only. This paper addresses whether the visual estimation of ordinal cover data and the treatment of these data with multivariate procedures tailored for ratio-scale data would lead to a significant loss of information with respect to the use of more accurate methods of data collection and analysis. To answer these questions we used three data sets sampled by different authors in different sites of Tuscany (central Italy) in which the species cover is measured with the point quadrat method. For each data set we used a Mantel test to compare the dissimilarity matrices obtained from the original point-quadrat cover data with those obtained from the corresponding ordinal interval classes. The results suggest that the ordinal data are suitable to represent the plot-to-plot dissimilarity structure of all data sets in a reasonable way and that in using such data there is no need to apply dissimilarity coefficients specifically tailored for ordinal scales.