Demarcation of communities in large databases
Bruelheide, Helge; Jandt, Ute
Different methods were tested in order to classify vegetation in large relevebased data sets. These methods were applied to 3907 releves of oatgrass meadows (Arrhenatherion) and Gentian-hairgrass swards (Mesobromion) in central Germany. Four methods were used: minimum variance clustering (Orloci 1967), number of character species in the Braun-Blanquet system, Twinspan (Hill 1979), and the species group method developed in Göttingen (Bruelheide 1995). Although some details differed, all four methods yielded satisfactory assignment results for both alliances. Differential species which make up the assignment criteria for the resulting vegetation units are obtained by the last two methods only. The species group method uses more species as differential criteria than Twinspan, and therefore assigns only well-characterized stands to a vegetation unit. The species selected by Twinspan result in a higher degree of assignment but have the disadvantage that more releves are misclassified. As a result, the species group method is especially suited for processing large databases and for extracting unambiguous assignment criteria for various uses like mapping vegetation in the field.