SPECIES ASSEMBLAGES AND INDICATOR SPECIES:THE NEED FOR A FLEXIBLE ASYMMETRICAL APPROACH

Abstract

This paper presents a new and simple method to find indicator species and species assemblages characterizing groups of sites. The novelty of our approach lies in the way we combine a species relative abundance with its relative frequency of occurrence in the various groups of sites. This index is maximum when all individuals of a species are found in a single group of sites and when the species occurs in all sites of that group; it is a symmetric indicator. The statistical significance of the species indicator values is evaluated using a randomization procedure. Contrary to Twinspan, our indicator index for a given species is independent of the other species relative abundances, and there is no need to use pseudospecies. The new method identifies indicator species for typologies of species relevés obtained by any hierarchical or nonhierarchical classification procedure; its use is independent of the classification method. Because indicator species give ecological meaning to groups of sites, this method provides criteria to compare typologies, to identify where to stop dividing clusters into subsets, and to point out the main levels in a hierarchical classification of sites. Species can be grouped on the basis of their indicator values for each clustering level, the heterogeneous nature of species assemblages observed in any one site being well preserved. Such assemblages are usually a mixture of eurytopic (higher level) and stenotopic species (characteristic of lower level clusters). The species assemblage approach demonstrates the importance of the “sampled patch size,” i.e., the diversity of sampled ecological combinations, when we compare the frequencies of core and satellite species. A new way to present species–site tables, accounting for the hierarchical relationships among species, is proposed. A large data set of carabid beetle distributions in open habitats of Belgium is used as a case study to illustrate the new method.

Keywords

Affiliated Institutions

• Université de Montréal CA
• UCLouvain BE

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