Theoretical Aspects of Numerical Identification

All identification processes are strictly probabilistic. Identification allocates initially unidentified operational taxonomic units (U-OTUs) to taxa contained in previously established classifications. Identification is therefore subject to a number of a priori conditions, such as the probabilistic nature of classifications, the manner in which classifications are made, the adequacy of classifications, and the adequacy of the set of characters describing U-OTUs. The advantages and disadvantages of continuous reclassification, incorporating U-OTUs, are discussed. Numerical identification is concerned with extracting from a classification a minimum, or near minimum, amount of information necessary to effect separation of all the taxa defined by the classification. Several strategies are available for achieving this-test reduction, OTU reduction, a combination of both of these, and key generation.