Numerical Taxonomy

Sanjeet Kumar

Numerical Taxonomy

The classification of Taxonomic units into various groups by numerical methods is called “Numerical Taxonomy”. The publication of pioneer work of Sokal and Sneath (1963) “Principle of Numerical Taxonomy” was the first comprehensive exposition in this regard. Since then, there has been a very rapid increase in the development of methods dealing with numerical taxonomy as well as their outstanding applications for the cause of this new aid to plant taxonomy.
 
It is a classification system in biological systematic which deals with the grouping by numerical methods of taxonomic units based on their character states. It aims to create a taxonomy using numeric algorithms like cluster analysis rather than using subjective evaluation of their properties. Robert R. Sokal and Peter H. A. Sneath in 1963, they divided the field into phenetics in which classifications are formed based on the patterns of overall similarities and cladistics in which classifications based on the branching patterns of the estimated evolutionary history of the taxa. Note: in recent years many authors treat numerical taxonomy and phenetics as synonyms despite the distinctions made by those authors. Although intended as an objective classification method, in practice the choice and implicit weighing of characteristics is, of course, influenced by available data and research interests of the investigator.
 
What was made objective was the introduction of explicit steps to be used to create phenograms and cladograms using numerical methods rather than subjective synthesis of data As a matter of fact, numerical taxonomy is primarily based on phenotypic evidence rather than on supposed phylogeny. Then, it is divided into a number of repeatable logical steps. The lowest ranking taxa in any particular study are called as operational taxonomic units (OTU’s). These basic units could be treated as an individual or supra-individual category such as species, genus or even higher ranked taxa.
 
 A sufficiently large number of suitable characters of OUT’s are selected in a regular manner. It is usually recommended that not less than 50 characters should be used and where feasible considerably more characters should be employed. The value of similarity coefficient becomes more stable with the increase in the number of characters sampled. It is suggested that taxonomic characters should be selected from all parts and all stages of the life cycles and all characters varying within the group studied should be used. Characters capable of expression as binary, qualitative multi state or quantitative multistate data are generally used while studying this numerical taxonomy. Binary characters are to possess two contrasting states, such as the presence or absence of some specific features ego presence or absence of spine or any other contrasting alleles of single character i.e. fruits being dehiscent or indehiscent.

 

Comments

Popular posts from this blog

Bryophytes: Amphibians of the Plant Kingdom

List of Medicinal Plants in Ekamravana, Bhubaneshwar

Important plant diseases with special reference to Bihar and Jharkhand