NUMERICAL TAXONOMY

 NUMERICAL TAXONOMY

·      Numerical Taxonomy is the mathematical method of classifying organisms with the help of Numerical methods. This method clarifies and illustrates the degree of relationship among the organisms in an unbiased manner (neutral manner without showing any partialities).

·     In Numerical Taxonomy, the organisms are arranged in their respective Taxa based on the Similarities and Differences. So, nowadays Numerical Taxonomy is a very important in Modern Systematics.

History of Numerical Taxonomy

·       In the period of 1957 to 1961, a French Botanist Michel Adanson planned to assign Numerical values to the similarities between organisms and he proposed that equal weightage should be given to all the characters while classifying plants. He used as many characters as possible for the classification, and these classifications came to be known as Adansonian classifications.

·       Later, Robert R. Sokal and Peter H. A. Sneath in 1963 divided the field into two categories

a)     Phenetics or Taximetrics – Based on Overall similarity.

b)    Cladistics - Based on temporal relation among various evolutionary history of the Taxa.

·       Numerical taxonomy was largely developed and popularized by Sneath and Sokal.

Arrangement of Organisms based on Numerical Taxonomy

·    In Numerical Taxonomy, organisms are compared on the basis of a large number of characteristics (traits). Organisms with a high proportion of characteristics in common are presumed to be closely related (Figure – 1).  

ü  Characteristics such as reaction to Gram staining, oxygen requirements, presence or absence of a capsule, properties of nucleic acids and proteins, and the presence or absence of particular enzymes and chemical reactions can be evaluated.

ü  Organisms are then compared, and patterns of similarities and differences are detected.

ü  With the use of Numerical Taxonomy, no single characteristic is used to arbitrarily divide all organisms into groups. If two organisms match on 90 % or more of the characteristics studied, they are presumed to belong to the same species.

Figure – 1: A probable Evolutionary Tree, arrived at by Numerical Taxonomy

·  Computerized Numerical Taxonomy offers great promise for improving our understanding of relationships among all organisms.

Two Aspects of Numerical Taxonomy

a)     Construction of taxonomic groups

ü  Individuals are selected and their characters are spotted.

ü  Larger the number of characters better is the approach.

ü  Then resemblances among the individuals are then established on the basis of character analysis.

b)     Discrimination of taxonomic groups

ü  When the taxonomic groups chosen for the study show overlapping of characters, discrimination (difference) should be used to select them.

Seven Principles of Numerical Taxonomy by Sneath and Sokal

a)     The greater the content of information in the taxa, and more the characters taken into consideration, the better a classification system will be.

b)     Every character should be given equal weightage in creating new taxa.

c)     For comparison purpose, the similarity between any 2 entities is considered.

d)    If Correlation (relationship) of characters differs in the groups of organisms under study. Thus, distinct taxa can be recognized.

e)   Phylogenetic conclusions can be drawn from the Taxonomic structure of a group and from character correlations, assuming some evolutionary mechanisms and pathways.

f)      The science of taxonomy is viewed and practiced as an empirical (experience) science.

g)     Phenetic similarity (Overall similarity) is the basis of classifications. 

Applications of Numerical Taxonomy

a)  Numerical Taxonomy can be successfully used in the study of various Angiospermic genera like Apocynum, Chenopodium, Crotalaria, Cucurbita, Oenothera, Salix, Zinnia, Wheat cultivars, Maize cultivars, etc.

b)     With the help of numerical taxonomy similarities and differences in bacteria, other microorganisms can be studied.

c)   Phytochemical data from seed Protein and Mitochondrial DNA RFLP studies (Restriction Fragment Length Polymorphism - A type of polymorphism [many forms] that results from variation in the DNA sequence recognized by Restriction enzymes) has been numerically analyzed to study the interspecific variations.

Advantages of Numerical Taxonomy

a)    The data of Conventional Taxonomy (normal taxonomic methods) is improved by Numerical Taxonomy as it utilizes better and more number of described characters.

b)     As numerical methods are more sensitive in delimiting taxa, the data obtained can be efficiently used in the construction of better keys and classification systems.

c)     Many existing biological concepts have been reinterpreted in the light of Numerical Taxonomy.

d)     Numerical Taxonomy allows more taxonomic work to be done by less highly skilled workers.

Disadvantages of Numerical Taxonomy

a)  The Numerical Taxonomy methods are useful in Phenetic classifications and not Phylogenetic classifications.

b)    Character selection is the greatest disadvantage in this approach. If characters chosen for comparison are inadequate, the statistical methods may give less satisfactory solution.

c)   Different Taxonometric procedures may yield different results. A major difficulty is to choose an apt procedure for the purpose and the number of characters needed in order to obtain satisfactory results by these mechanical aids.