This document discusses numerical taxonomy, which is the use of mathematical methods to group taxonomic units based on their characteristics. It defines key terms like phenetics and provides details on principles of numerical taxonomy like neo-Adansonian methods. The document outlines steps in classification, types of data used, and methods for numerical taxonomy including classic and clustering methods. It also discusses aims and applications of numerical taxonomy as well as merits and limitations.
4. Principles of
Numerical Taxonomy
CUST ISLAMABAD
Neo-Adansonian
• Content of information
• Weight of character
• Similarity between characters
• Recognition of distinct taxa
6. The Estimation
of Resemblance
CUST ISLAMABAD
• Collection of information
• Discovery or collection of
information
• Assignment of weight
• Measuring the resemblance
•
7. • Matrix of resemblance
• Computational methods
Construction of
Taxa
CUST ISLAMABAD
8. • Collection of data
• Data must be coded
• Similarity or resemblance
• Taxonomic structure
• Properties of the phenons can be
tabulated
Steps in
Classification
CUST ISLAMABAD
19. • Use of overall information
• uses intra-cluster information
• does not distorts this inform-
ation in any way
Improvements
of B Method
CUST ISLAMABAD
20. • Defining homogeneous clusters
• Integrating data of different
kinds
Aims of
Numerical Taxonomy
CUST ISLAMABAD
21. Attributes that an organism
possesses today
Similarity on
Observed Properties
CUST ISLAMABAD
22. Phylogeny of organisms, and not
necessarily to their present
attributes.
Relationship by
Ancestry
CUST ISLAMABAD
23. • Taxospecies (a cluster of strains of
high mutual phenetic similarity)
• Genospecies (a group of strains
capable of gene exchange)
Taxospecies
& Genospecies
CUST ISLAMABAD
24. • Nomenspecies (a group bearing
a binomial name whatever its status
in other respects)
• Genomospecies, a group of strains
that have high DNA-DNA
relatedness
Nomospecies
& Genomospecies
CUST ISLAMABAD
25. • Coding of reaction in to positive
negative form.
• give each character equal weight
• Adansonian
• Similarity and Matches
Coding of
Result
CUST ISLAMABAD
26. • Utilizes better and more number of
• described characters
• Sensitivity
• Reinterpretation
• Allows more taxonomic work
Merits of
Numerical Taxonomy
CUST ISLAMABAD
27. • Not for phylogenetic classification
• proponents of “biological” species
• Character selection
• Choose a procedure for
satisfactory results
Demerits of
Numerical Taxonomy
CUST ISLAMABAD
28. • Study of similarity and differences
in bacteria
• Delimitation of several angiospermic
genera
• Study of several other angiospermic
genera
Importance of
Numerical Taxonomy
CUST ISLAMABAD