The joint source-channel coding theorem (Shannon 1948), also known as source-channel separation theorem, shows that source coding and channel coding can be separated without influencing the other. If the channel capacity is strictly greater than source information entropy, noiseless communication can be achieved via sophisticated engineering. In practice, the information encoder is often engineered into decoupled source and channel encoders to serve different purposes as in Table 1.
Similarly, the differences between source coding and channel coding have been realized and practiced in many paleontological studies. From various studies including Nelson (1972) and Cracraft (1974), researchers have shown that the differences between classification (Linnaeus classification and its variants) and systematics (phylogenetic classification, evolutionary classification, evolutionary systematics, etc.). Harrison (1997) emphasized the necessity of separating classification, corresponding to source coding, and systematics, corresponding to channel coding, in paleontological systematic studies. This separation is actually automatically applied in paleontological systematic studies, especially studies reporting new taxa, in which the characterization of the new taxon needs only few diagnostic features, whereas subsequent systematic analysis requires many.
If every character has information entropy of 1 bit, \(n\) binary characters can classify \(2^{n}\) taxa in the ideal situation. Table 2 is an example character matrix including 9 taxa and 3 scored binary characters (0 means absence and 1 means presence of a structure) to illustrate the differences between source coding and channel coding in paleontological systematic studies.
Table 2. Example character matrix showing source coding