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Which is far from saying that taxonomic decision-making is completely arbitrary, either. Topography provides an excellent analogy, in which mountains, hills, and valleys are by no means purely mental constructs, even in the absence of sharp, non-arbitrary boundaries separating one from the other. The best framework for explaining the taxonomic decision-making process is that provided by fuzzy (vs. crisp) logic, pioneered by UC-Berkeley mathematician Lotfi Zadeh and now an integral part of computer technology. As summarized by McNeill and Frieberger (1993) in their popularized book on fuzzy logic, "Computers forced us to take crisp boundaries seriously, and when we went searching for them, we found they didn't exist and never had" (p. 100). As an alternative to elusive searches for rigorously precise definitions and demarcations where none exist, fuzzy logic provides a mechanism whereby classification results from the summation of multiple factors, any one of which can be relatively weak if counterbalanced by the strength of others.
Within this framework, I find that "taxonomic significance" at the species level results from the "fuzzy" summation of the following five factors, of which the first two are more-or-less directly observed, the second and third are generally inferred, and the fifth is somewhere in between:
Ertter, Barbara. 1993. Rosa. In: Hickman, J.C. (ed.) The Jepson manual: higher plants of California. University of California Press, Berkeley, CA, pp. 972--973.
McNeill, Daniel and Paul Freiberger. 1993. Fuzzy logic: the revolutionary computer technology that is changing our world. Touchstone edition, Simon & Schuster, Inc., New York, NY.