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A Q B M

50
40
30 Color
20 index
10
0

Q

P
A P A

Figure 4. Modal data for 403 quartz-bearing plutonic rocks from the Sierra Nevada batholith, plotted on the quartz-alkali feldspar-plagioclase (QAP)
triangle and in a tetrahedron whose base is QAP and whose apex M represents mafic minerals. It is clear that the proportion of mafic minerals (color
index) increases dramatically away from the center of the QAP triangle, toward the QP sideline. This trend is neglected by the International Union of
Geological Sciences classification. Data from Bateman et al. (1984) and Bateman et al. (1988).
separation-by-name of closely related of classification. Noting an analogy described in the literature are covered by
rocks is an unfortunate consequence of between mineral assemblages and life just one or two dozen. We compiled the
fitting observations into arbitrarily assemblages, he said: number of citations in GeoRef mentioning
defined boxes. How artificial a classification of faunas 19 of the most common IUGS names over
Figure 3 also shows that the color indi- would be which was based on the ratio of the period 1970–2018. “Granite” made up
ces of rocks called El Capitan Granite foxes to hares, of hares to moles and so on! just under half of the total number of cita-
range from near zero to more than 20, an To be sure it is by no means accidental that tions (~223,000) in this list, and the names
important point to which the name “gran- the ratio of hares to foxes is 10 in a certain were distributed as in Figure 5. The first
area and only 2 in another, but as compared
ite,” as defined by the IUGS system, gives with the broad factors controlling life in the nine names account for 90% of the cita-
no indication. In general, color index two areas it is relatively accidental… So it is tions (allowing for multiple counting of
increases moving away from the center of not accidental that a rock is nearly pure oliv- citations listing more than one name).
the quartz-alkali feldspar-plagioclase ine here and only 75 per cent olivine a few As is common with textual data,
feet distant, but it is relatively accidental and
(QAP) triangle, toward plagioclase (Fig. should not be made a fundamental factor rock names roughly obey Zipf’s Law
4). The abundances and identities of the in classification. (Aitchison et al., 2016), which states that
mafic phases (e.g., biotite, hornblende, the frequency of a given word is inversely
titanite) are typically where the geochem- Bowen clearly recognized the problems proportional to its frequency rank. There
ical action is, and yet the IUGS classifica- inherent in classifications based on min- are ~50,000 rock names in the North
tion has no provision for this. eral proportions, and yet that is the sys- American Volcanic and Intrusive Rock
Thus, the current system of igneous rock tem with which we live. We contend that
nomenclature suffers from several short- an improved system could address the
troctolite
comings: (1) it conceals the variability of shortcomings of the IUGS system by: norite clinopyroxenite,
monzonite
igneous rocks at the map unit scale with • using a more restricted set of names, harzburgite } wehrlite,
websterite,
syenite
restrictive names; (2) it lacks important because restricting the subdivision of dunite gabbronorite,
lherzolite
information about the mineralogy of the names allows each name to encompass anorthosite orthopyroxenite
rocks at scales ranging from pluton to hand greater modal variation; tonalite
sample; (3) it is burdened by unnecessary • allowing for overlap between rock
names that, by themselves, tell nothing; categories; and granodiorite granite
and (4) the quantitative data used to derive • including quantitative information about gabbro
a name are largely discarded once the modal mineralogy at scales for which
name is applied. This last point must be quantification is appropriate. diorite
addressed if we are to move field observa-
tions from “dark data” (Heidorn, 2008), ROCK NAMES, NECESSARY peridotite
buried in field notebooks, into sharable AND SUPERFLUOUS
digital form (Walker et al., in press). There are thousands of igneous rock Figure 5. Frequency distribution of documents
Bowen (1928) foresaw the problems names (e.g., Johannsen, 1932, and accom- using the given rock names in the GeoRef data-
with using mineral abundances as a basis panying volumes), but most samples base, 1970–2018. The ten most common names
account for more than 90% of the citations.
6 GSA Today | February 2019