A database of the ancient marbles of Göktepe near Aphrodisias is reported, and includes 160 white, black and bichrome samples from 13 quarries and two waste deposits. The quarries are grouped into four districts. Districts 1 and 2, to the north, produced exclusively black or dark grey marbles (nero antico). Districts 3 and 4 produced white statuary marble. Nero antico and a black and white stone were also quarried in district 4, where the black marble surfaces again. The samples were characterized using petrography, isotopic analysis, EPR spectroscopy and trace analysis. The Göktepe white exhibits an unparalleled combination of fine grain, low EPR intensity and high strontium concentration that often allows easy identification. The isotopic values are less distinctive and similar to those for Carrara. In most cases, however, they are tightly grouped and also quite indicative. The black marbles exhibit a much weaker metamorphic overprint. With respect to the white marbles, they show analytical similarities but also notable differences. Therefore, establishing their provenance can be more difficult and may require the support of petrographic analysis. The results suggest that the Göktepe marbles were among the most prized and widespread statuary marbles used in Roman times, particularly from the early second century AD onwards.
A multi‐method approach, based on petrography, stable isotope data and electron spin resonance spectroscopy for assigning the provenance of white marbles, is presented. A total of 11 experimental variables has been used, including the quantitative measurement of the sample colour and its homogeneity. On this basis we attempt to distinguish the three main quarrying basins of the Carrara district, that is, Torano, Miseglia and Colonnata. Such discrimination, extremely uncertain on the basis of the single techniques, may be performed with acceptable confidence’ using a properly selected subset of six petrographic, isotopic and spectroscopic variables. The final resubstitution and jackknifed re‐assignment rates are, respectively, 85% and 81%. Inclusion of the remaining five variables into the classification rule does not improve the results, but simply increases data overinterpretation. The practical possibility of using such an approach for more general provenancing problems is considered.
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