Morphometrics are fundamental for statistical analyses of fossils, particularly because soft parts or DNA are rarely preserved and thus hard parts such as shells are commonly the only source of information. Geometric morphometrics i.e. landmark analysis has been successfully established but exhibits a couple of shortcomings. On the one hand landmarking is rather subjective and on the other hand the application at the level of micro-sculpture is difficult.

With the aid of high-resolution 3D scanning technology and analyses of fractal dimensions, we test whether shortcomings of linear and geometric morphometrics can be overcome. As a model group, we selected a clade of modern viviparid gastropods from Lake Lugu, the shells of which show a high degree of sculptural variation. Linear and landmark analyses were applied to the same shells, in order to root the fractal dimensions. The genetic diversity of the gastropod clade was basically assessed.

The genetic results suggest that the gastropod clade represents a single species. The results of all morphometric methods applied are in line with the genetic results, which is that no clustering of morpho-types occurs. Apart from this overall agreement, landmark and fractal dimension analyses do not correspond with each other but represent data sets with different information. Generally, the fractal dimension values quantify the roughness of the shell surface, the resolution of the 3D-scans determining the level. In our approach, we captured the micro-sculpture but not the first-order sculptural elements, which explains that fractal dimension and landmark data are not in phase.

We can show that analyzing fractal dimensions of gastropod shells opens a window to more detailed information that can be considered in evolutionary and ecological contexts. We propose that using 3D-scans with a low resolution may successfully substitute landmark analyses because it overcomes the subjective landmarking. Analyses of 3D-scans with higher resolution than used in this study will provide surface roughness information at the mineralogical level. We suggest that fractal dimension analyses of a combination of differently resolved 3D-models will significantly improve the quality of shell morphometrics.

See Wiese et al., 2022