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Major tin (Sn) deposits within the Variscan orogen are closely related to 325–270 Ma postkinematic granites that intruded the metamorphic rocks of the former precollisional accretionary wedge of the Gondwana margin. In the Erzgebirge (Germany), some of these metasedimentary rocks have high Sn contents (locally more than 1000 ppm Sn). We report cassiterite (SnO2) U-Pb ages of 395–365 Ma and high Sn contents in prograde biotite in these metasedimentary rocks. These data demonstrate that Sn was already introduced into these rocks during accretion and prograde metamorphism. Mobilization of Sn from sedimentary source rocks during prograde fluid loss in a subduction-accretion setting represents an important process of pre-enrichment of sedimentary source rocks that upon partial melting may produce Sn-enriched melts. The large-scale metamorphic mobilization of Sn, documented here for the first time, highlights the possible importance of metamorphic Sn enrichment in accretionary complexes, thereby explaining the spatial distribution of major Sn districts within the Variscan orogen.

Self-organizing maps (SOM) are a useful tool to analyze and interpret gridded datasets like potential field or stream sediment geochemistry data. The data are transformed from geographic space to SOM space where they can be clustered according to overall similarity. By transforming the clusters back to geographic space, geological interpretation of the clusters is facilitated. We present the application of a multilayer perceptron (MLP) in SOM space to produce mineral predictive maps. The reduced number of grid cells in SOM space greatly enhances the performance of the MLP and the tolerance to noise in the input data, compared to an application of the MLP to the original data. The method is applied to tin skarn deposits in the German part of the Erzgebirge. The training and validation data required for the MLP are compiled from mining and exploration records. The input data for the SOM are reprocessed gravimetric, magnetic, stream sediment geochemistry, geologic and tectonic data sets. Potentially ore-controlling spatial relationships, such as the distance to different types of partly covered granite intrusions, are derived from a regional scale 3D geological model. The resulting mineral prediction map allows the definition of exploration zones for detailed studies.The paper has been compiled in the frame of "NEXT - New EXploration Technologies" project. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 776804.