When a continent collides with an island arc or other continent, continental crust of the subducted continent may be buried to depths exceeding 100 km, and exposed to pressures that can cause formation of coesite and diamond. This process leads to substantial density increase in SiO₂-rich rocks and, in turn, to a reduction of the buoyancy of the subducted material, which should inhibit exhumation. Nevertheless, coesite- and diamond-bearing continental crustal rocks are known from several occurrences worldwide. We report on the discovery of microdiamond in kyanite-garnet gneiss from allochthonous metasediments of the Seve Nappe Complex in the Scandinavian Caledonides. Our discovery calls for general reconsideration of existing exhumation models of deeply subducted continental crust. We propose that the diamond-bearing rocks were subducted in an arc-continent collision setting, and their exhumation was facilitated by local pressure reduction resulting from extraction of the forearc lithospheric block.

Identifying the data structure including trends and groups/clusters in geochemical problems is essential to discuss the origin of sources and processes from the observed variability of data. An increasing number and high dimensionality of recent geochemical data require efficient and accurate multivariate statistical analysis methods. In this paper, we show the relationship and complementary roles of k‐means cluster analysis (KCA), principal component analysis (PCA), and independent component analysis (ICA) to capture the true data structure. When the data are preprocessed by primary standardization (i.e., with the zero mean and normalized by the standard deviation), KCA and PCA provide essentially the same results, although the former returns the solution in a discretized space. When the data are preprocessed by whitening (i.e., normalized by eigenvalues along the principal components), KCA and ICA may identify a set of independent trends and groups, irrespective of the amplitude (power) of variance. As an example, basalt isotopic compositions have been analyzed with KCA on the whitened data, demonstrating clear rock type/tectonic occurrence/mantle end‐member discrimination. Therefore, the combination of these methods, particularly KCA on whitened data, is useful to capture and discuss the data structure of various geochemical systems, for which an Excel program is provided.

Pumice rafts that arrived at the Nansei Islands, Japan, provided a unique opportunity to investigate the Fukutoku‐Oka‐no‐Ba (FOB) eruption of August 2021. Despite drifting for 2 months for ~1300 km, the drift pumice raft had a large volume and contained a variety of pumice clasts, some of which were deposited during a high tide in a typhoon, while others were washed up on a sandy beach. Most of the drift pumice clasts are gray in color, vesicular, and have a groundmass containing black enclaves. Rare black pumice and the main gray pumice components have similar trachytic compositions, with SiO₂ = 61–62 mass% and total alkalis = 8.6–10 mass% (on an anhydrous basis). Both pumice types contain clinopyroxene, plagioclase, and rare olivine phenocrysts. Thin‐section observations show that the gray pumice has more elongated vesicles as compared with the black pumice that has spherical vesicles, even where the two types of pumice are in the same clast. The glass in the black pumice is transparent and brown in color, while that in the gray pumice is colorless. No micro or nano‐crystals were observed during electron and optical microscopy. Raman spectra of the brown‐colored glass exhibit a clear magnetite peak, suggesting magnetite nanolites cause the brown color. High‐Mg olivine in the black pumice has an equilibrium temperature of c. 1200 °C and a rim diffusion profile indicative of re‐equilibration with the surrounding melt over a period of hours to days. The textural relationships between the gray and black pumice suggest that the black pumice had become black and viscous before the two types of pumice mixed. Therefore, crystallization of magnetite nanolites and a corresponding increase in melt viscosity were important in the eruption preparation process, which then resulted in a large‐scale Plinian eruption.