Quantitative analysis of crustal thickness evolution across past geological periods poses significant challenges but provides invaluable insights into the planet’s geological history. It may help uncover new areas with potential critical mineral deposits and reveal the impacts of crustal thickness and elevation changes on the development of the atmosphere, hydrosphere, and biosphere. However, a significant knowledge gap in reconstructing regional paleo-crustal thickness distribution is that most estimation proxies are limited to arc-related magmas. By mining extensive geochemical data from present-day subduction zones, collision orogenic belts, and non-subduction-related intraplate igneous rock samples worldwide, along with their corresponding Moho depths during magmatism, we have developed a machine learning-based mohometry linking geochemical data to Moho depth, which is universally applicable in reconstructing ancient orogenic systems’ paleo-crustal evolution and tracking complex tectonic histories in both spatial and temporal dimensions. Our novel mohometry model demonstrates robust performance, achieving an R² of 0.937 and RMSE of 4.3 km. Feature importance filtering highlights key geochemical proxies, allowing for accurate paleo-crustal thickness estimation even when many elements are missing. The mohometry validity is demonstrated through applications to southern Tibet, which has well-constrained paleo-crustal thicknesses, and the South China Block, which is noted for its complex tectonic evolution and extensive 800-km-wide Cretaceous extensional system. Additionally, the evolution of reconstructed paleo-crustal thickness, particularly in areas with anomalously thick crust, strongly correlates with porphyry ore deposits. These findings offer valuable insights for prospecting for new porphyry ore deposits, particularly in ancient orogens where significant surface erosion has occurred.

The mechanism of crustal recycling in subduction zones has been a heated debate, and Mg–Fe isotopes may provide new constraints for this debate. This study reported the Fe–Mg isotope data for mafic plutonic rocks from the eastern and central Gangdese arc and their associated trench sediments in southern Tibet. The δ26Mg (–0.32 to –0.20‰) and δ56Fe (0.04 to 0.12‰) values of the eastern Gangdese arc rocks show negative and positive correlations with (87Sr/86Sr)i and (206Pb/204Pb)i values, but positive and negative correlations with εNd(t) and εHf(t) values, respectively. The Mg and Fe isotopic compositions (δ26Mg = –0.28 to –0.15‰; δ56Fe = 0.02 to 0.12‰) of the central Gangdese arc rocks are comparable with the eastern ones, but they are not covariant with Sr–Pb–Nd–Hf isotopes. More importantly, the Fe–Mg isotopes for most of the arc rocks fall in between local trench sediments (δ26Mg = –0.61 to –0.30‰; δ56Fe = 0.00 to 0.17‰) and the normal mantle. Integrated qualitative analyses and quantitative simulations suggest that while the Mg–Fe isotope variations in the eastern Gangdese arc rocks revealed the important role of source mixing between sediment-derived melts and peridotite, their variations in the central Gangdese arc rocks reflected the controlling effects of source mixing between carbonated serpentinite-derived Mg-rich fluid and peridotite and source melting. The good covariant relationships between Mg–Fe isotope and traditional geochemical tracers provide further evidence for the recycling of crustal materials in subduction zones via various types of slab-derived fluids and melts.

In this study, we for the first time applied a joint geodynamic-geophysical inversion (JGGI) approach to oceanic plateau subduction models, and compared the subduction style and corresponding topography and Bouguer gravity of two representative subduction scenarios with passive or active collision. We showed that the case of passive collision of the Ontong Java Plateau (OJP) crust better explains the topography, gravity, and seismic data than the active collision scenario. This implies that the OJP did not control the regional dynamics during the collisional process. We conclude that previous studies may have overestimated the role of the OJP in triggering subduction initiation, subduction polarity reversal, and even Pacific Plate rotation.

It is generally accepted that the subduction polarity reversal (SPR) results from the strong collision of two plates. Yet, the SPR of the Solomon Back-arc Basin is started in the “soft docking” stage, and the mechanism by which the “soft docking” induced subduction initiation (SI) remains elusive. We find that the mass depletion of the plateau influences the evolution of the subduction patterns during SI. And the island arc rheological strength affects the development of the shear zone between an island arc and back-arc basin which favors SI. What’s more, with the increase of the rheological strength difference, the SI is more easily to occur, and the contribution of the plateau collision to SI weakens. Hence, by combining the available geological evidence, we suggest that the Solomon Island Arc rheological strength and the Ontong-Java plateau collision jointly controlled the SI during the “soft docking” stage.