We present a new conceptual model for the interpretation of bedrock and detrital zircon data based on a comparison between theoretical α-damage inferred from U Pb data and actual α-damage measured by Raman analysis. The model is tested in the Cenozoic Adamello composite batholith in the Southern Alps (Italy), a natural laboratory where the progressive emplacement of successive magmatic bodies has thermally affected both the metamorphic country rocks and the previously emplaced igneous rocks under well-constrained geological conditions. Bedrock samples were collected along a traverse that spans the contact between plutons of different ages and their country rocks. We found that: (i) zircon rims from the Adamello batholith invariably show a complex, but consistent annealing history after crystallization, as induced by subsequent intrusion of younger plutonic bodies; (ii) zircon cores record damage accumulation starting from the age of rim crystallization; (iii) the severity of annealing in country rock zircons correlates with distance from the nearby plutons. Results on bedrock zircon are then exported to a synthetic detrital zircon population to test how the impact of reheating can be detected in detritus. We found that the application of our model allows increasing the resolution of provenance discrimination, providing a level of information approaching the evolution inferred from bedrock data. We conclude that an approach to detrital zircon geochronology complementing detrital U Pb ages with Raman spectroscopy could open new venues in sediment provenance analysis and could be proficiently used to improve the identification of clastic detritus sources. • New conceptual model for provenance studies based on zircon U Pb and Raman analysis. • The model compares theoretical and actual (Raman-based) α-damage in zircon. • Model tested on a multistage batholith formed under controlled geological conditions. • The impact of α-damage annealing can be detected in natural detrital zircon datasets. • Detrital zircon U Pb and Raman data shed new light on ancient geological landscapes.
Resentini et al. (Fri,) studied this question.