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Chemical discrimination of rutile from different metamorphic source rocks

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Rutile belongs to the group of ultra-stable minerals during processes of the sedimentary cycle, along with zircon and tourmaline. While detrital zircon mostly derives from felsic igneous rocks and tourmaline is hardly datable, rutile is mainly sourced from metamorphic rocks and routinely datable by U−Pb chronology. Thus, combining detrital rutile age information with trace-element based discrimination of different metamorphic source rocks has a high potential to gain time-resolved insights into the geodynamic evolution of the hinterland. However, trace-element based approaches are so far limited to (i) bivariate discrimination of mafic and felsic metamorphic source rocks by considering Cr and Nb concentrations (Zack et al. 2004a; Meinhold et al. 2008; Triebold et al. 2007, 2012), (ii) temperature information by considering Zr concentrations (e.g., Zack et al. 2004b; Kohn 2020) and assuming the same pressure conditions for all detrital grains, (iii) identification of fluid alteration based on e.g., W, Sn, V, Sb, Cr, Nb, Fe (Agangi et al. 2020; Pereira et al. 2021; Pereira & Storey 2023); and (iv) identifying very specific sources like mafic low-temperature/high-pressure rocks by considering H2O concentrations in combination with Zr, Nb, W, and Sn (Lueder et al. 2024).Here we compiled a dataset of 2,335 rutile trace-element analyses (16 elements) from 110 metamorphic rock samples of a wide range of pressure−temperature conditions. Using a modified version of the original random forest algorithm (Breiman 2001) for dealing with the hierarchically structured data, we trained three multivariate discrimination models. Under the assumption of a metamorphic source, the first model discriminates felsic and mafic rutile with a classification success rate of >90 %, which is a strong improvement compared to Cr versus Nb plots (72−86 % success on the same dataset). The second and third models discriminate rutile from rocks that formed under low and high temperature/pressure gradients (≤ 350 °C/GPa versus >350 °C/GPa) for felsic (>91 % success) and mafic rocks (>93 % success), respectively. We are currently integrating the three models to achieve a simultaneous prediction of composition and temperature/pressure gradients of the metamorphic source rock, taking rutile provenance analysis to a new level.
Title: Chemical discrimination of rutile from different metamorphic source rocks
Description:
Rutile belongs to the group of ultra-stable minerals during processes of the sedimentary cycle, along with zircon and tourmaline.
While detrital zircon mostly derives from felsic igneous rocks and tourmaline is hardly datable, rutile is mainly sourced from metamorphic rocks and routinely datable by U−Pb chronology.
Thus, combining detrital rutile age information with trace-element based discrimination of different metamorphic source rocks has a high potential to gain time-resolved insights into the geodynamic evolution of the hinterland.
However, trace-element based approaches are so far limited to (i) bivariate discrimination of mafic and felsic metamorphic source rocks by considering Cr and Nb concentrations (Zack et al.
2004a; Meinhold et al.
2008; Triebold et al.
2007, 2012), (ii) temperature information by considering Zr concentrations (e.
g.
, Zack et al.
2004b; Kohn 2020) and assuming the same pressure conditions for all detrital grains, (iii) identification of fluid alteration based on e.
g.
, W, Sn, V, Sb, Cr, Nb, Fe (Agangi et al.
2020; Pereira et al.
2021; Pereira & Storey 2023); and (iv) identifying very specific sources like mafic low-temperature/high-pressure rocks by considering H2O concentrations in combination with Zr, Nb, W, and Sn (Lueder et al.
2024).
Here we compiled a dataset of 2,335 rutile trace-element analyses (16 elements) from 110 metamorphic rock samples of a wide range of pressure−temperature conditions.
Using a modified version of the original random forest algorithm (Breiman 2001) for dealing with the hierarchically structured data, we trained three multivariate discrimination models.
Under the assumption of a metamorphic source, the first model discriminates felsic and mafic rutile with a classification success rate of >90 %, which is a strong improvement compared to Cr versus Nb plots (72−86 % success on the same dataset).
The second and third models discriminate rutile from rocks that formed under low and high temperature/pressure gradients (≤ 350 °C/GPa versus >350 °C/GPa) for felsic (>91 % success) and mafic rocks (>93 % success), respectively.
We are currently integrating the three models to achieve a simultaneous prediction of composition and temperature/pressure gradients of the metamorphic source rock, taking rutile provenance analysis to a new level.

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