Using Volatile Element Concentration Profiles in Crystal‐Hosted Melt Embayments to Estimate Magma Decompression Rate: Assumptions and Inherited Errors

Abstract

Volcanic eruption style is modulated by the process of volatile (e.g., H 2 O, CO 2 ) exsolution from ascending magma. Volatile exsolution efficiency strongly depends on composition, namely the degree of melt polymerization (e.g., Cassidy et al., 2018;Mangan et al., 2004). Highly polymerized melts, such as rhyolites, can inhibit volatile exsolution, a phenomenon typically not observed in less polymerized melts, such as basalts. However, kinetic processes can impact volatile exsolution and impact eruption style. For example, fast decompression rates can promote Plinian basaltic eruptions (e.g., Lloyd et al., 2014;Sable et al., 2006), while slow decompression rates can result in effusive rhyolitic eruptions (e.g., Castro et al., 2013;

Implications of Multiple Disequilibrium Textures in Quartz-Hosted Embayments

“…Morphologies were classified into five categories: simple, bulbous, bent, hourglass, and complex (Figure 3, Figure 4). Simple embayments are those ideal for embayment speedometry with near-perfect cylindrical geometry and little to no tapering of the outlet (Liu et al, 2007;deGraffenried and Shea, 2021). Bulbous embayments display a neck that tapers towards the outlet, extending from a rounded interior.…”

“…Successful modeling requires dense, glassy embayments, unmarred by bubbles or microlites. Simple shapes are also required for current models (deGraffenried and Shea, 2021). These requirements for geospeedometry may have resulted in a presumptive overrepresentation of the description of bubble-free embayments in the literature.…”

Are We Recording? Putting Embayment Speedometry to the Test Using High Pressure‐Temperature Decompression Experiments

“…Glass-coated quartz crystals were picked from the 500-1,000 μm size fraction of ashfall unit F9 of the 0.76 Ma Bishop Tuff, known to have abundant glass-filled embayments (Myers et al, 2018). Selected crystals were inspected with a stereo microscope for identification of glassy embayments with simple, cylindrical geometries (i.e., roughly uniform diameter from embayment interior to outlet) to justify the assumption of one-dimensional (1D) diffusion (deGraffenried & Shea, 2021). Embayments of different widths and lengths were selected in order to examine how natural variations in embayment dimensions within a single experiment might affect recovered decompression rates and/or textures (Table S2 in Supporting Information S2).…”

“…This has been interpreted to suggest an initial period of slow decompression that allows for re‐equilibration of the embayment interiors to lower concentrations prior to more rapid decompression approaching fragmentation (Myers et al., 2018). Additionally, although equilibrium degassing during decompression is a commonly applied boundary condition in embayment modeling, prior decompression experiments have emphasized the role of delayed, disequilibrium degassing, especially in high silica rhyolitic melts (Mangan & Sisson, 2000) and recent numerical studies have revealed the significant effect that the assumption of degassing mechanism can have on calculated decompression rates (deGraffenried & Shea, 2021). Lastly, order‐of‐magnitude variations in decompression rates within single ashfall units have been observed, and are thought to represent variable flow in the conduit or fluctuations in ascent dynamics experienced over the course of a single eruption (Myers et al., 2018; Saalfeld et al., 2022).…”

“…The embayment speedometer has been leveraged in explosive eruptions spanning a broad compositional range, with studies on rhyolite to rhyo‐dacite (Geshi et al., 2021; Humphreys et al., 2008; Liu et al., 2007; Myers et al., 2018, 2021; Saalfeld et al., 2022) as well as basaltic‐andesite to basalt (Ferguson et al., 2016; Lloyd et al., 2014; Moussallam et al., 2019; Newcombe et al., 2020; Zuccarello et al., 2022) providing insights into how magma decompression rate may (or may not) correlate with eruption composition and explosivity (Figure 1). However, attempts to model volatile concentration gradients in embayments have seen variable success, likely a result of complex magma decompression histories being met with simplifying model assumptions (deGraffenried & Shea, 2021; Su & Huber, 2017). For example, several studies have found that embayments often preserve interior H 2 O ± CO 2 concentrations and corresponding saturation pressures lower than those of co‐erupted melt inclusions, with the use of melt inclusion‐derived storage pressures therefore in some cases unsuccessful in producing good model fits to the observed concentration gradients (Lloyd et al., 2014; Myers et al., 2018, 2021; Saalfeld et al., 2022).…”