The processes involved in the formation and storage of magma within the Earth’s upper crust are of fundamental importance to volcanology. Many volcanic eruptions, including some of the largest, result from the eruption of components stored for tens to hundreds of thousands of years before eruption1,2,3. Although the physical conditions of magma storage and remobilization are of paramount importance for understanding volcanic processes, they remain relatively poorly known4,5. Eruptions of crystal-rich magma are often suggested to require the mobilization of magma stored at near-solidus conditions6,7,8; however, accumulation of significant eruptible magma volumes has also been argued to require extended storage of magma at higher temperatures7,8,9. What has been lacking in this debate is clear observational evidence linking the thermal (and therefore physical) conditions within a magma reservoir to timescales of storage—that is, thermal histories. Here we present a method of constraining such thermal histories by combining timescales derived from uranium-series disequilibria, crystal sizes and trace-element zoning in crystals. At Mount Hood (Oregon, USA), only a small fraction of the total magma storage duration (at most 12 per cent and probably much less than 1 per cent) has been spent at temperatures above the critical crystallinity (40–50 per cent) at which magma is easily mobilized. Partial data sets for other volcanoes also suggest that similar conditions of magma storage are widespread and therefore that rapid mobilization of magmas stored at near-solidus temperatures is common. Magma storage at low temperatures indicates that, although thermobarometry calculations based on mineral compositions may record the conditions of crystallization, they are unlikely to reflect the conditions of most of the time that the magma is stored. Our results also suggest that largely liquid magma bodies that can be imaged geophysically will be ephemeral features and therefore their detection could indicate imminent eruption.
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Funding for this project was provided by the US NSF (EAR-0838389 to KMC; EAR-0838421 to AJRK). We thank W. Bohrson for assistance with R-MELTS and measurement of CSD. F. Costa also provided assistance with diffusion modelling. We thank T. Plank for comments that improved the clarity and content of the manuscript.
The authors declare no competing financial interests.
Extended data figures and tables
a, Results of a model calculation illustrating effects of multiple stages of crystallization on 238U–230Th (orange) and 230Th–226Ra (blue) apparent crystal ages. The model simulates multiple pulses of crystal growth at 10,000-year intervals, with ageing and radioactive decay occurring between the episodes. The model assumes that each increment of crystallization adds the same volume of new growth, and that each increment of new growth has the same initial concentrations of U, Th and Ra. The diagram shows the model time versus apparent age of the bulk crystal population. We note that only the first part of the model simulation, after a single pulse of crystallization, shows concordant apparent ages for the 238U–230Th and 230Th–226Ra parent–daughter pairs. b, Diagram modified from Cooper and Reid37, showing apparent 238U–230Th and 230Th–226Ra ages calculated for a mixed crystal population resulting from two crystallization episodes: one zero-age population and one older population (assuming constant U, Th and Ra in each crystallization episode). The apparent ages given by each parent–daughter pair and the magnitude of the discrepancy between apparent ages given by the two parent–daughter pairs are a function of the proportion of old and young crystals in the mixed population (dashed grey lines; numbers above lines indicate the percentage of old population) and the age of the old population (blue curves; numbers along curves indicate age in thousands of years of the old population).
Extended Data Figure 2 Measured anorthite mole fraction and Sr concentration in profiles across selected plagioclase crystals from sample MH-09-05.
Profiles representing 1,000 years residence at 750 °C (grey dashed lines), based on the R-MELTS estimate of initial Sr distribution are also shown. See Methods for more details and the source data table for this figure for measured data.
Extended Data Figure 3 Measured anorthite mole fraction and Sr concentration in profiles across selected plagioclase crystals from sample MH-09-11.
Profiles representing 1,000 years residence at 750 °C (grey dashed lines), based on the R-MELTS estimate of initial Sr distribution are also shown. Note that profile MH-09-11-1-9-tr1 has anorthite mole fractions that are too high to allow us to use the R-MELTS method to estimate Sr contents. See Methods for more details and the source data table for this figure for measured data.
Extended Data Figure 4 Backscattered electron images of plagioclase crystals analysed in this study.
Locations of measured profiles are marked with white lines marked ‘tr’ (for ‘traverse’).
Extended Data Figure 5 Sr versus anorthite mole fraction for plagioclase crystals analysed in this study.
Red lines indicate linear regression lines with correlation coefficients (r) indicated. See Methods for more explanation.
Extended Data Figure 6 Observed, R-MELTS-modelled, and equilibrium correlations of measured anorthite versus Sr, and example finite-difference results.
a, Measured anorthite versus Sr for all plagioclase from this study. The best-fitting linear regression line for all data are also shown (thin line with short dashes) as well as an example (thicker line with long dashes) of the equilibrium relation between Sr and anorthite mole fraction calculated for a melt containing 200 µg g−1 Sr at 750 °C. The thick dashed grey line shows Sr content predicted by R-MELTS modelling of the liquid line of descent at 200 MPa, from an initial liquid containing 350 µg g−1 Sr. b, Representative results of finite difference models for sample MH-09-11-1-2-tr1, showing the change in correlation coefficient (r) for Sr versus anorthite mole fraction at temperatures between 700 °C and 950 °C for residence times of 1 to 10,000 years. Also shown is the dashed black line representing the observed r value (rmeasured = 0.62) for Sr versus anorthite for this crystal. Thin grey lines along the 750 °C curve represent the results from evaluation of uncertainties for this curve following the procedure outlined in the Methods. Note that the straight dashed grey lines joining each point (representing calculations for 1, 10, 50, 100, 500, 1,000, 5,000 and 10,000 years) are to aid the viewer but do not imply that the curve joining adjacent points is linear in log-linear space.
Extended Data Figure 7 Example of finite difference modelling of diffusion for crystal traverse MH-09-11-1-1-tr2.
a, Example from crystal MH-09-11-1-1-tr2 of the slope m and correlation r for the best-fitting lines between anorthite and Sr from initial, measured and equilibrium values. Also shown are symbols and best-fitting lines for calculated residence times (at 750 °C) of 100, 1,000 and 10,000 years. b, Measured, initial and equilibrium profile for the same plagioclase crystal, also showing lines representing 1,000 and 10,000 years residence at 750 °C. All calculations were done using R-MELTS estimates of the initial Sr distribution.
Extended Data Figure 8 Crystal residence ages for the Mount Hood silicic plagioclase population calculated as a function of crystal growth rate.
Shown is the total crystal growth duration to produce the maximum observed crystal size (3 mm; green line) and the mean crystal residence time calculated based on CSD slopes (blue lines). Assuming plagioclase growth rates of 10−8 to 10−10 cm s−1 results in growth durations or mean residence times of months to centuries; see Methods for further discussion of growth rates. The percentage of the total time represented by these residence ages is calculated compared to the minimum age of the old cores (21,000 years) and is shown on the right vertical axis.
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Cooper, K., Kent, A. Rapid remobilization of magmatic crystals kept in cold storage. Nature 506, 480–483 (2014). https://doi.org/10.1038/nature12991
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