Paper No. 44-5
Presentation Time: 3:05 PM
EMPLOYING CRYSTAL ZONATION TO QUANTIFY ERUPTION INITIATION MECHANISMS
One of the biggest challenges in volcano science today is better understanding the ultimate driving forces for eruptions, as well as their precursory signals. Crystal zonation offers a valuable window to the pre-eruptive magmatic processes, as crystal zones reflect abrupt changes in temperature, pressure, and composition often associated with eruption initiation mechanisms. For example, magma recharge or rejuvenation produce an injection of new molten material into a shallow crustal magma storage region with sufficient compositional contrast to produce sharp intracrystalline zones in the phenocryst cargo. Reverse phenocryst zoning is often used to evoke magma recharge as an eruptive initiation mechanism, yet the rate and efficacy of magma recharge prior to eruption in a variety of types of magmatic systems is poorly constrained. To quantify the frequency and efficacy of magma recharge, we have developed an image processing code that automates the identification of individual recharge events recorded as sharp compositional contrasts in phenocrysts using compositional-related crystal imagery such as BSE images. By analyzing hundreds of crystals from a given eruption, this method aims to analyze a statistically significant number of crystals to determine the number of recharge events recorded per crystal, as well as the overall distribution of recharge events in the crystal record of a particular eruption. As a test case we apply the code to the crystal cargo from a sample of the Mount St. Helens (WA, USA) 1980 cryptodome, where sharp intracrystalline zones are observed in the phenocryst cargo. We find that the plagioclase crystals record up to 17 magma injection events prior to eruption. These results can be set in time by comparing them to radiometric crystal ages or to diffusion chronometry on representative crystals and zones. The distribution of magma injection events from our code also provides a larger framework for interpreting results from intracrystalline diffusion chronometry and volcano monitoring data leading up the eruption, thereby working toward linking petrologic processes and eruption forecasting models.