The most voluminous caldera-forming eruptions on Earth are related to silica-rich magma; however, no one has directly observed or recorded any such eruption, which may eject hundreds to thousands of cubic kilometers of volcanic material. The lack of direct observations creates considerable uncertainty about how these systems evolve and what the warning signs of a large eruption might be. Thus, scientists rely on a variety of indirect approaches to understand magmatic processes in these systems.
In January 2018, 79 scientists from 13 countries participated in an American Geophysical Union Chapman Conference about large silicic magma systems and their associated hazards. Fittingly, the conference took place near Laguna del Maule, a young, silica-rich volcanic center in Chile that exhibits active surface deformation. Participants included scientists at various career stages who have studied large silicic systems from various disciplinary perspectives, including geologic mapping, geophysics, structural geology, petrology, geochemistry, geochronology, and geodynamic modeling.
To address the fundamental question of how large silicic systems develop, presentations were organized into four main sessions:
- integration of geophysics, petrochronology, and numerical modeling
- reservoir dimensions and location(s) of melt
- growth and evolution of systems on long and short timescales
- interpreting signals of unrest to improve eruption forecasting
Each session comprised research from across disciplines to incorporate different perspectives on how large silicic systems operate. In this way, panel discussions focused on what is needed to create an integrative model that can explain these different observations.
Of course, the central question posed by this Chapman Conference could not be answered in a mere week. Instead, the interdisciplinary discussions that resulted from the presentations, often led by early-career scientists and students, provided a springboard for a new generation of collaborations and research.
An overarching conclusion from the conference is that cross-disciplinary collaboration is vital to developing an integrated model that will ultimately better represent the physical nature and dynamics of these systems. Several research needs stood out for their potential to lead to breakthroughs:
- understanding and communicating the physical representations of geophysical features and their associated uncertainty (e.g., understanding the geologic structure underlying the “big red blobs” commonly seen by geophysicists)
- understanding the relationship between geophysical observables (velocity, resistivity, density) and temperature and melt percentages in natural systems using new mineral physics and phase equilibria experiments, along with in situ scientific drilling
- gaining an integrated perspective of how large silicic systems operate at various timescales (from short term to millions of years) and spatial scales (from crystals to big red blobs) throughout the lithospheric column (Figure 1)
- developing integrated models that relate physical processes to the state of magmatic reservoirs, which will improve our ability to forecast future eruptions and will help to propel the science forward, which, in turn, can benefit society
A special online issue of the Journal of Geophysical Research: Solid Earth will focus on bridging the observations and scales inherent in individual disciplines to enhance our knowledge of large silicic magma systems. Researchers may submit manuscripts beginning in April 2018, and we strongly encourage submissions that focus on an interdisciplinary approach to these systems.
—Jonathan R. Delph (email: firstname.lastname@example.org), Department of Earth, Environmental and Planetary Sciences, Rice University, Houston, Texas; Brad S. Singer, Department of Geoscience, University of Wisconsin–Madison; and Josef Dufek, School of Earth and Atmospheric Sciences, Georgia Institute of Technology, Atlanta
Delph, J. R.,Singer, B. S., and Dufek, J. (2018), Geoscientists collaborate to understand silicic magma systems, Eos, 99, https://doi.org/10.1029/2018EO097577. Published on 02 May 2018.
Text © 2018. The authors. CC BY 3.0
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