Dynamic Magma Evolution E-Book
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- Herausgeber: John Wiley & Sons
- Kategorie: Wissenschaft und neue Technologien
- Serie: Geophysical Monograph Series
- Sprache: Englisch
Explores the complex physico-chemical processes involved in active volcanism and dynamic magmatism Understanding the magmatic processes responsible for the chemical and textural signatures of volcanic products and igneous rocks is crucial for monitoring, forecasting, and mitigating the impacts of volcanic activity. Dynamic Magma Evolution is a compilation of recent geochemical, petrological, physical, and thermodynamic studies. It combines field research, experimental results, theoretical approaches, unconventional and novel techniques, and computational modeling to present the latest developments in the field. Volume highlights include: * Crystallization and degassing processes in magmatic environments * Bubble and mineral nucleation and growth induced by cooling and decompression * Kinetic processes during magma ascent to the surface * Magma mixing, mingling, and recharge dynamics * Geo-speedometer measurement of volcanic events * Changes in magma rheology induced by mineral and volatile content The American Geophysical Union promotes discovery in Earth and space science for the benefit of humanity. Its publications disseminate scientific knowledge and provide resources for researchers, students, and professionals.
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Table of Contents
Cover
Title Page
Copyright Page
CONTRIBUTORS
PREFACE
Part I: Timescales and Time Sensor
1 Rates and Timescales of Magma Transfer, Storage, Emplacement, and Eruption
1.1. INTRODUCTION
1.2. METHODS AND TECHNIQUES FOR ESTIMATION OF RATES AND TIMESCALES
1.3. MECHANISMS, RATES, AND TIMESCALES OF MAGMA EMPLACEMENT, STORAGE, AND MIGRATION
1.4. CONCLUSIONS AND OUTLOOK
ACKNOWLEDGMENTS
REFERENCES
2 Boundary‐Layer Melts Entrapped as Melt Inclusions? The Case of Phosphorus‐ and CO
2
‐Rich Spinel‐Hosted Melt Inclusions from El Hierro, Canary Islands
2.1. INTRODUCTION
2.2. SAMPLES AND METHODS
2.3. RESULTS AND DISCUSSION
2.4. CONCLUSIONS
ACKNOWLEDGMENTS
SUPPLEMENTARY MATERIAL
REFERENCES
3 Apatite as a Monitor of Dynamic Magmatic Evolution at Torfajökull Volcanic Center, Iceland
3.1. INTRODUCTION
3.2. GEOLOGICAL BACKGROUND
3.3. METHODS
3.4. RESULTS
3.5. DISCUSSION
3.6. CONCLUSIONS AND IMPLICATIONS
ACKNOWLEDGMENTS
SUPPLEMENTARY MATERIAL
REFERENCES
4 Control of Magma Plumbing Systems on Long‐Term Eruptive Behavior of Sakurajima Volcano, Japan: Insights from Crystal‐Size‐Distribution Analysis
4.1. INTRODUCTION
4.2. BACKGROUND
4.3. CSD ANALYSIS
4.4. DISCUSSION
4.5. CONCLUSIONS
ACKNOWLEDGMENTS
REFERENCES
Part II: Physical Properties in Magma
5 Dynamics of Volcanic Systems: Physical and Chemical Models Applied to Equilibrium Versus Disequilibrium Solidification of Magmas
5.1. INTRODUCTION
5.2. MAGMAS AT CRUSTAL DEPTHS
5.3.
P–T–t
PATHS DURING MAGMA ASCENT AND EMPLACEMENT
5.4. PHYSICAL PROPERTIES OF MAGMAS
5.5. MAGMA ASCENT AND ERUPTION
5.6. TEXTURES
5.7. KINETICALLY CONTROLLED CATION EXCHANGES IN CLINOPYROXENE AND PLAGIOCLASE
5.8. CLINOPYROXENE DISEQUILIBRIUM GROWTH
5.9. PLAGIOCLASE DISEQUILIBRIUM GROWTH
5.10. ASSESSMENT OF EQUILIBRIUM AND ESTIMATE OF
P
–
T
–H
2
O CRYSTALLIZATION CONDITIONS
5.11. THE IMPORTANCE OF MODEL CALIBRATION TO RETRIEVE THE INTENSIVE VARIABLES OF MAGMA
5.12. THE COMPLEXITY OF CLINOPYROXENE SECTOR ZONING
5.13. CONCLUSIONS
ACKNOWLEDGMENTS
REFERENCES
6 Architecture of the Magmatic System in the Main Ethiopian Rift
6.1. INTRODUCTION
6.2. METHODOLOGY
6.3. RESULTS AND DISCUSSION
6.4. TOWARDS A VOLCANOLOGICAL MODEL
ACKNOWLEDGMENTS
SUPPLEMENTARY MATERIAL
REFERENCES
7 Rheological Behavior of Partly Crystallized Silicate Melts Under Variable Shear Rate
7.1. INTRODUCTION
7.2. STARTING MATERIALS
7.3. EXPERIMENTAL AND ANALYTICAL METHODS
7.4. RESULTS
7.5. DISCUSSION
7.6. CONCLUSION
ACKNOWLEDGMENTS
REFERENCES
8 Investigating the Crystallization Kinetics Via Time‐Resolved Neutron Diffraction
8.1. INTRODUCTION
8.2. NEUTRON DIFFRACTION
8.3. A CASE STUDY: ISOTHERMAL CRYSTALLIZATION IN SUPERCOOLED GeO
2
8.4. POSSIBLE FRAMEWORKS FOR DATA INTERPRETATION
8.5. CONCLUSIONS
ACKNOWLEDGMENTS
REFERENCES
9 Axial Melt‐Lens Dynamics at Fast Spreading Midocean Ridges
9.1. INTRODUCTION
9.2. FOSSILIZED AML FROM FAST SPREADING MIDOCEAN RIDGES: INSIGHTS INTO MAGMATIC AND HYDROTHERMAL PROCESSES
9.3. IODP LEGACY DRILLING AT SITE 1256: FIRST PENETRATION OF AN INTACT DIKE/GABBRO BOUNDARY
9.4. MAGMATIC EVOLUTION WITHIN AML
9.5. FELSIC MELT GENERATION WITHIN AML
9.6. MAGMATIC PROCESSES AT THE AML ROOF
9.7. THE TRANSITION FROM MAGMATIC TO METAMORPHIC PROCESSES: THE ROLE OF HYDROTHERMAL FLUIDS
9.8. CONSTRAINTS ON TIMESCALES FOR THE VERTICAL FLUCTUATIONS OF THE AML
ACKNOWLEDGMENTS
SUPPLEMENTARY MATERIAL
REFERENCES
Index
End User License Agreement
List of Tables
Chapter 1
Table 1.1 Principles, Benefits, Limits, and Uncertainties of Methods and Tech...
Table 1.2 Review of the Ascent Velocities from Mid‐ to Deep‐Crustal Levels as...
Table 1.3 Review of Ascent Velocities from Shallow Reservoirs for Different V...
Table 1.4 Summary of Timescales of Open Magmatic System Experiencing Magma Re...
Chapter 2
Table 2.1 Input Parameters in Diffusion Calculations of Boundary‐Layer Melt
Chapter 3
Table 3.1 Sample Names, Locations, and Ages
Table 3.2 Average Major and Volatile Element Compositions of Torfajökull Glas...
Table 3.3 Representative Analyses of Torfajökull Apatites (25th, 50th, and 75...
Chapter 4
Table 4.1 Summary of Plagioclase Phenocryst CSD Analyses and Textural Data fo...
Chapter 5
Table 5.1 Parameters used for the Two‐Dimensional Model of Heat Transfer
Table 5.2 Chemical Compositions (wt%) of Basalt and Rhyolite used for all the...
Table 5.3 Input Data for the H
2
O Solubility Model of Papale et al. (2006)
Table 5.4 Simulated ΔP/Δt Rates and Related Velocity Values
Table 5.5 Data Input for Viscosity and Density Modeling of B
100
and R
100
Magm...
Chapter 6
Table 6.1 Bulk Composition for Selected Rock Samples
Table 6.2 Chemical Data of Selected Clinopyroxenes
Table 6.3 Modal composition for both analyzed major and trace elements
Chapter 7
Table 7.1 Starting and Residual Melt (RM) Compositions Representing an Averag...
Table 7.2 Experimental Conditions and Results of Melts Viscosity Measurements...
Table 7.3 Experimental Conditions and Results of the Apparent Viscosity Measu...
Chapter 8
Table 8.1 Summary of the Main Properties of X‐Rays and Neutrons as a Probe fo...
Chapter 9
Table 9.1 Mineral Compositions of Two Samples from the Dike–Gabbro Contact at...
Table 9.2 Compilation of Studies Reporting Oceanic Plagiogranite from Current...
List of Illustrations
Chapter 1
Figure 1.1 Number of manuscripts published from 1980 to 2018 containing the ...
Figure 1.2 Simplified scheme of a mush‐dominated volcanic plumbing system de...
Figure 1.3 Range of timescales that can be determined using the reported ana...
Figure 1.4 Dike ascent velocities (m s
−1
) obtained by the (a) buoyancy...
Figure 1.5 Pressure–temperature diagram showing liquidi of andesitic melts t...
Figure 1.6 Summary of rates and timescales of magma transfer, storage, empla...
Chapter 2
Figure 2.1 Spinel textures in the El Hierro basanite. All panels but (d) (re...
Figure 2.2 Composition of spinel macrocrysts (Macro; squares), microlites (M...
Figure 2.3 Major element composition of spinel‐hosted melt inclusions (MI‐sp...
Figure 2.4 Primitive‐mantle normalized (McDonough & Sun, 1995) multielement ...
Figure 2.5 Volatile and volatile/lithophile element systematics of spinel‐ho...
Figure 2.6 Backscattered electron images and Si and Fe intensity line scans ...
Figure 2.7 Synentrapment and postentrapment modification scenarios for spine...
Figure 2.8 Comparison of diffusion coefficients for Si (Lesher et al., 1996)...
Figure 2.9 Slow‐diffuser/fast‐diffuser ratios as a function of melt‐inclusio...
Figure 2.10 Primitive‐mantle normalized (McDonough & Sun, 1995) trace elemen...
Figure 2.11 Modeling of boundary‐layer‐melt composition in front of a growin...
Figure 2.12 Cracking threshold estimates as a function of size and host mine...
Figure 2.13 Behavior of halogens. (a) Most spinel‐hosted melt inclusions hav...
Chapter 3
Figure 3.1 Geologic map of Iceland. Torfajökull is located in southern Icela...
Figure 3.2 Geologic map of Torfajökull volcano, showing the distribution of ...
Figure 3.3. Example thin‐section photographs of eruptive units IETHB and ITH...
Figure 3.4 Evaluation of the EPMA apatite data. The P/Ca apfu ratios of the ...
Figure 3.5 Major elements and volatiles in bulk rock samples and matrix glas...
Figure 3.6 Apatite halogen ternary plot showing F, Cl, and OH compositions o...
Figure 3.7 Sulfur evolution in Torfajökull apatites as a function of Cl cont...
Figure 3.8 Rare‐earth‐element contents and evolution in apatite. (a) Scatter...
Figure 3.9 Substitution mechanisms for REEs in apatite. Scatterplots display...
Figure 3.10 Sulfur contents in the matrix glasses compared to sulfide solubi...
Figure 3.11 Estimation of the S contents in the matrix glasses based on Torf...
Figure 3.12 Histograms of the S contents in apatite. (a) 1477 CE unit (ITN);...
Figure 3.13 Degassing trends recorded by apatite and melt inclusions in the ...
Chapter 4
Figure 4.1 (a)Location of Sakurajima Volcano. (b) Geological map of Sakuraji...
Figure 4.2 Compositional distributions of clear plagioclase at both cores an...
Figure 4.3 Representative backscattered electron images of type A–C plagiocl...
Figure 4.4 Example of color maps for the crystal size distribution analyses ...
Figure 4.5 Crystal size distribution (CSD) for (upper panel) type A and (low...
Figure 4.6 A model of the magma plumbing system of Sakurajima volcano since ...
Figure 4.7 Correlation between discharge rates and slopes of CSD of high An ...
Chapter 5
Figure 5.1 Simulations of cooling conditions of a sill 1 km thick, located a...
Figure 5.2 Simulations of cooling conditions of a sill 100 m thick, located ...
Figure 5.3 Simulations of cooling conditions of a dike 20 m wide intruded fr...
Figure 5.4 Simulations of cooling conditions of a lava flow 1 m thick. Condu...
Figure 5.5 Modeling data for the solubility of H
2
O in B
100
and R
100
magmas a...
Figure 5.6 Viscosity (top panels) and density (bottom panels) modeling data ...
Figure 5.7 Estimates of magma ascent velocities for (a) B
100
and (b) R
100
as...
Figure 5.8 BSE‐SEM microphotographs showing the textural features of (left) ...
Figure 5.9 (a) Al
2
O
3
, TiO
2
, and FeO in the melt next to the advancing crysta...
Figure 5.10 (a)
K
Fe
,
K
Ti
, and
K
Na
measured between clinopyroxene and melt...
Figure 5.11 (a) CaO, FeO, and MgO in the melt next to the advancing crystal ...
Figure 5.12 (a)
K
Al
,
K
Fe
, and
K
Mg
measured between plagioclase and melt a...
Figure 5.13 The departure from
equilibrium
of clinopyroxene compositions obt...
Figure 5.14 The departure from
equilibrium
of plagioclase compositions obtai...
Figure 5.15 Errors of (a) pressure and (b) temperature estimates caused by t...
Figure 5.16 Reverse compositional changes of (100) and (‐111) sectors in cli...
Chapter 6
Figure 6.1 Location map of the area studied.
Figure 6.2 (a) Total‐alkali versus silica classification diagram. Literature...
Figure 6.3 Microphotographs of selected MER samples at different magnificati...
Figure 6.4 Variation diagrams of major elements against silica.
Figure 6.5 Variation diagrams of trace elements against Zr.
Figure 6.6 Megacryst Mcpx: (a) photograph with the reported profile lines us...
Figure 6.7 Volume of M1 octahedron plotted against the cell volume. High‐pre...
Figure 6.8 Pressure versus temperature diagram. Data obtained combining Neav...
Figure 6.9 Calculated magma (a) viscosity and (b) ascent velocity versus cry...
Figure 6.10 Schematic cross‐section (not to scale) showing a possible model ...
Chapter 7
Figure 7.1 Details of the furnace, viscometer, and sample holder used in thi...
Figure 7.2 Total alkali versus silica diagram showing the three natural and ...
Figure 7.3 Viscosity data of melts at superliquidus conditions. Light gray, ...
Figure 7.4 Selected BSE images obtained after experiments performed at shear...
Figure 7.5 Solid phases chemistry: (a) plagioclase crystal chemistry for the...
Figure 7.6 Effective viscosity‐time paths for (a) Calbuco, (b) E122 and (c) ...
Figure 7.7 Relationship between relative viscosity (
η
r
) and crystal f...
Figure 7.8 Experimental and literature apparent viscosity data (see referenc...
Chapter 8
Figure 8.1 Schematic diagram of the scattering process.
Figure 8.2 Schematic diagram of a typical diffractometer for liquids and amo...
Figure 8.3 (a) Time evolution of the static structure factor of GeO
2
at
T
exp
Figure 8.4 Time evolution of the crystalline and amorphous fractions
A
c
and
Figure 8.5 Time evolution of the crystalline fraction
A
c
(black open diamond...
Figure 8.6 (a) Best fit of the time evolution of the crystalline fraction
A
c
Chapter 9
Figure 9.1 Schematic model depicting the axial melt‐lens (AML) system presen...
Figure 9.2 Core 312, section 1, from 45 to 60 cm, showing the dike–gabbro co...
Figure 9.3 Energy dispersive X‐ray (EDX) mosaic maps for Al, Fe, Si, Na, and...
Figure 9.4 Anorthite content from plagioclase analyses acquired via profiles...
Figure 9.5 TiO
2
versus Al
2
O
3
diagram for clinopyroxenes of two thin sections...
Figure 9.6 Composition diagrams for amphiboles of two thin sections (hay213‐...
Figure 9.7 Fractional crystallization modeling using the MELTS software pack...
Figure 9.8 Water content and melt viscosity model as a result of fractional ...
Figure 9.9 Schematic cross‐axis view for axial melt lenses at fast spreading...
Figure 9.10 Classification of oceanic felsic magmatic rocks (SiO
2
> 63 wt%) ...
Figure 9.11 Complementary normal MORB (Gale et al., 2013) trace‐element patt...
Figure 9.12 Simplified geological model for illustrating the temperature var...
Guide
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CONTRIBUTORS
Tamara L. CarleyDepartment of Geology and Environmental Geosciences, Lafayette College, Easton, PA, USA
Lissie ConnorsDepartment of Geology and Environmental Geosciences, Lafayette College, Easton, PA, USA
Luca CaricchiDepartment of Earth Sciences, University of Geneva, Geneva, Switzerland
Adrian FiegeDepartment of Earth and Planetary Sciences, American Museum of Natural History, New York, NY, USA
Letizia GiulianiDepartment of Engineering and Geology (InGeo), University G. d'Annunzio of Chieti‐Pescara, Italy
François HoltzInstitute of Mineralogy, Leibniz University Hannover, Hannover, Germany
Gianluca IezziDepartment of Engineering and Geology (InGeo), University G. d'Annunzio of Chieti‐Pescara, Italy and National Institute of Geophysics and Volcanology (INGV) Rome, Italy
Jürgen KoepkeInstitute of Mineralogy Leibniz University Hannover, Hannover, Germany
Marc‐Antoine LongpréSchool of Earth and Environmental Sciences, Queens College, City University of New York, NY, USA
Silvio MolloNational Institute of Geophysics and Volcanology (INGV), Rome, Italy and Department of Earth Sciences, Sapienza University of Rome, Rome, Italy
Sabrina NazzareniDepartment of Physics and Geology, University of Perugia, Perugia, Italy
Maurizio PetrelliDepartment of Physics and Geology, University of Perugia, Perugia, Italy
Caterina PetrilloDepartment of Physics and Geology, University of Perugia, Perugia, Italy and National Institute for Nuclear Physics (INFN), Perugia Section, Perugia, Italy
Stefano RossiDepartment of Physics and Geology, University of Perugia, Perugia, Italy
Francesco SacchettiDepartment of Physics and Geology, University of Perugia, Perugia, Italy
Nobumichi ShimizuWoods Hole Oceanographic Institution, Woods Hole, MA, USA
John StixEarth and Planetary Sciences, McGill University, Montreal, Quebec, Canada
Atsushi ToramaruDepartment of Earth and Planetary Sciences, Kyushu University, Fukuoka, Japan
Francesco VetereDepartment of Physics and Geology, University of Perugia, Perugia, Italy
Shunsuke YamashitaDepartment of Earth and Planetary Sciences, Kyushu University, Fukuoka, Japan. Now at Idemitsu Kosan Co., Ltd., Tokyo, Japan
Marco ZanattaDepartment of Informatics, University of Verona, Verona, Italy
Georg F. ZellmerVolcanic Risk Solutions, Massey University, Palmerston North, New Zealand
Chao ZhangInstitute of Mineralogy Leibniz University Hannover, Hannover, Germany and State Key Laboratory of Continental Dynamics, Northwest University, Xi'an, China
PREFACE
How and when a volcano will erupt, and the damage and disruption it may cause, is a question of great scientific and public concern. However, up to now we do not have the relevant knowledge to answer this fundamental question. While volcanic events can be catastrophic, they remain mostly unpredictable. More insights are needed into the key mechanisms involved in these dramatic natural events.
One of the areas requiring greater study is understanding the magmatic processes responsible for the chemical and textural signatures of volcanic products and igneous rocks. This includes investigating both equilibrium scenarios (e.g., phase stabilities, element partitioning) and kinetically controlled events such as the function of changing magma chemistry (replenishment), cooling, decompression (e.g., crystal and bubble nucleation and growth), devolatilization, and shear stress.
The coexistence of crystals, bubbles, and liquid phases needs to be considered as a dynamic environment in which temporal evolution depends on the system’s characteristic features (e.g., bulk composition) and on its thermodynamic conditions. In this scenario, kinetics play a major role allowing possible liquid to solid phase transitions occurring at different times. Knowing the rate at which such transformations occur will provide fundamental information as it defines the eruption behavior of volcanoes. Kinetic processes are, indeed, responsible for abrupt changes in the rheological behavior of magmas, resulting in rapid and unexpected changes from low‐ to high‐energy eruptions. It is then obvious that a better understanding of magma dynamics will improve our abilities to monitor volcanic activity and mitigate its potentially devastating impact.
The complexity of the physico‐chemical processes involved during active volcanism and dynamic magmatism, which cover wide ranges of dimensions (from submicron to intercontinental) and timescales (from seconds during explosive eruptions to thousands of years for volcano‐tectonic processes), demands multidisciplinary research approaches. Covering all scientific aspects related to this topic is far beyond the scope of this book, but this compilation of geochemical, petrological, physical, and thermodynamic studies provides a comprehensive overview about recent progress, often achieved using unconventional and novel techniques. The book can be a useful compendium for lecturers and students, as well as a reference for researchers developing new and innovative ideas and projects.
This book is divided into two sections. The first section (chapters 1–4) focuses on geochemical, petrological, and geophysical studies to understand dynamic magma evolution and the timescales involved, including processes such as magma recharge, mixing, and mingling. The second section (chapters 5–9) focuses on physical, thermodynamic, and theoretical approaches to investigating magmas according to the different geological scenarios that occur naturally.
Chapter 1 by Petrelli and Zellmer deals with rates and timescales of crustal magma transfer, storage, emplacement, and eruption. The authors review the most pertinent unresolved questions in this field, and highlight geochemical and geophysical methods that are available to address these questions. Long‐storage magmatic timescales are discussed in detail as well as the influence of volatiles in volcanic environments and possible storage depths or ascent rates.
Chapter 2 by Longpré, Stix, and Shimizu, deals with melt inclusions as a unique material to retrieve information on the volatile budgets and compositional diversity of magmatic systems. Their results document a rare case of boundary‐layer melt entrapment in natural magmas, indicating that melt inclusions hosted by fast‐grown spinel are not a reliable record for melt evolution. The authors highlight the importance of boundary‐layer melt entrapments as a tracer for dynamic magmatic processes.
Chapter 3 by Connors, Carley, and Fiege is dedicated to the properties of apatite as a tool for understanding the evolution of volatile and trace elements in magmatic systems. Torfajökull, a historically active Icelandic volcano erupting apatite‐bearing magmas, is a key study site since it exhibits a unique compositional history, showing transitioning from more‐evolved peralkaline rhyolites (Pleistocene) to less‐evolved metaluminous rhyolites (Holocene). This study reveals the potential of apatite to elucidate magmatic and volcanic processes in Iceland.
Chapter 4 by Yamashita and Toramaru investigates the crystal size distribution (CSD) of plagioclase phenocrysts in four historical lavas from Sakurajima volcano, southern Kyushu, Japan. The results reveal a correlation between CSD and geological data (volumes and intervals between eruptions) for large historical eruptions, suggesting that the supply rate from the mantle controls the triggering of eruptions.
Chapter 5 by Giuliani, Iezzi and Mollo investigates the solidification of magmas occurring by cooling‐ (∆T/∆t) and/or degassing‐induced decompression (∆P/∆t), as a function of solidus temperature, glass transition temperature, and melting temperature, respectively. The study evaluates the influence of bulk chemical composition of a silicate liquid, P, T, fO2, and H2O on magma solidification. The most relevant solidification conditions of magmas leading to possible crystallization paths and relative physical models and reconstruction of magmatic intensive variables using mineral composition variability, are discussed. Chemical attributes of minerals are reviewed in order to discriminate their equilibrium and disequilibrium formations and, finally, using chemical composition of solid phases the authors reconstruct magmatic intensive variables.
Chapter 6 by Nazzareni, Rossi, Petrelli, and Caricchi is dedicated to the Main Ethiopian Rift (MER). The MER represents a young continental rift with an associated large volume of magmatism that forms one of the major large igneous provinces. The authors used clinopyroxene crystals in order to record variations of P, T, and fO2 with the aim of reconstructing the geological history of host rocks. Clinopyroxene geobarometry was performed combining X‐ray diffraction with mineral chemistry to highlight a complex polybaric plumbing system active since 7.5–3.7 Ma. The continuous polybaric MER clinopyroxene crystallization from the lower to middle crust is explained by a plumbing system composed of a dyke complex where magmas rise, stall, and, finally, crystallize.
In Chapter 7, Vetere and Holtz compare viscosity data from three different compositions: basalt, andesite, and a synthetic pyroxenite. In addition to the determination of melt viscosities, viscosity data were collected at subliquidus conditions in partially crystallized systems, under controlled shear rates of 0.1 and 1 s‐1. Experimental data show that changes of shear rates from 0.1 and 1 s‐1 may cause a viscosity difference of half to one order of magnitude, pointing to the so called “shear‐thinning effect.” The authors suggest that this effect should be taken into account when considering magmatic processes occurring in volcanic conduits as it could drastically change the dynamics of the magmatic system.
Chapter 8 by Zanatta, Petrillo, and Sacchetti propose the time‐resolved neutron diffraction as a tool for the study of crystallization kinetics of glasses and supercooled liquids. In the situation of multiple crystallizing phases, the analysis of the Bragg peaks can provide an unambiguous identification of the crystal structures with proper lattice parameters and crystallization timescales for each phase. Results show that the isotopic sensitivity of neutrons could be exploited to highlight a single species with respect to the surrounding medium, thus facilitating data interpretation for complex systems such as ascending magmas. Neutron‐based techniques are particularly suitable to measure bulk samples controlling environmental parameters such as T and P. This can be pivotal for geological studies aiming at in situ measurements during time‐dependent processes such as crystallization in magmas. Moreover, an empirical model for the interpretation of the crystallization kinetics in supercooled liquids is presented.
Chapter 9 by Koepke and Zhang sheds new light on the complexity of magmatic and metamorphic processes ongoing within and at the roof of axial melt lenses (AMLs), with a focus on the petrological and geochemical record provided by fossilized AMLs. The International Ocean Discovery Program (IODP) Hole 1256D in the equatorial Pacific is the location, where for the first time, the transition between sheeted dikes and gabbros in an intact fast spreading crust was penetrated, providing a core with a continuous record of the upper part of an AML. This location can be regarded as Rosetta Stone to answer long‐standing questions on the complex magmatic evolution within an AML, as well as on metamorphic and anatectic processes ongoing at the roof of a dynamic AML.
The topics presented in this book cover a wide range of observations and measurements on dynamic magmatic processes, merging insights from fieldwork and experimental results, theoretical approaches, and computational modeling.
The coexistence of crystals and melt must be seen as a dynamic process for which time evolution depends on various intrinsic (e.g., chemical compositions, temperature, pressure) and extrinsic parameters (e.g, tectonic environment). Kinetics play a fundamental role allowing a variety of possible phase transitions: liquid to solid, liquid immiscibility or exsolution in minerals, mineral reactions, and formation of compositional zoning. Knowing the rate at which such transformation occurs is fundamental as it defines the eruption behavior in volcanoes. Kinetic processes are responsible for abrupt changes in the rheological behavior of magmas, resulting in low‐ to high‐energy eruptions. Thus, a better understanding of magma dynamics will improve our ability to monitor and forecast volcanic activity. The results presented in this book represent another step forward in this direction.
Francesco Vetere, University of Perugia
January 2020
Part ITimescales and Time Sensor
1Rates and Timescales of Magma Transfer, Storage, Emplacement, and Eruption
Maurizio Petrelli1 and Georg F. Zellmer2
1 Department of Physics and Geology, University of Perugia, Perugia, Italy
2 Volcanic Risk Solutions, Massey University, Palmerston North, New Zealand
ABSTRACT
The rates and timescales of crustal magma transfer, storage, emplacement, and eruption are a key to understanding subvolcanic processes, characterizing volcanic hazards, and developing mitigation strategies. In this chapter, we review the most pertinent open questions in this field, as well as the many geochemical and geophysical methods that are available to address these questions. Results point to long storage timescales, of up to ~106 years, in deep (i.e., ~20–30 km), crustal hot zones. Estimated ascent velocities from deep reservoirs to shallower systems span a vast range of ~10 orders of magnitude, and are a function of the thermophysical parameters of the ascending magma (e.g., density, viscosity, and overpressures in the reservoirs) and the host rocks. At mid‐ to upper crustal levels (i.e., < 15–20 km), we elucidate the cold storage of magma mushes for long periods, which can be unlocked during short‐term events to form ephemeral magma chambers. Unlocking timescale estimates range from minutes to thousands of years, indicating a variability of about ~8 to ~10 orders of magnitude. This large variation results from the interplay among many processes, often nonlinearly coupled, occurring before an eruption. For example, exsolved volatile species have a significant role in modulating preeruptive dynamics and relative timescales; they increase the buoyancy of magmas, affect phase equilibria, promote convective dynamics, and may ultimately trigger eruptive events. As a consequence, understanding the role of volatiles in subvolcanic magmatic processes, including ascent rates, storage mechanisms, and relative timescales, will be paramount for future studies.
1.1. INTRODUCTION
There are about 500 active volcanoes on Earth with approximately 500 million people living on or close to them (Siebert et al., 2011, 2015). On average, about 50 volcanoes erupt each year (Siebert et al., 2015), generating a direct hazard for the people living in their surroundings. For example, the 1815 eruption of Tambora volcano, Indonesia, killed more than 90,000 people, including deaths resulting from subsequent crop loss and famine (Stothers, 1984). Taking into account population growth through time, an equivalent eruption today, in populated areas (e.g., Indonesia and the Philippines), would potentially involve more than 20 million people (Newhall et al., 2018). Further, explosive eruptions constitute a significant economic risk on a global scale. The modest ash cloud generated by Eyjafjallajökull volcano (Iceland) in April 2010 paralyzed the air traffic of a large part of Europe for about 1 week (Sigmundsson et al., 2010), causing an economic loss of several billion Euros as millions of travelers were grounded and industrial production was decelerated or halted. Often, explosive eruptions occur with virtually no warning time or with only weak geophysical precursors. Examples are the eruptions of Chaitén (2 May 2008; Castro & Dingwell, 2009; Wicks et al., 2011) and Calbuco volcanoes (22 April 2015; Arzilli et al., 2019; Romero et al., 2016) in Chile.
Figure 1.1 Number of manuscripts published from 1980 to 2018 containing the words “magma” and “timescales” in title, abstract, or keyword fields.
[Source: Scopus®).]
Understanding the processes occurring in crustal sections below active volcanoes and their time evolution is therefore essential in the provision of prompt and reliable information to decision makers and institutions in order to define appropriate hazard mitigation plans. To achieve this goal, we need to improve our knowledge of rates and timescales of the processes occurring below active volcanoes before an eruption. It is of note that the number of manuscripts involving estimates of timescales for magmatic processes is now approaching more than 50 per year (Figure 1.1); some well‐documented review studies are included among these (K.M. Cooper, 2019; Hawkesworth et al., 2004; S. Turner & Costa, 2007). One chapter of the Treatise on Geochemistry (Turekian & Holland, 2013) is about the timescales of magma transfer (i.e., the process of magma migration, typically from deeper to shallower crustal regions) and magma storage (i.e., the mechanisms and the processes governing the stagnation of magmas at a fixed depth) in the crust (Reid, 2003). Four chapters of The Encyclopedia of Volcanoes (2nd edition; Sigurdsson, 2015) deal with the modeling and timescale estimations of melt migration (Daines & Pec, 2015), magma ascent and storage (Browne & Szramek, 2015), magma transport in dikes (Gonnermann & Taisne, 2015), and magma ascent and degassing at shallow levels (Burgisser & Degruyter, 2015). Also, focused reviews and extensive studies are available on the timescales for specific fields of study and techniques (e.g., Bachmann, 2010; K.M. Cooper, 2019). Examples are the modeling of zoning patterns in crystals (Costa et al., 2008; S. Turner & Costa, 2007), uranium series isotopes (K.M. Cooper & Reid, 2008), magma ascent rates (Burgisser & Degruyter, 2015; Crisp, 1984; Gonnermann & Manga, 2013; Rutherford, 2008; Scandone et al., 2007), magma degassing (M.B. Turner et al., 2013), volatiles accumulation (Petrelli et al., 2018), and pluton assembly (Caricchi et al., 2012). Finally, entire books are focused on the evolution of volcanic plumbing systems (defined as the structural framework of pathways and storage regions through which magma travels on its journey from its source region to the Earth’s surface; Burchardt, 2018), timescales of magmatic processes (Dosseto et al., 2010), and petrochronological methods (Kohn et al., 2018).
All of these works contributed to unblurring our vision of preeruptive processes, and their evolution in time and space. In detail, early models of volcanic plumbing systems considered a long‐lived, melt‐dominated magma chamber, typically emplaced at shallow (i.e., below ~10 km depth) crustal levels (Montagna et al., 2015; Oldenburg et al., 1989). The simplest models assume the magma chamber to behave as a closed system, filled by a Newtonian melt (Oldenburg et al., 1989), where crystals nucleate and progressively grow (Petrelli et al., 2016). Other models, in addition, account for periodic refilling with new magma, thus considering the magma chamber as an open system (Annen, 2009). The most evolved models further account for the non‐Newtonian rheology of magmas, as well as volatile saturation and exsolution, occasionally including the effects of overpressure in the system due to, for example, refilling with new magma, volatile exsolution, and regional stresses (Dufek & Bachmann, 2010; Parmigiani et al., 2016; Petrelli et al., 2018; Ruprecht et al., 2008).
Figure 1.2 Simplified scheme of a mush‐dominated volcanic plumbing system developing from deep crustal levels to shallow depthsand its relationship to the four main open questions addressed by this chapter.
Many lines of evidence suggest, however, that the conceptual model of shallow magma chambers as melt‐dominated domains is unrealistic (Cashman et al., 2017; Sparks & Cashman, 2017). Further, physical models based on thermal, mechanical, and dynamical principles suggest that long‐lived and melt‐dominated magma chambers are unlikely to develop or to be maintained, especially in the upper crust (Annen et al., 2015). As a consequence, magmatic reservoirs (i.e., the physical locus hosting magmas that may be melt‐dominated or crystal‐rich) have to be considered as complex systems formed mainly of crystal mushes, where liquid‐dominated regions (i.e., volumes of eruptible magma) ephemerally develop from shallow to deep crustal levels (Bachmann & Huber, 2016; Cashman et al., 2017; K.M. Cooper & Kent, 2014; Edmonds et al., 2019; Sparks & Cashman, 2017; Zellmer & Annen, 2008), and where volatiles play a significant role (e.g., Bachmann & Bergantz, 2008; Edmonds & Wallace, 2017; Edmonds & Woods, 2018).
In this chapter, we present the methods and techniques currently utilized to unravel rates and timescales of magmatic processes. We then review the evidence that provides insights into magma ascent rates through the crust, timescales of magma storage, and the dynamic processes occurring in volcanic plumbing systems before eruptions. Our main goal is to link all the different clues that are currently utilized in the estimation of time‐dependent magmatic processes, and to provide an inclusive vision of preeruptive dynamics with their associated rates and timescales. The questions that we will address are (Figure 1.2): How does the melt phase evolve in space and time in a mush‐dominated magmatic plumbing system? Do long‐lived magmatic reservoirs exist? What are the timescales of preeruptive events? What are the rates of magma ascent to the Earth surface before an eruption?
1.2. METHODS AND TECHNIQUES FOR ESTIMATION OF RATES AND TIMESCALES
In this section we present the methods and techniques currently utilized to unravel rates and timescales in magmatic systems, including: isotopic‐decay dating, chemical‐diffusion‐based geospeedometers, crystal‐size‐distribution analysis, melt‐inclusion timekeepers, thermal modeling of magmatic systems, mechanical modeling of magma ascent, and the modeling of the volatile phase. The fundamental principles of each technique are reported in Table 1.1, together with the main benefits, limitations, and uncertainties.
1.2.1. Isotopic‐Decay Dating Techniques
Isotopic‐decay dating techniques can be divided into those that allow the determination of eruption ages, and those that provide insight into preeruptive processes. The difference is principally due to the closure temperature of the elements and isotopes used. For the former, closure temperatures are significantly lower than magmatic temperatures, and the clock therefore starts ticking only at the point of rapid cooling due to eruption. For the latter, closure temperatures are at or close to magmatic temperatures, and preeruptive processes can therefore be timed if eruption ages are known or can be determined.
Table 1.1 Principles, Benefits, Limits, and Uncertainties of Methods and Techniques for Rates and Timescales Estimations. For the References, Please Refer to the Main Text
Method/technique
Principles
Benefits
Limits
Uncertainties
K–Ar and Ar–Ar dating
Decay of
40
K to
40
Ar by electron capture; step heating allows ages to be obtained from partially altered rocks
Absolute dating of eruption age of K‐bearing rocks, even if some parts have lost Ar due to alteration
Young rocks require high K contents to be datable; excess Ar problem, i.e. initial Ar content may be elevated
Relative uncertainties highly dependent on the age of the sample
Rb–Sr dating
Decay of
87
Rb to
87
Sr by electron emission
Absolute dating of eruption age of old samples
Rb and Sr are both fluid mobile large ion lithophile elements, and many systems do not remain closed for the long time periods measured
Variable, but typically millions of years for samples billions of years old
(U–Th)/He dating
Alpha decay from natural decay chains and
147
Sm producing
4
He
Determining rates and timescales of rock exhumation, mountain building and landscape evolution, with access to very young eruption ages in combination with U‐series dating
When used to date volcanic eruptions, post‐eruptive reheating events may significantly alter the results; also, radiation damage may influence the sensitivity of the (U‐Th)/He system
Uncertainty of (U–Th)/He ages is typically in the range of 2–5%, expressed as 1σ
U‐series dating
Radioactive decay from
238
U,
235
U, and
232
Th through a number of short‐lived daughters to stable
206
Pb,
207
Pb and
208
Pb, respectively
Secular disequilibria introduced by geological processes can be dated; a range of intermediate isotopes with a range of half‐lives provides access to a range of processes and ages; internal checks for consistency may be available through the use of different isotope pairs; inconsistencies may point to complexities
Typically, five times the half‐life of the shortest‐lived isotope involved; system needs to remain closed for this time; the geological processes introducing the disequilibria need to be short relative to the half‐life of the isotope‐pair investigated to provide age information without additional modeling
Dependent on degree of disequilibria displayed (high if close to the limit of five half‐lives), and the half‐life of the isotope‐pair investigated
Geospeedometry
Diffusion of elements within or between crystals at magmatic temperatures
Dating high‐
T
preeruptive processes; a range of elements with different diffusivities allows access to a range of timescales; provides constraints on magmatic temperatures when combined with radiometric determination of preeruptive ages
An initial concentration profile needs to be assumed; for dating purposes, temperatures need to be independently estimated
Absolute uncertainties are order of magnitudes, as diffusivities are typically not well enough constrained; relative uncertainties, i.e. difference between ages obtained, depend on age
Crystal‐melt reactions
Reaction of crystals with surrounding melt due to crystal‐melt disequilibrium; width of reaction rim provides yield time
Access to magma mixing processes that result in mineral–melt disequilibrium; access to very short timescales
Reaction rates need to be experimentally constrained, and are highly dependent on composition, temperature, and pressure of the system
Age‐dependent, and unless experimental work done on system investigated, order‐of‐magnitude estimates
CSD analysis
Distribution of crystal sizes carries information on the timescales of crystallization
Simple systems provide access to time if growth rates can be constrained; further, CSDs can help reveal magmatic processes such as crystal fractionation, crystal accumulation, and magma mixing
To yield time information, growth rates need to be independently constrained, which is rarely the case
Order‐of‐magnitude or worse uncertainties, unless crystal growth rates are independently constrained
Concentration variance decay
Based on the concept of the time decay of the variance of chemical composition during magma mixing
Provides information about mixing‐to‐eruption timescales; statistically robust, since it considers multiple chemical elements, more than the few typically utilized by classical geospeedometers
Ability to track only the last mixing event before the eruption; requires ”ad hoc” experiments
Constrained by experiments developed for each single case
Melt inclusion textural analysis
Based on quantitative three‐dimensional textural analyses to calculate melt‐inclusion faceting times
Determination of melt‐inclusion faceting times provides information about the longevity of the magmatic system
Many different parameters must be independently constrained to provide significant results
On the order of 100%
Thermal modeling
Provides a wide range of analytical solutions and numerical models dealing with heat transfer during geological processes
Powerful tool based on a well known physical process; new numerical schemes and solutions are continuously developed
To provide reliable solutions, a careful selection of the adopted analytical solution and/or numerical scheme is required; initial and boundary conditions must be carefully constrained
Depending on the adopted analytical solution or numerical scheme
Mechanical modeling of volatile phase
Includes the numerical modeling of magma ascent and decompression, experimental constraints at high pressure and temperature, analogue modeling, and the measurement of bubble number density
Provides constraints on topical processes occurring during magma ascent and eruption
Behavior of volatile phases is still poorly understood, and requires further investigations
Depending on the approach adopted
Mechanical modeling of magma ascent
Models melt migration and magma ascent velocities
Provides insights about magma ascent patways, velocities and timescales; useful for inferring preeruptive dynamics
Requires knowledge of rheological properties of magma and surrounding hosting rocks; to achieve reliable results, knowledge of the provailing stress field is also required
Physical formulation and associated uncertainities are mainly related to the length‐scale of the processes addressed
MND water exsolution rates
Based on the decompression‐induced crystallization of microlites due to phase equilibria changes following water exsolution
Examining the link between the decompression process and the formation of microlites provides information on magma ascent and the resulting water exsolution processes
Main limitations are due to the disequilibrium vesiculation; kinetic constant must be determined accurately; not applicable to microlite‐poor samples
Reproduces experimental MND by first order approximation
Seismic constraints
Spatial propagation of seismicity over time associated with magma movement
Direct access to rock fracturing in response to magma movement, and therefore direct access to ascent rates if earthquake locations can be constrained accurately
Constraining hypocentre locations accurately is dependent on good knowledge of subsurface seismic properties and geological structures; seismic signals of magma movement often too small to be detected
Dependent on the limits listed
1.2.1.1. Constraining Eruption Ages
1.2.1.1.1. K–Ar and Ar–Ar Dating
Both K–Ar and Ar–Ar dating techniques are based on the decay of a naturally occurring isotope of potassium, 40K, to 40Ar (Kelley, 2002). The essential difference between K–Ar and Ar–Ar dating techniques lies in the measurement of potassium. In the K–Ar method, potassium is measured directly, whereas in the Ar–Ar technique, K is measured after the transformation of 39K to 39Ar by neutron bombardment (Kelley, 2002). The main advantage of the Ar–Ar technique over the K–Ar dating is that potassium and argon are effectively measured simultaneously (i.e., on the same aliquot of sample), providing a greater internal precision. Many efforts have been made to increase the precision of K–Ar dating (e.g., Gillot et al. 2006). Ar–Ar and K–Ar dating methods have been widely applied to estimate the ages of eruptive events (Bachmann, Oberli, et al., 2007; Bacon & Lanphere, 2006; Chenet et al., 2007; Deino et al., 2004; Iverson et al., 2014; Jicha et al, 2016; Lanphere, 2000; Muir et al., 2015; Petrosino et al., 2016; Reichow et al., 2002). As such, these methods are a prerequisite for determining preeruptive ages of crystallization and other magmatic processes through the use of radiometric clocks. However, dating young (< 20 ka) eruptive deposits remains a challenge, unless they are highly potassic, because of the long half‐life of 40K. As in all isotopic‐decay dating techniques, the system needs to be closed to obtain reliable ages. Argon loss through alteration or high temperature events that can damage the mineral lattices will result in age estimates that are too young, while excess argon, which may be derived from degassing of deeper magmas or from the assimilation of old crustal xenoliths, will result in age estimates that are too old.
1.2.1.1.2. Rb–Sr Dating
The Rb–Sr method is based on the decay of 87Rb to 87Sr (half‐life of 4.88 × 1010 years). It is one of the oldest (Hahn & Walling, 1938) and widely utilized bulk‐dating techniques in geology (Rink et al., 2015), finding extensive applications in igneous petrology (Glodny et al., 2002, 2003; Halama et al., 2018). Due to the low closure temperature of the Rb–Sr isotope system, this also is technique for determining eruption age—preeruption ages cannot be determined using this technique. Further, the long half‐life of 87Rb precludes high‐resolution dating, but it is applicable for constraining the eruption ages of ancient volcanic rocks. In recent times, extensive application of the Rb–Sr dating method has been limited in situ techniques such as ion microprobe and laser ablation inductively coupled plasma mass spectrometry (LA‐ICP‐MS) are not possible with this method. Developments in new analytical techniques, however, have allowed the Rb–Sr method using laser ablation ICP‐MS (Zack & Hogmalm, 2016), to be applied to the study of timescales of ancient subsolidus plutonic processes, such as pluton emplacement and hydrothermal alteration of plutonic rocks (Zellmer, Kimura, et al., 2018).
1.2.1.1.3. (U–Th)/He dating
(U–Th)/He chronology relies on the radioactive decay of 238U, 235U, 232Th, and 147Sm to 4He (Farley, 2002; Farley & Stockli, 2019). It is commonly applied to U‐ and Th‐bearing minerals (e.g., apatite, titanite, and zircon) to unravel rates and timescales of rock exhumation, mountain building, and landscape evolution (Ehlers & Farley, 2003; House et al., 1998; Shuster et al., 2005). As an example, closure temperatures for apatite and zircon range from ~50 to ~200°C (Reiners, 2005). As a consequence, this technique is also suitable for dating strong cooling events in magmatic systems (i.e., eruptions; Farley et al., 2002; Schmitt et al. 2006, 2010). Although not yet widely utilized, the (U–Th)/He technique can successfully date the eruption age of young magmatic systems (i.e., < 1.5 Ma). For example, Danišík et al. (2017) recently showed how the combination of U–Th disequilibrium/U–Pb and (U–Th)/He methods can be applied successfully in dating zircons up to 2.5 ka, opening new perspectives for dating Quaternary magmatic systems. Also, the method has been applied successfully to refine the eruption chronology of the Ciomadul volcanic complex (e.g., Harangi, Lukács, et al., 2015; Molnár et al., 2018, 2019).
1.2.1.2. Constraining Preeruptive Crystallization Ages
Uranium‐series dating methods are based on the decay of 232Th, 238U, and 235U to 208Pb, 206Pb, and 207Pb, respectively (Bourdon et al., 2003; K.M Cooper, 2015, 2019; K.M. Cooper & Reid, 2008; Ivanovich & Harmon, 1992; Schmitt, 2011; Schoene, 2013). These decay chains are widely utilized to provide crystallization ages of accessory minerals like zircon (Charlier & Zellmer, 2000; S.E. Jackson et al., 2004; Reid et al., 1997, 2011; Reid & Coath, 2000; Wilson & Charlier, 2016), monazite (Parrish, 1990), and titanite (Frost et al., 2001). Also, intermediate daughter nuclides are utilized in U‐series disequilibrium dating. Closure temperatures are typically well above the solidus (e.g., above 900°C for Zircons; Lee et al., 1997), so that preeruptive crystallization ages can be determined through these dating methods. In detail, 238U, 235U, and 232Th decay through a series of intermediate daughter nuclides (e.g., 234U, 230Th, 226Ra, 222Rn, and 210Pb for 238U) that are both radiogenic and radioactive, with half‐lives ranging from seconds to 245 kyr. U‐series disequilibrium dating is widely utilized for the estimation of the rates and timescales of magmatic systems (Black et al., 1998; Blundy et al., 2008; Bourdon et al., 2000; Cooper & Reid, 2003; Cunningham, Turner, Patia, et al., 2009; Landwehr et al., 2001; Pyle et al., 1988; Sims et al., 2013; M.B. Turner et al., 2013; Zellmer et al., 2008), providing a powerful tool in petrochronology. Example applications of uranium‐series analyses to the study of eruptible magmas are: (a) the tracing of preeruptive magma degassing (Berlo et al., 2006; Kayzar et al., 2009; M.B. Turner et al., 2013); (b) timescale estimations of mixing events associated with eruptive events (Ruprecht & Cooper, 2012); (c) estimating the rates of magmatic processes, including cooling rates and residence times in magma reservoirs before eruptions (Bourdon et al., 2000; Charlier & Wilson, 2010; K.M. Cooper & Kent, 2014; Cunningham. Turner, Dosseto, et al., 2009; Harangi, Lukács, et al., 2015; Kuritani et al., 2007; Reid & Vazquez, 2017; Rogers et al., 2004; Schmitt et al., 2010, 2011; Wotzlaw et al., 2013); (d) constraining the genesis of volcanic rocks (Avanzinelli et al., 2007); (e) unraveling magma evolution and ascent at volcanic arcs (Zellmer et al., 2005); (f) determining the chronology of petrogenetic processes at mid‐ocean ridges (Goldstein et al., 1993; K.H. Rubin et al., 2005).
As with other radiogenic dating methods, one of the key prerequisites of U‐series dating is that the system remains closed to loss or gain of the specific isotopes used for age estimation of the event that established disequilibrium. In magmatic studies, the (234U/238U) activity ratio is frequently monitored for deviation from equilibrium, which would indicate interaction with fluids carrying fluid mobile elements (such as U and Ra). Recent work has shown that in some volcanic rocks, groundmasses in 234U–238U equilibrium can carry crystal cargo in 234U–238U disequilibrium (Zellmer, Freymuth, et al., 2014; Zellmer, Rubin, et al., 2015), precluding the determination of meaningful mineral isochrons. This demonstrates that care must be taken to obtain reliable mineral formation ages for magmatic systems on the basis of U‐series dating.
1.2.2. Chemical‐Diffusion‐Based Geospeedometers
Chemical diffusion is a time‐dependent process, widely used for the estimation of rates and timescales of magmatic processes (Costa et al., 2008; Costa & Morgan, 2010). It consists of the analyses of chemical heterogeneities in crystals and glasses, providing a record of magmatic processes. These heterogeneities progressively move to equilibrium profiles at rates that are mainly controlled by the diffusion coefficients. As a consequence, knowing suitable values for the diffusion coefficients, and measuring the chemical heterogeneities, makes it possible to obtain the timescales of the system using Fick’s second law of diffusion.
Many studies focus on Fick’s second‐law‐based geospeedometers to obtain timescales of open‐system processes in magmatic reservoirs before an eruption, by investigating chemical heterogeneities in crystals (Costa et al., 2003, 2008; Costa & Dungan, 2005; Dohmen et al., 2018; Druitt et al., 2012; Flaherty et al., 2018; Garzanti et al., 2011; Petrone et al., 2016, 2018; Turner & Costa, 2007; Zellmer & Turner, 2007; Zellmer et al., 1999, 2011, 2012; Zellmer, Sakamoto, et al., 2016). Also, such geospeedometers have been applied to chemical heterogeneities in crystals for the study of magma cooling rates (Dohmen et al., 2018; Newcombe et al., 2014) and ascent rates (Demouchy et al., 2006; Ferriss et al., 2018; Lloyd et al., 2016).
It is noteworthy that Fick’s second‐law‐based geospeedometers have not been used exclusively to study chemical heterogeneities in crystals. For example, they have been applied successfully to constrain ascent timescales using melt embayments (i.e., melt inclusions that have failed to become fully enclosed; Ferguson et al., 2016; Humphreys et al., 2008; Liu et al., 2007; Lloyd et al., 2014; Myers et al., 2018). During ascent and degassing, melt embayments will experience diffusive volatile loss due to direct connection to the host melt. This process has been modeled successfully by Fick’s second law, providing constraints on the timescales of diffusive reequilibration, which can be related to the decompression rate of the magma (Humphreys et al., 2008; Lloyd et al., 2014).
1.2.3. Rates from Crystal‐Melt Reactions During Magma Ascent
The rates of phenocryst‐melt reactions produced by decompression can be utilized successfully to estimate the rates of magma ascent (Browne & Gardner, 2006). For example, the loss of volatiles from the melt during its ascent toward the surface produces the breakdown of volatile‐bearing phenocrysts, such as amphibole and biotite. The kinetics of these reactions are complex functions of many variables, including mineral and glass compositions, melt viscosity, and temperature. As a consequence, they are not easily constrained theoretically, but they can be successfully studied experimentally (Rutherford & Devine, 2003). For example, the rates of reaction between amphibole phenocrysts and a coexisting rhyolitic melt have been studied (Rutherford & Hill, 1993), and these calibrations can be used to estimate ascent rates for dacitic and andesitic composition magmas. De Angelis et al. (2015) examined the process of amphibole decomposition through isobaric heating of magnesio‐hornblende phenocrysts within a natural high‐silica andesite glass, highlighting that the injection of new magma (i.e., heating) in a shallow magmatic reservoir produces amphibole reaction rims that have thicknesses, textures, and mineralogies consistent with many of the natural reaction rims seen at island‐arc andesite volcanoes. De Angelis et al. (2015) also showed that heating‐induced reaction rims are texturally consistent with experimental decompression reaction rims. As a consequence, it may be challenging to discern between decompression and heating mechanisms in nature (De Angelis et al., 2015). Phenocryst–melt reactions have been also applied to estimate magma ascent rates in alkali basalt and kimberlite magmas through studying the reactions occurring between the melt phase and garnets in garnet‐bearing xenoliths (Canil & Fedortchouk, 1999). Finally, crystal–melt reaction rates may sometimes be determined from natural samples through geospeedometric techniques (
