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University of Cambridge

Data-driven approaches towards understanding trace metal and magmatic processes in arc volcanoes, with applications to Java, Indonesia

Abstract

dc:description.abstract

Expanding human populations combined with the challenges of climate change, have resulted in higher degrees of human risk exposure to natural disasters like volcanoes. Such increased volcanic risk is especially pronounced along tectonic plate margins like subduction zones (or "arcs"), where explosive volcanism is more common. The aforementioned social and economic pressures will necessitate a move towards "greener" economies, invariably leading to increased competition for natural mineral resources. While much progress has been made in the past 40 years understanding what processes shape ore development and volcanism in subduction zones, it is only in recent years that the enormous amounts of data produced can be synthesized to develop data-rich models to elucidate a more refined understanding of subduction zone magmatism and igneous geochemistry. Here, I present a data-driven approach to both global and regional scale magmatic processes in subduction zones using a combination of global datasets, novel computational methods, and microanalytical petrology. Beginning with a global perspective, I identify key metamorphic processes that are controlling geochemical patterns in subduction zone magmas, using careful compilations and statistical analyses of large datasets. These investigations address longstanding questions in igneous petrology, such as: which specific mineral reactions are driving fluid mobile element enrichment in arc magmas and how does this vary from arc to arc? A later chapter asks: what petrological processes favor the enrichment of copper and the optimization of ore-forming potential in a magma? These global insights are complemented by a detailed petrological study of Mount Slamet volcano, Java, Indonesia, infused with computational advances in machine-learning. Java has 45 active volcanoes, which showcase a variety of hazardous behaviors, and the island hosts one of the largest and most productive porphyry copper deposits in the world. To understand Java’s volcanism, I combine my data-driven petrological methods with microanalytical techniques applied to whole rock powders, individual crystals, and melt inclusions (small pockets of magma trapped inside a crystal). At Slamet volcano, I show the transcrustal complexity of polygenetic-monogenetic volcanic systems, and highlight the role of scoria cones in probing deeply-stored magmas. Together, these three threads comprise a holistic picture of the physical and chemical processes shaping magmatism in subduction zones.

Degree

thesis:*
Name dc:type.qualificationname
Doctor of Philosophy (PhD)
Level dc:type.qualificationlevel
Doctoral
Grantor dc:publisher.institution
University of Cambridge
Year dc:date.issued
2022

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Barber, Nicholas
Advisors dc:contributor.advisor
  • Edmonds, Marie
  • Williams, Helen
  • Jenner, Frances

Subjects

dc:subject × 8

Rights

dc:rights
Language dc:language
eng

Identifiers

dc:identifier.*
Author Identifier
0000-0003-4513-2421
OAI identifier oai:identifier
oai:www.repository.cam.ac.uk:1810/348027

Chain of custody

source
Harvested from
Cambridge University
Base URL
api.repository.cam.ac.uk/server/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Barber, Nicholas. Data-driven approaches towards understanding trace metal and magmatic processes in arc volcanoes, with applications to Java, Indonesia. Doctoral thesis, University of Cambridge, 2022. https://doi.org/10.17863/CAM.95445