About the project
This project investigates enigmatic long-distance geochemical trends in fundamental magmato-tectonic systems including plume-to-rift and rift-to-spreading contexts. We aim to determine if plate-scale mantle flow patterns or regional-scale interconnected melt transport networks drive these trends, shedding light on Earth's complex dynamics. The study will combine tools from advanced modeling and machine learning.
Understanding the geochemical trends linked to mantle magmatic systems across plate-scale distances presents a compelling challenge in geosciences. Current models of mid-ocean ridge magmatism suggest magma transport is confined within 40-60 kilometers of the ridge axis, which conflicts with 1000 km-scale geochemical trends observed in complex tectonic systems where plume-related hotspots or continental rift zones interact with or transition to oceanic spreading centres. Available geochemical data can be used to constrain the dynamics of melt generation and transport in tectonically complex oceanic systems and help interpret the geochemical systematics of plume-ridge interactions and rift-to-spreading transitions. The project will focus on two study sites, the Wolf-Darwin lineament connecting the Galapagos hotspot with the Galapagos spreading centre, and the Afar Depression where the East African Rift transitions into a new spreading centre.
This project will investigate two contrasting hypotheses to elucidate these long-distance geochemical trends:
- that asthenospheric mantle flow from plume to ridge controls geochemical variability of mantle magma output
- that interconnected melt transport networks along the lithosphere-asthenosphere boundary give rise to long-distance trends in magma geochemistry
You will test the hypotheses by developing advanced numerical models of magma/mantle dynamics coupled to petrological phase equilibria, as well as major, trace, and isotopic magma evolution and will analyse parameter sensitivities and compare to data from natural systems using statistical/machine learning techniques.
This research will build a fundamental understanding of how geochemical signatures reveal underlying magma/mantle dynamics by revealing how magmatic systems can communicate over hundreds of kilometres. In sum, this project will unravel the intricacies of mantle magmatism's long-distance relationships, shaping our understanding of Earth's dynamic interior.
Supervisory team
The supervisory team includes supervisors from several organisations. Please contact the Lead Supervisor for more information about the team.
Training
The INSPIRE DTP programme provides comprehensive personal and professional development training alongside extensive opportunities for students to expand their multi-disciplinary outlook through interactions with a wide network of academic, research and industrial/policy partners. The student will be registered at the University of Southampton and hosted at the School of Ocean and Earth Science.
The training program for this specific project will cover several essential areas. The successful candidate will learn to use Matlab software for numerical modelling techniques as applied to mantle flow and melt transport. The programme will also provide training in machine learning techniques in Python, as well as (potentially) GPU-accelerated parallel computing techniques in Julia. Given this programme of training, the successful candidate will gain invaluable experience that will equip them with highly sought-after skills for a career in either academia or industry.
