Links Between Volcanic Eruptions and Magma Body Geometry Revealed by Seismic Reflection Imaging at the East Pacific Rise
Bibliographic record
Abstract
The structure of the magmatic system beneath subaerial volcanos, including the architecture and distribution of the bodies where magma is stored and the network of conduits that transport melt between these accumulations and the surface, plays a fundamental role in all aspects of volcano construction and evolution, from igneous differentiation to hazard assessment. However, due to inaccessibility, little is known about the geometry of the magma bodies residing beneath subaerial volcanos. Mid-ocean ridges host the most extensive magmatic system on Earth, with 98% of its length below the ocean surface, which makes them an ideal target to be scanned by controlled-source marine seismic techniques. Beneath some portions of this vast system, the shallowest magma bodies are present and represented by long-linear Axial Magma Lenses (AML). It is at these shallow-most AMLs where dikes nucleate and connect the magma accumulations to the surface to result in an eruption. To explore the magma plumbing systems at mid-ocean ridges, we use 3-D multichannel seismic data across a mid-ocean ridge environment and apply advanced marine seismic techniques to develop the highest resolution reflection images of the AMLs so far. The data were collected across a magmatically dynamic portion of the East Pacific Rise at 9°50’N with documented dike intrusion and eruptions in 1991/1992 and 2005/06.The observations indicate that the magma reservoirs in the shallow crust are not represented by smooth bodies, but show strongly lineated topography that is spatially linked to the distribution of eruptive fissures and erupted lavas above. In the detailed topography, we find evidence for: 1) a dike root zone beneath where a caldera-like axial eruptive fissure zone is present, 2) deep excavation of this root zone within the primary eruption site for the last documented eruption, and 3) dikes rupturing from edges as well as the center of magma lenses. We also demonstrate that the distribution of additional, off-axis crustal magma accumulations further impact the stresses and melt budget at shallow-level magma accumulations leading to more frequent eruptions. Our results show that the mechanism behind eruptions along mid-ocean ridges is predominantly bottom-up and not fundamentally different from the eruptions’ mechanism at subaerial volcanoes. Considering the fine-scale morphology of shallow magma bodies will be critical for future generations of more realistic numerical models to aid in effective global volcanic hazard assessment and mitigation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".