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Contribution of background seismicity to forearc uplift

Abstract

Rock exhumation and surface uplift over subduction zones require part of the stresses to cause crustal thickening within the wedge and/or through basal accretion. Although accumulated elastic strain around subduction zones is released through megathrust earthquakes and related aftershocks, these large events often result in no permanent forearc surface uplift. Nevertheless, energy is also released by more frequent and dispersed background seismicity, a signal that is often overlooked. Here we investigate the variability of this energy along the Peru–Chile and Japan margins. We find that the pattern of background seismicity correlates with the margin-parallel long-wavelength wedge geometry and with published estimates of geologic-timescale coastal uplift. Furthermore, the orientation of the principal stresses related to these background events is consistent with contractional seismicity, predominantly located at the deep (30–60 km) plate interface depth. Taken together, these results indicate that background seismicity is associated with crustal thickening during the megathrust interseismic period. This mechanism may contribute substantially to the surface uplift of subduction margins over geologic timescales.

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Fig. 1: Topography, tectonic architecture and earthquake frequency of the studied margins.
Fig. 2: Trench-parallel changes in background seismic moment and proxies for long-term uplift.
Fig. 3: Depth distribution of events.
Fig. 4: Proposed model of subduction dynamics and related crustal deformation in the analysed margins.

Data availability

The raw data used in this study (seismic catalogue, digital elevation models, coastal uplift data and shelf-break location data) are freely available and accessible at their respective cited references/URLs. Source data are provided with this paper.

Code availability

Data analyses and plotting were performed in Python using the packages Matplotlib64, GeoPandas65 and functions from the ArcPy library of the software ArcGIS. All figures were additionally edited in the software Affinity Designer. The DBSCAN clustering algorithm is available in the Python library Scikit-learn54. The mathematical steps necessary to reproduce the results are illustrated in Main and Methods sections. Python scripts that integrate the described workflow are available from the corresponding author upon reasonable request.

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Acknowledgements

Research was funded through the Swiss National Science Foundation Early Postdoc Mobility grant no. 178460 awarded to A.M. The authors thank A. Dielforder and O. Oncken for inspiring discussions, as well as M. Farías and V. Mouslopoulou for constructive comments.

Author information

Authors and Affiliations

Authors

Contributions

A.M. developed the study, collected and analysed the data. A.M. and T.A.E. contributed to writing the manuscript.

Corresponding author

Correspondence to Andrea Madella.

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The authors declare no competing interests.

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Peer review information Primary Handling Editor: Stefan Lachowycz. Nature Geoscience thanks Vasiliki Mouslopoulou and Marcelo Farías for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 Margin-parallel variations of background seismicity and proxies for long-term uplift along the Peru-Chile margin.

BSM (shades of black) is compared to changes of topographic slope (shades of blue), basal friction (shades of green), inverse of the trench-shelf break distance (shades of magenta) and long-term uplift rates from Melnick12 (shades of purple). Smoothing length increases with transparency from 150 to 300 km. Correlation coefficients R refer to the 250 km smoothing length (all p-values < 0.05, except where in italics).

Source data

Extended Data Fig. 2 Margin-parallel variations of background seismicity and proxies for long-term uplift along the Japan margin.

BSM (shades of black) is compared to changes of topographic slope (shades of blue), basal friction (shades of green), inverse of the trench-shelf break distance (shades of magenta) and long-term uplift rates from Tam & Yokohama26 (shades of purple). Smoothing length increases with transparency from 150 to 300 km. Correlation coefficients R refer to the 250 km smoothing length (all p-values < 0.05, except where in italics).

Source data

Extended Data Fig. 3 Plots of background seismic moment (y axes) against each of the analyzed proxy for long-term uplift (x axis) in the Peru-Chile margin.

The circles sample the margin with a margin-parallel 25-km step size, with a 250-km-smoothing length. Color coding refers to the latitude along the dashed yellow line in Fig. 1 of the main text. All Pearson correlation coefficients are associated with p-values < 0.05, except where in italics.

Source data

Extended Data Fig. 4 Plots of background seismic moment (y axes) against each of the analyzed proxy for long-term uplift (x axis) in the Japan margin.

The circles sample the margin with a margin-parallel 25-km step size, with a 250-km-smoothing length. Color coding refers to the latitude along the dashed yellow line in Fig. 1 of the main text. All Pearson correlation coefficients are associated with p-values < 0.05, except where in italics.

Source data

Extended Data Fig. 5 Stereographic projection of maximum and minimum (σ1: white circles, σ3: black circles) compressive stress orientations from focal mechanisms of background events.

The plotted 105 (Peru-Chile) and 165 (Japan) focal mechanisms refer exclusively to events from the considered background seismicity catalogues. They are in the 30–60 km-depth range and within 15 km vertical distance from the plate interface. For illustrative purposes, the shading shows the beach ball diagram obtained for the most frequent orientation of the focal mechanisms. Red arrows inform the regional convergence direction62,63.

Source data

Supplementary information

Supplementary information

Information on how to download the raw seismic catalogues. Supplementary Tables 1–4 and Figs. 1 and 2.

Supplementary Table 5

A .csv file containing latitude, longitude, elevation, topographic slope angle, slab dip angle, slab depth and effective coefficient of basal friction for the analysed portion of the Japan margin.

Supplementary Table 6

A .csv file containing latitude, longitude, elevation, topographic slope angle, slab dip angle, slab depth and effective coefficient of basal friction for the analysed portion of the Peru–Chile margin.

Source data

Source Data Fig. 2

Line Plot Source Data

Source Data Fig. 3

Statistical Source Data

Source Data Extended Data Fig. 1

Line Plot Source Data

Source Data Extended Data Fig. 2

Line Plot Source Data

Source Data Extended Data Fig. 3

Scatter Plot Source Data

Source Data Extended Data Fig. 4

Scatter Plot Source Data

Source Data Extended Data Fig. 5

Stereographic Plot Source Data

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Madella, A., Ehlers, T.A. Contribution of background seismicity to forearc uplift. Nat. Geosci. 14, 620–625 (2021). https://doi.org/10.1038/s41561-021-00779-0

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