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Science Advances

Science Advances: explore 5 source-linked works published from 2024 to 2026, with original documents and citations.

This collection is a preview while coverage and quality are evaluated.

Coverage and selection

Includes records with this source-supplied label or an explicit phrase match in their metadata. Matches indicate a mention, not proof that a paper uses a method or tests a material. Source versions are consolidated by DOI.

Sources: usgs. Collection updated 2026-09-15. Counts describe this index, not the complete source archives.

USGS2026

Widespread abyssal turbidites record megathrust earthquake-triggered landslides and coseismic deformation in the Cascadia subduction zone

Abyssal marine turbidites provide some of the longest and most spatially extensive records of subduction zone earthquake recurrence globally; however, correlation of these deposits over long distances and interpretation of synchronous emplacement requires both an understanding of the turbidite generating systems and precise dating. Here, we present an integrated suite of high-resolution bathymetry, subbottom profiles, and sediment cores from combined autonomous underwater vehicle, remotely operated vehicle, and ship-based studies at a key paleoseismic site in the southern Cascadia subduction zone. We demonstrate how widespread, earthquake-triggered landslides on the lower slope deposit discrete, proximal mass transport deposits (MTDs) that grade offshore into complex, interfingered abyssal turbidites, which correspond to records of megathrust earthquake history. We propose accretion and oversteepening of thrust folds on the lower slope both preconditions the slope to fail and provides a perpetual source of unstable material to fail during every earthquake cycle. Furthermore, we suggest the periodic and pervasive landsliding indicates coseismic deformation of the outer accretionary wedge during megathrust rupture.

California, Oregon↗

USGS2025

Rapid fault healing from cementation controls the dynamics of deep slow slip and tremor

Despite its status as one of the most important discoveries in geophysics, the physical mechanism(s) responsible for slow slip events (SSEs) are not well understood. Here, we synthesize observations of deep SSEs in the Cascadia Subduction Zone and argue that rapid, cohesive fault strengthening may control the dynamics of deep SSEs. Cohesive strength is frequently ignored in constitutive laws used to describe fault rheology in numerical simulations of earthquakes and SSEs alike. To demonstrate its importance, we perform and analyze a suite of petrological experiments that simulate fault healing under representative pressure and temperature conditions. We show that significant cohesive strength recovery caused by dissolution-precipitation processes occurs on timescales of just a few hours. Together, our experimental and observational results support the idea that cohesion is a key component of fault strength under SSE conditions and highlight the need for its inclusion in both future experiments and numerical models of fault slip.

British Columbia, Washington↗

USGS2025

Long-term dynamics of earthquake swarms in the Yellowstone caldera

The factors controlling the spatial distribution and temporal evolution of earthquake swarms in volcanic systems remain unclear. We leverage leading-edge deep learning algorithms and a detailed three-dimensional velocity model to construct a 15-year high-resolution earthquake catalog of the Yellowstone caldera region. More than half of the region’s earthquakes are clustered into swarm-like families characterized by episodes of hypocenter expansion and migration. Adjacent earthquake swarms, separated by long quiescent periods, are found to be a dominant feature. We suggest that these swarms are controlled by the interplay between slowly diffusing aqueous fluids and rapid episodic fluid injections, which may result from the breaking of permeability seals. Our analyses also indicate that clustered seismicity beneath the caldera occurs on relatively immature, rougher fault structures, compared to more planar faults outside. Our results provide additional context for understanding seismicity in hydrothermal systems, highlighting the key role played by long-term fluid diffusion processes in driving the occurrence of earthquake swarms.

Idaho, Montana, Wyoming↗

USGS2025

Overcoming the data limitations in landslide susceptibility modelling

Data-driven models widely used for assessing landslide susceptibility are severely limited by the landslide and environmental data needed to create them. They rely on inventories of past landslide locations, which are difficult to collect and often nonrepresentative. Furthermore, susceptibility maps are most needed in regions without the means to assemble an inventory. To overcome these challenges, we develop a method for assessing shallow landslide susceptibility based on a probabilistic morphometric analysis of the landscape’s topography, rather than the characteristics of landslides. The model assumes that hillslopes with higher relief and gradient compared to the surrounding landscape are more prone to landslides. We demonstrate the superior performance of this approach over contrasting data-driven models across the northwestern United States. As our morphometric model only requires elevation data, it overcomes the major limitations of data-driven models and facilitates the creation of effective susceptibility models in areas where it was previously unfeasible.

Oregon, Washington↗

USGS2024

Evaluation of the lithium resource in the Smackover Formation brines of southern Arkansas using machine learning

Global demand for lithium, the primary component of lithium-ion batteries, greatly exceeds known supplies, and this imbalance is expected to increase as the world transitions away from fossil fuel energy sources. High concentrations of lithium in brines have been observed in the Smackover Formation in southern Arkansas (>400 milligrams per liter). We used published and newly collected brine lithium concentration data to train a random forest machine-learning model using geologic, geochemical, and temperature explanatory variables and create a map of predicted lithium concentrations in Smackover Formation brines across southern Arkansas. Using these predicted lithium maps with reservoir parameters and geologic information, we calculated that there are 5.1 to 19 million tons of lithium in Smackover Formation brines in southern Arkansas, which represents 35 to 136% of the current US lithium resource estimate. Based on these calculations, in 2022, 5000 tons of dissolved lithium were brought to the surface within brines as waste streams of the oil, gas, and bromine industries.

Arkansas↗

Compare source metadata on this page

Work	Published	Source identifier	Source
Widespread abyssal turbidites record megathrust earthquake-triggered landslides and coseismic deformation in the Cascadia subduction zone	2026-01-14	70274201	usgs
Rapid fault healing from cementation controls the dynamics of deep slow slip and tremor	2025-11-19	70277751	usgs
Long-term dynamics of earthquake swarms in the Yellowstone caldera	2025-07-18	70271168	usgs
Overcoming the data limitations in landslide susceptibility modelling	2025	70263799	usgs
Evaluation of the lithium resource in the Smackover Formation brines of southern Arkansas using machine learning	2024	70259385	usgs

These are bibliographic comparisons, not experimental rankings. Follow the original document for methods and conditions.