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The moment magnitude $(M_w )$ 7.9 Fort Tejon earthquake of 1857, with a ~350-kilometer-long surface rupture, was the most recent major earthquake along the south-central San Andreas Fault, California. Based on previous measurements of its surface slip distribution, rupture along the ~60-kilometer-long Carrizo segment was thought to control the recurrence of 1857-like earthquakes. New high-resolution topographic data show that the average slip along the Carrizo segment during the 1857 event was 5.3 ± 1.4 meters, eliminating the core assumption for a linkage between Carrizo segment rupture and recurrence of major earthquakes along the south-central San Andreas Fault. Earthquake slip along the Carrizo segment may recur in earthquake clusters with cumulative slip of ~5 meters.

Advancing the capabilities of earthquake nowcasting, the real-time forecasting of seismic activities, remains crucial for reducing casualties. This multifaceted challenge has recently gained attention within the deep learning domain, facilitated by the availability of extensive earthquake datasets. Despite significant advancements, the existing literature on earthquake nowcasting lacks comprehensive evaluations of pre-trained foundation models and modern deep learning architectures; each focuses on a different aspect of data, such as spatial relationships, temporal patterns, and multi-scale dependencies. This paper addresses the mentioned gap by analyzing different architectures and introducing two innovative approaches called Multi Foundation Quake and GNNCoder. We formulate earthquake nowcasting as a time series forecasting problem for the next 14 days within 0.1-degree spatial bins in Southern California. Earthquake time series are generated using the logarithm energy released by quakes, spanning 1986 to 2024. Our comprehensive evaluations demonstrate that our introduced models outperform other custom architectures by effectively capturing temporal-spatial relationships inherent in seismic data. The performance of existing foundation models varies significantly based on the pre-training datasets, emphasizing the need for careful dataset selection. However, we introduce a novel method, Multi Foundation Quake, that achieves the best overall performance by combining a bespoke pattern with Foundation model results handled as auxiliary streams.

Yes Plain Language Summary The question of whether earthquake occurrence is random in time, or perhaps chaotic with order hidden in the chaos, is of major importance to the determination of risk from these events. It was shown many years ago that if aftershocks are removed from the earthquake catalogs, what remains are apparently events that occur at random time intervals, and therefore not predictable in time. In the present work, we enlist machine learning methods using Receiver Operating Characteristic analysis. With these methods, probabilities of large events and their associated information value can be computed. Here information value is defined using Shannon entropy, shown by Claude Shannon to define the surprise value of a communication such as a string of computer bits. Random messages can be shown to have high entropy, surprise value, or uncertainty, whereas low entropy is associated with reduced uncertainty and high reliability. An earthquake nowcast probability associated with reduced uncertainty and greater reliability is most desirable. Examples of the latter could be the statements that there is a 90% probability of a major earthquake within 3 years, or a 5% chance of a major earthquake within 1 year. Despite the random intervals between major earthquakes, we find that it is possible to make low uncertainty, high reliability statements on current hazard by the use of machine learning methods using catalog data from 1970‐present. Key Points Interval statistics have been used to conclude that major earthquakes are random events in time and cannot be anticipated or predicted Machine learning is a powerful new technique that enhances our ability to understand the information content of earthquake catalogs Using small earthquake rates, we show that catalogs contain significant information on predictability of future large earthquakes

This paper describes the methods used to estimate positions, velocities, breaks, and seasonal terms from daily Global Navigation Satellite System (GNSS) measurements. Break detection and outlier removal have been automated so that decades of daily measurements from thousands of stations can be processed in a few hours. New measurements are added, and parameters are updated every week. Model parameters allow separation of interseismic, annual, coseismic, and postseismic signals. Tools available through GeoGateway (http://geo-gateway.org) allow rapid visualization and analysis of these terms for results that can be subsetted in time or space. Results show highly variable and nonlinear motion for GPS stations in southern California. The variable motion is related to seasonal motions, distributed tectonic motion, earthquakes, and postseismic motions that can continue for years. In some areas results suggest that additional processes are responsible for the observed motions. In general, following earthquakes, stations return to their long‐term motions after 2–3 years, though some exceptions occur. The use of the tools shows nonlinear motion in the Salton Trough of southern California related to the 2010 M7.2 El Mayor‐Cucapah earthquake, 2012 Brawley earthquake swarm, and a creep event on the Superstition Hills fault in 2017. Key Points Positions, velocities, breaks, and seasonal terms for thousands of GNSS stations are updated every week These results can be used to study interseismic plate motion, coseismic deformation, postseismic deformation, and seasonal variations The use of these tools shows highly variable nonlinear motion of GPS stations in southern California

Nowcasting is a term originating from economics, finance, and meteorology. It refers to the process of determining the uncertain state of the economy, markets or the weather at the current time by indirect means. In this paper, we describe a simple two‐parameter data analysis that reveals hidden order in otherwise seemingly chaotic earthquake seismicity. One of these parameters relates to a mechanism of seismic quiescence arising from the physics of strain‐hardening of the crust prior to major events. We observe an earthquake cycle associated with major earthquakes in California, similar to what has long been postulated. An estimate of the earthquake hazard revealed by this state variable time series can be optimized by the use of machine learning in the form of the Receiver Operating Characteristic skill score. The ROC skill is used here as a loss function in a supervised learning mode. Our analysis is conducted in the region of 5° × 5° in latitude‐longitude centered on Los Angeles, a region which we used in previous papers to build similar time series using more involved methods (Rundle & Donnellan, 2020, https://doi.org/10.1029/2020EA001097; Rundle, Donnellan et al., 2021, https://doi.org/10.1029/2021EA001757; Rundle, Stein et al., 2021, https://doi.org/10.1088/1361-6633/abf893). Here we show that not only does the state variable time series have forecast skill, the associated spatial probability densities have skill as well. In addition, use of the standard ROC and Precision (PPV) metrics allow probabilities of current earthquake hazard to be defined in a simple, straightforward, and rigorous way. Plain Language Summary Earthquake nowcasting refers to the determination of hazard for major earthquakes at the present time, the recent past, and the near future. Nowcasting is an idea borrowed from economics, markets, and meteorology, where it has been frequently used. In this paper, we show that there is order hidden within chaotic earthquake seismicity using a very simple transformation of the data. Small earthquakes appear to transition from unstable stick‐slip events that produce seismic waves, to stable sliding where no seismic waves are produced. Our hypothesis is that this transition is due to a material phenomenon called strain‐hardening, that is frequently observed in laboratory rock mechanics experiments. The result is a state variable time series, computed over the last 51 years in California, that strongly resembles the long‐anticipated cycle of stress accumulation and release. Using supervised machine learning techniques, we can optimize the two‐parameter model. From that optimized model, we can rigorously calculate the probability of current hazard from major earthquakes. Extending these methods, we can also compute spatial hazard as well. The result is a new method for assessing earthquake hazard that may be useful for a variety of applications. Key Points “Chaotic” seismicity contains hidden structure in the form of state variable time series Standard data science methods can be used to convert the time series to probabilities Both temporal and spatial probabilities can be computed

The spatial and temporal distribution of fault slip is a critical parameter in earthquake source models. Previous geomorphic and geologic studies of channel offset along the Carrizo section of the south central San Andreas Fault assumed that channels form more frequently than earthquakes occur and suggested that repeated large-slip earthquakes similar to the 1857 Fort Tejon earthquake illustrate typical fault behavior. We found that offset channels in the Carrizo Plain incised less frequently than they were offset by earthquakes. Channels have been offset by successive earthquakes with variable slip since approximately 1400. This nonuniform slip history reveals a more complex rupture history than previously assumed for the structurally simplest section of the San Andreas Fault.

This study investigated the relationship between circulating soluble receptor for advanced glycation end products (sRAGE) and parameters of bone health in patients with Charcot neuroarthropathy (CNA). Eighty men (aged 55.3±9.0 years), including 30 healthy control subjects, 30 type 2 diabetic patients without Charcot, and 20 type 2 diabetic patients with stage 2 (nonacute) CNA, underwent evaluations of peripheral and autonomic neuropathy, nerve conduction, markers of bone turnover, bone mineral density, and bone stiffness of the calcaneus. CNA patients had worse peripheral and autonomic neuropathy and a lower bone stiffness index than diabetic or control individuals (77.1, 103.3, and 105.1, respectively; P<0.05), but no difference in bone mineral density (P>0.05). CNA subjects also had lower sRAGE levels than control (162 vs. 1,140 pg/mL; P<0.01) and diabetic (162 vs. 522 pg/mL; P<0.05) subjects, and higher circulating osteocalcin levels. CNA patients had significantly lower circulating sRAGE, with an accompanying increase in serum markers of bone turnover, and reduced bone stiffness in the calcaneus not accompanied by reductions in bone mineral density. These data suggest a failure of RAGE defense mechanisms against oxidative stress in diabetes. Future studies should determine if medications that increase sRAGE activity could be useful in mitigating progression to CNA.

Biogenic reefs are important for habitat provision and coastal protection. Long‐term datasets on the distribution and abundance of Sabellaria alveolata (L.) are available from Britain. The aim of this study was to combine historical records and contemporary data to (1) describe spatiotemporal variation in winter temperatures, (2) document short‐term and long‐term changes in the distribution and abundance of S. alveolata and discuss these changes in relation to extreme weather events and recent warming, and (3) assess the potential for artificial coastal defense structures to function as habitat for S. alveolata. A semi‐quantitative abundance scale (ACFOR) was used to compare broadscale, long‐term and interannual abundance of S. alveolata near its range edge in NW Britain. S. alveolata disappeared from the North Wales and Wirral coastlines where it had been abundant prior to the cold winter of 1962/1963. Population declines were also observed following the recent cold winters of 2009/2010 and 2010/2011. Extensive surveys in 2004 and 2012 revealed that S. alveolata had recolonized locations from which it had previously disappeared. Furthermore, it had increased in abundance at many locations, possibly in response to recent warming. S. alveolata was recorded on the majority of artificial coastal defense structures surveyed, suggesting that the proliferation of artificial coastal defense structures along this stretch of coastline may have enabled S. alveolata to spread across stretches of unsuitable natural habitat. Long‐term and broadscale contextual monitoring is essential for monitoring responses of organisms to climate change. Historical data and gray literature can be invaluable sources of information. Our results support the theory that Lusitanian species are responding positively to climate warming but also that short‐term extreme weather events can have potentially devastating widespread and lasting effects on organisms. Furthermore, the proliferation of coastal defense structures has implications for phylogeography, population genetics, and connectivity of coastal populations. This study presents data from 49 locations that were surveyed using the same sampling protocols during three different surveys spanning a warming period between 1984 and 2012. It describes the changes in distribution of an important ecosystem engineer in relation to short‐term extreme weather events, recent warming and the construction of a network of artificial coastal defence structures near its northern range edge in Britain. We present new information regarding the temporal stability of this important habitat that has not previously been recorded in the published literature and it is anticipated that this will be of significant use to those tasked with the management and protection of these habitats.

We use UAVSAR interferograms to characterize fault slip, triggered by the Mw 7.2 El Mayor‐Cucapah earthquake on the 1 San Andreas Fault in the Coachella Valley providing comprehensive maps of short‐term geodetic surface deformation that complement in situ measurements. Creepmeters and geological mapping of fault offsets on Durmid Hill recorded 4 and 8 mm of average triggered slip respectively on the fault, in contrast to radar views that reveal significant off‐fault dextral deformation averaging 20 mm. Unlike slip in previous triggered slip events on the southernmost San Andreas fault, dextral shear in 2010 is not confined to transpressional hills in the Coachella valley. Edge detection and gradient estimation applied to the 50‐m‐sampled interferogram data identify the location (to 20 m) and local strike (to <4°) of secondary surface ruptures. Transverse curve fitting applied to these local detections provides local estimates of the radar‐projected dextral slip and a parameter indicating the transverse width of the slip, which we equate with the depth of subsurface shear. These estimates are partially validated by fault‐transverse interferogram profiles generated using the GeoGateway UAVSAR tool, and appear consistent for radar‐projected slip greater than about 5 mm. An unexpected finding is that creep and triggered slip on the San Andreas fault terminate in the shallow subsurface below a surface shear zone that resists the simple expression of aseismic fault slip. We introduce the notion of a surface locking depth above which fault slip is manifest as distributed shear, and evaluate its depth as 6–27 m. Plain Language Summary An aircraft‐mounted imaging radar relies on a highly sensitive reflected interference pattern to form precise maps of surface changes. Images obtained from flights before and after the April 4, 2010 magnitude 7.2 El Mayor‐Cucapah earthquake view the San Andreas Fault in California's Coachella Valley. Although the earthquake occurred 75 miles to the south of this fault, computer vision brings out complicated reshaping near and on the fault. The quiet deformation is concentrated in patches along the fault between the Mecca Hills and the Salton Sea, and matches the sense of slip expected from long‐known continental plate motions surrounding this region. Slip at the fault surface are radar‐measured at less than 3/4\" but when compared to measurements in the broader fault zone we find that slip triggered by the distant earthquake is usually confined below a level 30 feet beneath the surface, reshaping a zone around the fault more than one hundred and 80 feet wide. This newly discovered barrier may be an interwoven network of clay lumps in the fault zone. Our finding explains why the process of slow fault slip is rarely obvious on the surface, but is usually observed as a series of discontinuous cracks following the fault. Key Points Airborne radar interferograms map displacement in the Coachella Valley using visits before and after the El Mayor Cucapah earthquake UAVSAR‐determined triggered slip on southern San Andreas and Hidden Spring fault has distinct slip zones and gaps Concentrated deformation at the San Andreas Fault displays a variable‐width deformation zone

PurposeEvery year several thousand female cadets participate in the Combined Cadet Force (CCF) in the UK, but little is known about the impact that this experience has on the subsequent employability of the female cadets. This study aimed to understand the perceptions of academic teenage girls from one all-female unit of their participation in CCF and the personal benefit or otherwise in relation to their ultimate employability.Design/methodology/approachThis qualitative study used semi-structured interviews to explore the experiences of 10 young women who had participated in CCF for at least three years. Data were analysed using a thematic analysis.FindingsParticipants were effusive about the transformative effects of CCF in relation to personal confidence, recognising transferable skills and raising personal aspiration, all key elements to employability, particularly for women. They also considered they had gained future workplace advantage having had opportunity to trial leadership strategies in mixed gender teams, an experience unavailable elsewhere to them. Loyalty to the contingent pervaded every discussion and the importance of team goals, although this level of selfless commitment may be detrimental to employability, subsuming their personal interests to the greater good.Originality/valueResearch into the benefit or otherwise of teenage girls' extra-curricular activities is scarce, and this is the first study, to the authors' knowledge, that explores the perceptions of the impact their time in CCF had on their graduate employability skills.