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1. False Positives in the Identification of Dynamic Earthquake Triggering

   https://doi.org/10.1029/2025JB031566  

   Hardebeck, Jeanne L; DeSalvio, Nicolas D; Fan, Wenyuan; Barbour, Andrew J (July 2025, Journal of Geophysical Research: Solid Earth)

   Abstract Dynamic earthquake triggering is commonly identified through the temporal correlation between increased seismicity rates and global earthquakes that are possible triggering events. However, correlation does not imply causation. False positives may occur when unrelated seismicity rate changes coincidently occur at around the time of candidate triggers. We investigate the expected false positive rate in Southern California with globalM ≥ 6 earthquakes as candidate triggers. We compute the false positive rate by applying the statistical tests used by DeSalvio and Fan (2023),https://doi.org/10.1029/2023jb026487to synthetic earthquake catalogs with no real dynamic triggering. We find a false positive rate of ∼3.5%–8.5% when realistic earthquake clustering is present, consistent with the 95% confidence typically used in seismology. However, when this false positive rate is applied to the tens of thousands of spatial‐temporal windows in Southern California tested in DeSalvio and Fan (2023),https://doi.org/10.1029/2023jb026487, thousands of false positives are expected. The expected false positive occurrence is large enough to explain the observed apparent triggering following 70% of large global earthquakes (DeSalvio & Fan, 2023,https://doi.org/10.1029/2023jb026487), without requiring any true dynamic triggering. Aside from the known triggering from the nearby El Mayor‐Cucapah, Mexico, earthquake, the spatial and temporal characteristics of the reported triggering are indistinguishable from random false positives. This implies that best practice for dynamic triggering studies that depend on temporal correlation is to estimate the false positive rate and investigate whether the observed apparent triggering is distinguishable from the correlations that may occur by chance. 

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2. Improved Observations of Deep Earthquake Ruptures Using Machine Learning

   https://doi.org/10.1029/2023JB027334  

   Shi, Qibin; Denolle, Marine A. (December 2023, Journal of Geophysical Research: Solid Earth)

   Abstract Elevated seismic noise for moderate‐size earthquakes recorded at teleseismic distances has limited our ability to see their complexity. We develop a machine‐learning‐based algorithm to separate noise and earthquake signals that overlap in frequency. The multi‐task encoder‐decoder model is built around a kernel pre‐trained on local (e.g., short distances) earthquake data (Yin et al., 2022,https://doi.org/10.1093/gji/ggac290) and is modified by continued learning with high‐quality teleseismic data. We denoise teleseismic P waves of deep Mw5.0+ earthquakes and use the clean P waves to estimate source characteristics with reduced uncertainties of these understudied earthquakes. We find a scaling of moment and duration to beM₀ ≃ τ⁴, and a resulting strong scaling of stress drop and radiated energy with magnitude ( and ). The median radiation efficiency is 5%, a low value compared to crustal earthquakes. Overall, we show that deep earthquakes have weak rupture directivity and few subevents, suggesting a simple model of a circular crack with radial rupture propagation is appropriate. When accounting for their respective scaling with earthquake size, we find no systematic depth variations of duration, stress drop, or radiated energy within the 100–700 km depth range. Our study supports the findings of Poli and Prieto (2016,https://doi.org/10.1002/2016jb013521) with a doubled amount of earthquakes investigated and with earthquakes of lower magnitudes. 

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3. Regional Characteristics of Observable Foreshocks

   https://doi.org/10.1785/0220220122  

   Wetzler, Nadav; Brodsky, Emily E.; Chaves, Esteban J.; Goebel, Thomas; Lay, Thorne (October 2022, Seismological Research Letters)

   Abstract Measures of foreshock occurrence are systematically examined using earthquake catalogs for eight regions (Italy, southern California, northern California, Costa Rica, Onshore Japan, Alaska, Turkey, and Greece) after imposing a magnitude ≥3.0 completeness level. Foreshocks are identified using three approaches: a magnitude-dependent space + fixed-time windowing method, a nearest-neighbor clustering method, and a modified magnitude-dependent space + variable-time windowing method. The method with fixed-time windows systematically yields higher counts of foreshocks than the other two clustering methods. We find similar counts of foreshocks across the three methods when the magnitude aperture is equalized by including only earthquakes in the magnitude range M*−2≤ M< M*, in which M* is the mainshock magnitude. For most of the catalogs (excluding Italy and southern California), the measured b-values of the foreshocks of all region-specific mainshocks are lower by 0.1–0.2 than b-values of respective aftershocks. Allowing for variable-time windows results in relatively high probabilities of having at least one foreshock in Italy (∼43%–56%), compared to other regional catalogs. Foreshock probabilities decrease to 14%–41% for regions such as Turkey, Greece, and Costa Rica. Similar trends are found when requiring at least five foreshocks in a sequence to be considered. Estimates of foreshock probabilities for each mainshock are method dependent; however, consistent regional trends exist regardless of method, with regions such as Italy and southern California producing more observable foreshocks than Turkey and Greece. Some regions with relatively high background seismicity have comparatively low probabilities of detectable foreshock activity when using methods that account for variable background, possibly due to depletion of near-failure fault conditions by background activity. 

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4. Stress-driven recurrence and precursory moment-rate surge in caldera collapse earthquakes

   https://doi.org/10.1038/s41561-023-01372-3  

   Segall, Paul; Matthews, Mark V.; Shelly, David R.; Wang, Taiyi A.; Anderson, Kyle R. (March 2024, Nature Geoscience)

   Predicting the recurrence times of earthquakes and understanding the physical processes that immediately precede them are two outstanding problems in seismology. Although geodetic measurements record elastic strain accumulation, most faults have recurrence intervals longer than available measurements. Foreshocks provide the principal observations of processes before mainshocks, but variability between sequences limits generalizations of pre-failure behaviour. Here we analyse seismicity and deformation data for highly characteristic caldera collapse earthquakes from 2018 Kīlauea Volcano (Hawaii, USA), with a mean recurrence interval of 1.4 days. These events provide a unique test of stress-induced earthquake recurrence and document processes preceding mainshocks with magnitude greater than five. We show that recurrence intervals are well predicted by stress histories inferred from near-field deformation measurements and that cycle-averaged seismicity reveals a critical phase, minutes before mainshocks, where earthquakes grew larger and seismic moment rate surged dramatically. The average moment rate in the final 15 minutes (0.7% of the mean cycle duration) was 4.75 times the background, a highly significant change. We infer that as the average stress increased, ruptures were more likely to overcome geometric barriers and grow larger, leading to characteristic, whole-fault ruptures. These findings imply that stress heterogeneity influences both earthquake nucleation and growth, including on potentially hazardous tectonic faults. 

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5. Coherent Spatial Variations in the Productivity of Earthquake Sequences in California and Nevada

   https://doi.org/10.1785/0320230039  

   Trugman, Daniel T.; Ben-Zion, Yehuda (October 2023, The Seismic Record)

   Abstract Earthquakes are clustered in space and time, with individual sequences composed of events linked by stress transfer and triggering mechanisms. On a global scale, variations in the productivity of earthquake sequences—a normalized measure of the number of triggered events—have been observed and associated with regional variations in tectonic setting. Here, we focus on resolving systematic variations in the productivity of crustal earthquake sequences in California and Nevada—the two most seismically active states in the western United States. We apply a well-tested nearest-neighbor algorithm to automatically extract earthquake sequence statistics from a unified 40 yr compilation of regional earthquake catalogs that is complete to M ∼ 2.5. We then compare earthquake sequence productivity to geophysical parameters that may influence earthquake processes, including heat flow, temperature at seismogenic depth, complexity of quaternary faulting, geodetic strain rates, depth to crystalline basement, and faulting style. We observe coherent spatial variations in sequence productivity, with higher values in the Walker Lane of eastern California and Nevada than along the San Andreas fault system in western California. The results illuminate significant correlations between productivity and heat flow, temperature, and faulting that contribute to the understanding and ability to forecast crustal earthquake sequences in the area. 

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