Sea Level Changes Affect Seismicity Rates in a Hydrothermal System Near Istanbul

Small stress changes such as those from sea level fluctuations can be large enough to trigger earthquakes. If small and large earthquakes initiate similarly, high-resolution catalogs with low detection thresholds are best suited to illuminate such processes. Below the Sea of Marmara section of the North Anatolian Fault, a segment of urn:x-wiley:00948276:media:grl65397:grl65397-math-0001150 km is late in its seismic cycle. We generated high-resolution seismicity catalogs for a hydrothermal region in the eastern Sea of Marmara employing AI-based and template matching techniques to investigate the link between sea level fluctuations and seismicity over 6 months. All high resolution catalogs show that local seismicity rates are larger during time periods shortly after local minima of sea level, when it is already rising. Local strainmeters indicate that seismicity is promoted when the ratio of differential to areal strain is the largest. The strain changes from sea level variations, on the order of 30–300 nstrain, are sufficient to promote seismicity

Sex Attractant Pheromone of the House Fly: Isolation, Identification and Synthesis

A sex pheromone isolated from the cuticle and feces of the female house fly attracts the male fly; it has been identified as (Z)-9-tricosene. Chemical and biological comparisons of the natural and synthesized compounds show that they are identical

Machine learning and earthquake forecasting—next steps

A new generation of earthquake catalogs developed through supervised machine-learning illuminates earthquake activity with unprecedented detail. Application of unsupervised machine learning to analyze the more complete expression of seismicity in these catalogs may be the fastest route to improving earthquake forecasting

Sex Attractant Pheromone of the House Fly: Isolation, Identification and Synthesis

A sex pheromone isolated from the cuticle and feces of the female house fly attracts the male fly; it has been identified as (Z)-9-tricosene. Chemical and biological comparisons of the natural and synthesized compounds show that they are identical

On the Use of High‐Resolution and Deep‐Learning Seismic Catalogs for Short‐Term Earthquake Forecasts: Potential Benefits and Current Limitations

Enhanced earthquake catalogs provide detailed images of evolving seismic sequences. Currently, these data sets take some time to be released but will soon become available in real time. Here, we explore whether and how enhanced seismic catalogs feeding into established short-term earthquake forecasting protocols may result in higher predictive skill. We consider three enhanced catalogs for the 2016–2017 Central Italy sequence, featuring a bulk completeness lower by at least two magnitude units compared to the real-time catalog and an improved hypocentral resolution. We use them to inform a set of physical Coulomb Rate-and-State (CRS) and statistical Epidemic-Type Aftershock Sequence (ETAS) models to forecast the space-time occurrence of M3+ events during the first 6 months of the sequence. We track model performance using standard likelihood-based metrics and compare their skill against the best-performing CRS and ETAS models among those developed with the real-time catalog. We find that while the incorporation of the triggering contributions from new small magnitude detections of the enhanced catalogs is beneficial for both types of forecasts, these models do not significantly outperform their respective near real-time benchmarks. To explore the reasons behind this result, we perform targeted sensitivity tests that show how (a) the typical spatial discretizations of forecast experiments (urn:x-wiley:21699313:media:jgrb55931:jgrb55931-math-00012 km) hamper the ability of models to capture highly localized secondary triggering patterns and (b) differences in earthquake parameters (i.e., magnitude and hypocenters) reported in different catalogs can affect forecast evaluation. These findings will contribute toward improving forecast model design and evaluation strategies for next-generation seismic catalogs. Key Points We compare retrospective forecast models informed by enhanced versus real-time earthquake catalogs for the 2016–2017 Central Italy sequence To realize the benefits of high-resolution catalogs, models should integrate advanced experimental setups, like finer spatial grids Results stimulate further testing on the optimal design of next-generation forecast models based on enhanced seismic catalog

Spatial correlation of aftershock locations and on-fault main shock properties

[1] We quantify the correlation between spatial patterns of aftershock hypocenter locations and the distribution of coseismic slip and stress drop on a main shock fault plane using two nonstandard statistical tests. Test T1 evaluates if aftershock hypocenters are located in low‐slip regions (hypothesis H1), test T2 evaluates if aftershock hypocenters occur in regions of increased shear stress (hypothesis H2). In the tests, we seek to reject the null hypotheses H0: Aftershock hypocenters are not correlated with (1) low‐slip regions or (2) regions of increased shear stress, respectively. We tested the hypotheses on four strike‐slip events for which multiple earthquake catalogs and multiple finite fault source models of varying accuracy exist. Because we want to retain earthquake clustering as the fundamental feature of aftershock seismicity, we generate slip distributions using a random spatial field model and derive the stress drop distributions instead of generating seismicity catalogs. We account for uncertainties in the aftershock locations by simulating them within their location error bounds. Our findings imply that aftershocks are preferentially located in regions of low‐slip (u ≤ equation imageu max) and of increased shear stress (Δσ < 0). In particular, the correlation is more significant for relocated than for general network aftershock catalogs. However, the results show that stress drop patterns provide less information content on aftershock locations. This implies that static shear stress change of the main shock may not be the governing process for aftershock genesis.ISSN:2169-9313ISSN:0148-0227ISSN:2169-935

Laboratory earthquake forecasting. A machine learning competition

Earthquake prediction, the long-sought holy grail of earthquake science, continues to confound Earth scientists. Could we make advances by crowdsourcing, drawing from the vast knowledge and creativity of the machine learning (ML) community? We used Google’s ML competition platform, Kaggle, to engage the worldwide ML community with a competition to develop and improve data analysis approaches on a forecasting problem that uses laboratory earthquake data. The competitors were tasked with predicting the time remaining before the next earthquake of successive laboratory quake events, based on only a small portion of the laboratory seismic data. The more than 4,500 participating teams created and shared more than 400 computer programs in openly accessible notebooks. Complementing the now well-known features of seismic data that map to fault criticality in the laboratory, the winning teams employed unexpected strategies based on rescaling failure times as a fraction of the seismic cycle and comparing input distribution of training and testing data. In addition to yielding scientific insights into fault processes in the laboratory and their relation with the evolution of the statistical properties of the associated seismic data, the competition serves as a pedagogical tool for teaching ML in geophysics. The approach may provide a model for other competitions in geosciences or other domains of study to help engage the ML community on problems of significance

Triggering of the 2014 M_w7.3 Papanoa earthquake by a slow slip event in Guerrero, Mexico

Since their discovery two decades ago, slow slip events have been shown to play an important role in accommodating strain in subduction zones. However, the physical mechanisms that generate slow slip and the relationships with earthquakes are unclear. Slow slip events have been recorded in the Guerrero segment of the Cocos–North America subduction zone. Here we use inversion of position time series recorded by a continuous GPS network to reconstruct the evolution of aseismic slip on the subduction interface of the Guerrero segment. We find that a slow slip event began in February 2014, two months before the magnitude (M_w) 7.3 Papanoa earthquake on 18 April. The slow slip event initiated in a region adjacent to the earthquake hypocentre and extended into the vicinity of the seismogenic zone. This spatio-temporal proximity strongly suggests that the Papanoa earthquake was triggered by the ongoing slow slip event. We demonstrate that the triggering mechanism could be either static stress increases in the hypocentral region, as revealed by Coulomb stress modelling, or enhanced weakening of the earthquake hypocentral area by the slow slip. We also show that the plate interface in the Guerrero area is highly coupled between slow slip events, and that most of the accumulated strain is released aseismically during the slow slip episodes