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We determine optimal on-fault earthquake spatial distributions using a combinatorial method that minimizes the long-term cumulative stress resolved on the fault. An integer-programming framework was previously developed to determine the optimal arrangement of a millennia-scale earthquake sample that minimizes the misfit to a target slip rate determined from geodetic data. The resulting cumulative stress from just slip-rate optimization, however, can greatly exceed fault strength estimates. Therefore, we add an objective function that minimizes cumulative stress and broad stress constraints to limit the solution space. We find that there is a trade-off in the two objectives: minimizing the cumulative stress on a fault within fault strength limits concentrates earthquakes in specific areas of the fault and results in excursions from the target slip rate. Both slip-rate and stress objectives can be combined in either a weighted or lexicographic (hierarchical) method. Using a combination of objectives, we demonstrate that a Gutenberg–Richter sample of earthquakes can be arranged on a constant slip-rate finite fault with minimal stress and slip-rate residuals. We apply this method to determine the optimal arrangement of earthquakes on the variable slip-rate Nankai megathrust over 5000 yr. The sharp decrease in slip rate at the Tokai section of the fault results in surplus cumulative stress under all scenarios. Using stress optimization alone restricts this stress surplus to the northeast end of the fault at the expense of decreasing the slip rate away from the target slip rate at the southwest end of the fault. A combination of both slip-rate and stress objectives provides an adequate fit to the data, although alternate model formulations for the fault are needed at the Tokai section to explain persistent excess cumulative stress. In general, incorporating stress objectives and constraints into the integer-programming framework adds an important aspect of fault physics to the resulting earthquake rupture forecasts.

Coseismic stress changes have been the primary physical principle used to explain aftershocks and triggered earthquakes. However, this method does not adequately forecast earthquake rates and diverse rupture populations when subjected to formal testing. We show that earthquake forecasts can be impaired by assumptions made in physics-based models such as the existence of hypothetical optimal faults and regional scale invariability of the stress field. We compare calculations made under these assumptions along with different realizations of a new conceptual triggering model that features a complete assay of all possible ruptures. In this concept, there always exists a set of theoretical planes that has positive failure stress conditions under a combination of background and coseismic static stress change. In the Earth, all of these theoretical planes may not exist, and if they do, they may not be ready to fail. Thus, the actual aftershock plane may not correspond to the plane with the maximum stress change value. This is consistent with observations that mainshocks commonly activate faults with exotic orientations and rakes. Our testing ground is the M 7.2, 2010 El Mayor–Cucapah earthquake sequence that activated multiple diverse fault populations across the United States–Mexico border in California and Baja California. We carry out a retrospective test involving 748 M≥3.0 triggered earthquakes that occurred during a 3 yr period after the mainshock. We find that a probabilistic expression of possible aftershock planes constrained by premainshock rupture patterns is strongly favored (89% of aftershocks consistent with static stress triggering) versus an optimal fault implementation (35% consistent). Results show that coseismic stress change magnitudes do not necessarily control earthquake triggering, instead we find that the summed background stress and coseismic stress change promotes diverse ruptures. Our model can thus explain earthquake triggering in regions where optimal plane mapping shows coseismic stress reduction.

Alzheimer’s disease (AD) involves pathological processing of amyloid precursor protein (APP) into amyloid-β and microtubule associated protein Tau (MAPT) into hyperphosphorylated Tau tangles leading to neurodegeneration. Only 5% of AD cases are familial making it difficult to predict who will develop the disease thereby hindering our ability to treat the causes of the disease. A large population who almost certainly will, are those with Down syndrome (DS), who have a 90% lifetime incidence of AD. DS is caused by trisomy of chromosome 21 resulting in three copies of APP and other AD-associated genes, like dual specificity tyrosine-phosphorylation-regulated kinase 1A (DYRK1A) overexpression. This implies that DYRK1a inhibitors may have therapeutic potential for DS and AD, however It is not clear how overexpression of each of these genes contributes to the pathology of each disease as well as how effective a DYRK1A inhibitor would be at suppressing any of these. To address this knowledge gap, we used Drosophila models with human Tau, human amyloid-β or fly DYRK1A (minibrain (mnb)) neuronal overexpression resulting in photoreceptor neuron degeneration, premature death, decreased locomotion, sleep and memory loss. DYRK1A small molecule Type 1 kinase inhibitors (DYR219 and DYR533) were effective at suppressing these disease relevant phenotypes confirming their therapeutic potential.

Measuring variations of seismic attenuation over time provides unique insights into the dynamic state of stress of the Earth’s crust vs depth. We analyze seismometric data from earthquakes of the 2...

SUMMARYCombinatorial methods are used to determine the spatial distribution of earthquake magnitudes on a fault whose slip rate varies along strike. Input to the problem is a finite sample of earthquake magnitudes that span 5 kyr drawn from a truncated Pareto distribution. The primary constraints to the problem are maximum and minimum values around the target slip-rate function indicating where feasible solutions can occur. Two methods are used to determine the spatial distribution of earthquakes: integer programming and the greedy-sequential algorithm. For the integer-programming method, the binary decision vector includes all possible locations along the fault where each earthquake can occur. Once a set of solutions that satisfy the constraints is found, the cumulative slip misfit on the fault is globally minimized relative to the target slip-rate function. The greedy algorithm sequentially places earthquakes to locally optimize slip accumulation. As a case study, we calculate how earthquakes are distributed along the megathrust of the Nankai subduction zone, in which the slip rate varies significantly along strike. For both methods, the spatial distribution of magnitudes depends on slip rate, except for the largest magnitude earthquakes that span multiple sections of the fault. The greedy-sequential algorithm, previously applied to this fault (Parsons et al., 2012), tends to produce smoother spatial distributions and fewer lower magnitude earthquakes in the low slip-rate section of the fault compared to the integer-programming method. Differences in results from the two methods relate to how much emphasis is placed on minimizing the misfit to the target slip rate (integer programming) compared to finding a solution within the slip-rate constraints (greedy sequential). Specifics of the spatial distribution of magnitudes also depend on the shape of the target slip-rate function: that is, stepped at the section boundaries versus a smooth function. This study isolates the effects of slip-rate variation along a single fault in determining the spatial distribution of earthquake magnitudes, helping to better interpret results from more complex, interconnected fault systems.

A critical component of seismic hazard analysis is understanding the frequency and spatial distribution of earthquakes with different magnitudes on nearby faults. A framework for determining the optimal spatial distribution of earthquakes on a complex fault system is developed using combinatorial optimization methods. Input to the framework is a millennia-scale sample of earthquakes taken from a regional Gutenberg-Richter (G-R) relation. We then determine the optimal spatial arrangement of each earthquake in the fault system according to an objective function and constraints. Our previously published results focus on minimizing the total misfit in slip rates as the objective function; constraints were maximum and minimum slip rate values that incorporate uncertainty in slip-rate values for each fault. Both global and local combinatorial optimization methods have been developed to solve these problems: integer programming and the greedy sequential algorithm, respectively. Resulting on-fault magnitude distributions cannot be simply classified as being either purely characteristic or G-R. For example, faults may exhibit multiple “characteristic” magnitudes or a power-law distribution of magnitudes over a restricted range. Current research involves adapting the general combinatorial framework to include other and multiple objective functions, including minimizing the variation in accumulated stress over millennia. The framework can also accommodate branching and step-over connections for the slip-rate objective, while current research is underway to include interaction stress loading among the different faults in the fault system for stress-based objectives. Results from these methods are valuable for verifying the assumed magnitude-frequency distributions for faults in probabilistic seismic and tsunami hazard analyses.

AGU Advances, 2 (1), ISSN:2576-604X

Background: Chronic exertional compartment syndrome (CECS) of the lower limb usually responds well to fasciotomy in patients with failed nonoperative treatment. Careful history taking and compartment pressure testing are both required to accurately diagnose CECS. Purposes: To evaluate patients with CECS after fasciotomy to establish predictive criteria of positive outcomes and to develop a scoring system to aid clinicians in their management of such patients. Study Design: Case-control study; Level of evidence, 3. Methods: We reviewed data from 28 patients who underwent fasciotomy between 2017 and 2019. All patients had undergone preoperative dynamic intracompartmental pressure (ICP) monitoring. For each patient, subjective preoperative and postoperative pain scores were gained via a questionnaire. The point biserial and Pearson correlation coefficients were used to calculate the association between multiple diagnostic criteria and a reduction in visual analog scale (VAS) pain scores after fasciotomy. Results: A reduction in VAS pain scores was strongly correlated with a peak ICP >40 mm Hg ( r = 0.71; P = .0007) and an area under the receiver operating characteristic curve for an intraexercise ICP >22,000 mm Hg·s2 ( r = 0.76; P = .0002). A moderate correlation was found between a history of CECS pain ( r = 0.61; P = .005), a duration of symptoms of 10 mm Hg ( r = 0.60; P = .006). When combined into an objective, weighted scoring system (2 points for factors with r > 0.7; 1 point for r = 0.5-0.7), a score of ≥4 points (of 7) had a strong correlation ( r = 0.85; P < .00001) with postoperative improvement in the VAS pain score. Linear regression of this score demonstrated a good fit ( R 2 = 0.61; P < .0001), indicating a degree of predictive power. Conclusion: We identified diagnostic criteria in the history and examination of patients with CECS that can be used to help predict positive outcomes after fasciotomy. We propose a scoring system to aid clinicians in their management of such patients. We recommend taking these results forward in prospective trials to test the efficacy of predictive scoring.

The M 7.1 2018 Anchorage earthquake occurred in the bending part of the subducting North Pacific plate near the geometrical barrier formed by the underthrusting Yakutat terrane. We calculate the triggering potential related with stress redistribution from deformation sources including the M 9.2 1964 earthquake coseismic slip, postseismic deformation, slip from regional M > 5 earthquakes, and the cumulative slip of previously detected slow slip events over the past 55 years. We investigate the deeper shallow depth (20–60 km) seismicity response to these perturbations using an epidemic type aftershock sequence model to describe earthquake‐to‐earthquake interactions. The statistical forecast captures the triggered seismicity during the 1983 M 6+ aftershocks in Columbia Bay but performs poorly during the slow slip event period between 1992.0 and 2004.8 that presents a statistically significant rate change (β , Z > 2; M < 4.0). We find that stress effects from the 1964 postseismic source and the 12‐year‐long slow slip event (~M 7.8) contribute to the 2018 Anchorage earthquake occurrence and that slow slip events modulate the deeper shallow depth seismicity patterns in the region.

Operational earthquake forecasting protocols commonly use statistical models for their recognized ease of implementation and robustness in describing the short-term spatiotemporal patterns of triggered seismicity. However, recent advances on physics-based aftershock forecasting reveal comparable performance to the standard statistical counterparts with significantly improved predictive skills when fault and stress-field heterogeneities are considered. Here, we perform a pseudoprospective forecasting experiment during the first month of the 2019 Ridgecrest (California) earthquake sequence. We develop seven Coulomb rate-and-state models that couple static stress-change estimates with continuum mechanics expressed by the rate-and-state friction laws. Our model parameterization supports a gradually increasing complexity; we start from a preliminary model implementation with simplified slip distributions and spatially homogeneous receiver faults to reach an enhanced one featuring optimized fault constitutive parameters, finite-fault slip models, secondary triggering effects, and spatially heterogenous planes informed by pre-existing ruptures. The data-rich environment of southern California allows us to test whether incorporating data collected in near-real time during an unfolding earthquake sequence boosts our predictive power. We assess the absolute and relative performance of the forecasts by means of statistical tests used within the Collaboratory for the Study of Earthquake Predictability and compare their skills against a standard benchmark epidemic-type aftershock sequence (ETAS) model for the short (24 hr after the two Ridgecrest mainshocks) and intermediate terms (one month). Stress-based forecasts expect heightened rates along the whole near-fault region and increased expected seismicity rates in central Garlock fault. Our comparative model evaluation not only supports that faulting heterogeneities coupled with secondary triggering effects are the most critical success components behind physics-based forecasts, but also underlines the importance of model updates incorporating near-real-time available aftershock data reaching better performance than standard ETAS. We explore the physical basis behind our results by investigating the localized shut down of pre-existing normal faults in the Ridgecrest near-source area.

Members of the editorial board of AGU Advances express their appreciation to those who served as peer reviewers for the journal in its inaugural year.

The M = 8.1 Chiapas and the M = 7.1 Puebla earthquakes occurred in the bending part of the subducting Cocos plate 11 days and ~600 km apart, a range that puts them well outside the typical aftershock zone. We find this to be a relatively common occurrence in Mexico, with 14% of M > 7.0 earthquakes since 1900 striking more than 300 km apart and within a 2 week interval, not different from a randomized catalog. We calculate the triggering potential caused by crustal stress redistribution from large subduction earthquakes over the last 40 years. There is no evidence that static stress transfer or dynamic triggering from the 8 September Chiapas earthquake promoted the 19 September earthquake. Both recent earthquakes were promoted by past thrust events instead, including delayed afterslip from the 2012 M = 7.5 Oaxaca earthquake. A repeated pattern of shallow thrust events promoting deep intraslab earthquakes is observed over the past 40 years.

Applying probabilistic methods to infrequent but devastating natural events is intrinsically challenging. For tsunami analyses, a suite of geophysical assessments should be in principle evaluated because of the different causes generating tsunamis (earthquakes, landslides, volcanic activity, meteorological events, and asteroid impacts) with varying mean recurrence rates. Probabilistic Tsunami Hazard Analyses (PTHAs) are conducted in different areas of the world at global, regional, and local scales with the aim of understanding tsunami hazard to inform tsunami risk reduction activities. PTHAs enhance knowledge of the potential tsunamigenic threat by estimating the probability of exceeding specific levels of tsunami intensity metrics (e.g., run-up or maximum inundation heights) within a certain period of time (exposure time) at given locations (target sites); these estimates can be summarized in hazard maps or hazard curves. This discussion presents a broad overview of PTHA, including (i) sources and mechanisms of tsunami generation, emphasizing the variety and complexity of the tsunami sources and their generation mechanisms, (ii) developments in modeling the propagation and impact of tsunami waves, and (iii) statistical procedures for tsunami hazard estimates that include the associated epistemic and aleatoric uncertainties. Key elements in understanding the potential tsunami hazard are discussed, in light of the rapid development of PTHA methods during the last decade and the globally distributed applications, including the importance of considering multiple sources, their relative intensities, probabilities of occurrence, and uncertainties in an integrated and consistent probabilistic framework.

Under homeostatic conditions, animals use well-defined hypothalamic neural circuits to help maintain stable body weight, by integrating metabolic and hormonal signals from the periphery to balance food consumption and energy expenditure. In stressed or disease conditions, however, animals use alternative neuronal pathways to adapt to the metabolic challenges of altered energy demand. Recent studies have identified brain areas outside the hypothalamus that are activated under these 'non-homeostatic' conditions, but the molecular nature of the peripheral signals and brain-localized receptors that activate these circuits remains elusive. Here we identify glial cell-derived neurotrophic factor (GDNF) receptor alpha-like (GFRAL) as a brainstem-restricted receptor for growth and differentiation factor 15 (GDF15). GDF15 regulates food intake, energy expenditure and body weight in response to metabolic and toxin-induced stresses; we show that Gfral knockout mice are hyperphagic under stressed conditions and are resistant to chemotherapy-induced anorexia and body weight loss. GDF15 activates GFRAL-expressing neurons localized exclusively in the area postrema and nucleus tractus solitarius of the mouse brainstem. It then triggers the activation of neurons localized within the parabrachial nucleus and central amygdala, which constitute part of the 'emergency circuit' that shapes feeding responses to stressful conditions. GDF15 levels increase in response to tissue stress and injury, and elevated levels are associated with body weight loss in numerous chronic human diseases. By isolating GFRAL as the receptor for GDF15-induced anorexia and weight loss, we identify a mechanistic basis for the non-homeostatic regulation of neural circuitry by a peripheral signal associated with tissue damage and stress. These findings provide opportunities to develop therapeutic agents for the treatment of disorders with altered energy demand.

In the Basin and Range extensional province of the western United States, coseismic offsets, under the influence of gravity, display predominantly subsidence of the basin side (fault hanging wall), with comparatively little or no uplift of the mountainside (fault footwall). A few decades later, geodetic measurements [GPS and interferometric synthetic aperture radar (InSAR)] show broad (∼100 km) aseismic uplift symmetrically spanning the fault zone. Finally, after millions of years and hundreds of fault offsets, the mountain blocks display large uplift and tilting over a breadth of only about 10 km. These sparse but robust observations pose a problem in that the coesismic uplifts of the footwall are small and inadequate to raise the mountain blocks. To address this paradox we develop finite-element models subjected to extensional and gravitational forces to study time-varying deformation associated with normal faulting. Stretching the model under gravity demonstrates that asymmetric slip via collapse of the hanging wall is a natural consequence of coseismic deformation. Focused flow in the upper mantle imposed by deformation of the lower crust localizes uplift, which is predicted to take place within one to two decades after each large earthquake. Thus, the best-preserved topographic signature of earthquakes is expected to occur early in the postseismic period.

The use of a newly developed earthquake simulator has allowed the production of catalogs lasting 100 kyr and containing more than 100,000 events of magnitudes ≥4.5. The model of the fault system upon which we applied the simulator code was obtained from the DISS 3.2.0 database, selecting all the faults that are recognized on the Calabria region, for a total of 22 fault segments. The application of our simulation algorithm provides typical features in time, space and magnitude behavior of the seismicity, which can be compared with those of the real observations. The results of the physics-based simulator algorithm were compared with those obtained by an alternative method using a slip-rate balanced technique. Finally, as an example of a possible use of synthetic catalogs, an attenuation law has been applied to all the events reported in the synthetic catalog for the production of maps showing the exceedance probability of given values of PGA on the territory under investigation.

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The probability distribution of far-field tsunami amplitudes is explained in relation to the distribution of seismic moment at subduction zones. Tsunami amplitude distributions at tide gauge stations follow a similar functional form, well described by a tapered Pareto distribution that is parameterized by a power-law exponent and a corner amplitude. Distribution parameters are first established for eight tide gauge stations in the Pacific, using maximum likelihood estimation. A procedure is then developed to reconstruct the tsunami amplitude distribution that consists of four steps: (1) define the distribution of seismic moment at subduction zones; (2) establish a source-station scaling relation from regression analysis; (3) transform the seismic moment distribution to a tsunami amplitude distribution for each subduction zone; and (4) mix the transformed distribution for all subduction zones to an aggregate tsunami amplitude distribution specific to the tide gauge station. The tsunami amplitude distribution is adequately reconstructed for four tide gauge stations using globally constant seismic moment distribution parameters established in previous studies. In comparisons to empirical tsunami amplitude distributions from maximum likelihood estimation, the reconstructed distributions consistently exhibit higher corner amplitude values, implying that in most cases, the empirical catalogs are too short to include the largest amplitudes. Because the reconstructed distribution is based on a catalog of earthquakes that is much larger than the tsunami catalog, it is less susceptible to the effects of record-breaking events and more indicative of the actual distribution of tsunami amplitudes.

We forecast time-independent and time-dependent earthquake ruptures in the Marmara region of Turkey for the next 30 years using a new fault segmentation model. We also augment time-dependent Brownian passage time (BPT) probability with static Coulomb stress changes (ΔCFF) from interacting faults. We calculate Mw > 6.5 probability from 26 individual fault sources in the Marmara region. We also consider a multisegment rupture model that allows higher-magnitude ruptures over some segments of the northern branch of the North Anatolian Fault Zone beneath the Marmara Sea. A total of 10 different Mw = 7.0 to Mw = 8.0 multisegment ruptures are combined with the other regional faults at rates that balance the overall moment accumulation. We use Gaussian random distributions to treat parameter uncertainties (e.g., aperiodicity, maximum expected magnitude, slip rate, and consequently mean recurrence time) of the statistical distributions associated with each fault source. We then estimate uncertainties of the 30 year probability values for the next characteristic event obtained from three different models (Poisson, BPT, and BPT + ΔCFF) using a Monte Carlo procedure. The Gerede fault segment located at the eastern end of the Marmara region shows the highest 30 year probability, with a Poisson value of 29% and a time-dependent interaction probability of 48%. We find an aggregated 30 year Poisson probability of M > 7.3 earthquakes at Istanbul of 35%, which increases to 47% if time dependence and stress transfer are considered. We calculate a twofold probability gain (ratio time dependent to time independent) on the southern strands of the North Anatolian Fault Zone.

Vertical deformation of extensional provinces varies significantly and in seemingly contradictory ways. Sparse but robust geodetic, seismic, and geologic observations in the Basin and Range province of the western United States indicate that immediately after an earthquake, vertical change primarily occurs as subsidence of the normal fault hanging wall. A few decades later, a ±100 km wide zone is symmetrically uplifted. The preserved topography of long-term rifting shows bent and tilted footwall flanks rising high above deep basins. We develop finite element models subjected to extensional and gravitational forces to study time-varying deformation associated with normal faulting. We replicate observations with a model that has a weak upper mantle overlain by a stronger lower crust and a breakable elastic upper crust. A 60° dipping normal fault cuts through the upper crust and extends through the lower crust to simulate an underlying shear zone. Stretching the model under gravity demonstrates that asymmetric slip via collapse of the hanging wall is a natural consequence of coseismic deformation. Focused flow in the upper mantle imposed by deformation of the lower crust localizes uplift under the footwall; the breakable upper crust is a necessary model feature to replicate footwall bending over the observed width (

What exactly happens on the rupture surface as an earthquake nucleates, spreads, and stops? We cannot observe this directly, and models depend on assumptions about physical conditions and geometry at depth. We thus measure a natural fault surface and use its 3-D coordinates to construct a replica at 0.1m resolution to obviate geometry uncertainty. We can recreate stick-slip behavior on the resulting finite element model that depends solely on observed fault geometry. We clamp the fault together and apply steady state tectonic stress until seismic slip initiates and terminates. Our recreated M~1 earthquake initiates at contact points where there are steep surface gradients because infinitesimal lateral displacements reduce clamping stress most efficiently there. Unclamping enables accelerating slip to spread across the surface, but the fault soon jams up because its uneven, anisotropic shape begins to juxtapose new high-relief sticking points. These contacts would ultimately need to be sheared off or strongly deformed before another similar earthquake could occur. Our model shows that an important role is played by fault-wall geometry, although we do not include effects of varying fluid pressure or exotic rheologies on the fault surfaces. We extrapolate our results to large fault systems using observed self-similarity properties and suggest that larger ruptures might begin and end in a similar way, although the scale of geometrical variation in fault shape that can arrest a rupture necessarily scales with magnitude. In other words, fault segmentation may be a magnitude-dependent phenomenon and could vary with each subsequent rupture.

The 2014 Working Group on California Earthquake Probabilities (WGCEP 2014) presents time-dependent earthquake probabilities for the third Uniform California Earthquake Rupture Forecast (UCERF3). Building on the UCERF3 time-in- dependent model published previously, renewal models are utilized to represent elastic- rebound-implied probabilities. A new methodology has been developed that solves applicability issues in the previous approach for unsegmented models. The new meth- odology also supports magnitude-dependent aperiodicity and accounts for the historic open interval on faults that lack a date-of-last-event constraint. Epistemic uncertainties are represented with a logic tree, producing 5760 different forecasts. Results for a variety of evaluation metrics are presented, including logic-tree sensitivity analyses and comparisons to the previous model (UCERF2). For 30 yr M ! 6:7 probabilities, the most significant changes from UCERF2 are a threefold increase on the Calaveras fault and a threefold decrease on the San Jacinto fault. Such changes are due mostly to differences in the time-independent models (e.g., fault-slip rates), with relaxation of segmentation and inclusion of multifault ruptures being particularly influential. In fact, some UCERF2 faults were simply too long to produce M 6.7 size events given the segmentation assumptions in that study. Probability model differences are also influential, with the implied gains (relative to a Poisson model) being generally higher in UCERF3. Accounting for the historic open interval is one reason. Another is an effective 27% increase in the total elastic-rebound-model weight. The exact factors influencing differences between UCERF2 and UCERF3, as well as the relative im- portance of logic-tree branches, vary throughout the region and depend on the evalu- ation metric of interest. For example, M ! 6:7 probabilities may not be a good proxy for other hazard or loss measures. This sensitivity, coupled with the approximate nature of the model and known limitations, means the applicability of UCERF3 should be evaluated on a case-by-case basis.

Larger earthquakes unlocked by fluids are seen globally to take a predictably longer time to begin., Earthquakes triggered by other remote seismic events are explained as a response to long-traveling seismic waves that temporarily stress the crust. However, delays of hours or days after seismic waves pass through are reported by several studies, which are difficult to reconcile with the transient stresses imparted by seismic waves. We show that these delays are proportional to magnitude and that nucleation times are best fit to a fluid diffusion process if the governing rupture process involves unlocking a magnitude-dependent critical nucleation zone. It is well established that distant earthquakes can strongly affect the pressure and distribution of crustal pore fluids. Earth’s crust contains hydraulically isolated, pressurized compartments in which fluids are contained within low-permeability walls. We know that strong shaking induced by seismic waves from large earthquakes can change the permeability of rocks. Thus, the boundary of a pressurized compartment may see its permeability rise. Previously confined, overpressurized pore fluids may then diffuse away, infiltrate faults, decrease their strength, and induce earthquakes. Magnitude-dependent delays and critical nucleation zone conclusions can also be applied to human-induced earthquakes.