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At least 1,099 records · Page 61Linked to original sources

USGS2023

Mapping closed depressions in the karst region of northwest Puerto Rico using lidar-derived elevation data obtained in 2018 after Hurricane Maria

Identifying and analyzing closed depressions in karst areas is important for sinkhole hazard evaluation and land management. We created a sinkhole inventory in the karst region of northwest Puerto Rico using a lidar-derived elevation model acquired in 2018 approximately eleven months after Hurricane Maria. The goal of this project is to develop a geodatabase of sinkhole feature classes (polygons and points), relevant geometric attributes of each feature, and a density raster to portray areas of greater clustering of sinkholes as an input for future sinkhole susceptibility assessment. We used ArcGIS Pro® v3.0 to create closed depression polygons using two semi-automated extraction methods. A fill-difference method was used to capture depressions nine square meters and larger, and a contour tree method was used to capture nested depressions larger than one hundred square meters. Quality checks were conducted to eliminate non-karst depressions, such as human-made depressions and those resulting as artifacts from the automated methods. Geospatial data of land cover, soils, and geology helped to refine the results and improve quality control. The most challenging aspect of this effort was determining a true karst sinkhole from other depressions extracted from the lidar-derived elevation model. Limitations of this semi-automated method include false-positive depressions in the automated results and the exclusion of sinkholes in conducting large-scale eliminations based on landscape attributes. We approached this challenge by combining layers of other geospatial information to evaluate the type of process that could result in a closed depression. This project will help develop an efficient method to visualize karst hazards utilizing lidar-derived elevation models and sinkhole geomorphic expressions. The resulting geodatabase can be used to efficiently identify sinkhole susceptibility and support land management decision-making in karst areas.

Puerto Rico↗

USGS2025

A monitoring framework to assess forest bird population response to landscape scale mosquito suppression using the Incompatible Insect Technique

The Birds, Not Mosquitoes Monitoring and Support Science Working Group detailed methods for monitoring the population response of Hawaiian forest birds during implementation of the Incompatible Insect Technique (IIT) on the islands of Maui and Kauaʻi. The group prioritized methods for measuring the influence of mosquito suppression on populations within IIT treatment and control areas and identified focal species for IIT efficacy monitoring in birds. Three primary metrics were established to assess the impact of IIT on vulnerable species: population demography, density, and geographic range. Each metric can be evaluated using multiple methods. This report reviews those methods, with emphasis on approaches supported by pre-IIT baseline data and compatible with a before-after control-impact (BACI) study design for evaluating population responses over time. Focal avian species were selected based on population size estimates, fecundity, and disease susceptibility. We identified ʻākohekohe (Palmeria dolei), ʻiʻiwi (Drepanis coccinea), Maui ʻalauahio (Paroreomyza montana), Hawaiʻi ʻamakihi (Chlorodrepanis virens), Kauaʻi ʻamakihi (Chlorodrepanis stejnegeri), Kauaʻi ʻelepaio (Chasiempis sclateri), and ʻanianiau (Magumma parva) as focal species for monitoring population level response to disease suppression. Populations of kiwikiu (Pseudonestor xanthophrys), ʻakikiki (Oreomystis bairdi), akekeʻe (Loxops caeruleirostris), and the ʻiʻiwi population on Kauaʻi may be too small (e.g., <100 individuals) to effectively monitor, and it is unlikely that sufficient data can be collected from these birds to show IIT efficacy in a relatively short time frame (i.e., 5–10 years). Despite the logistical challenges to IIT implementation, there is potential to maintain disease-free status in individual populations of birds. Indeed, the continued existence of these critically endangered species in the wild within or near IIT treatment areas could be considered an accomplishment of IIT, given the current predictions for their extinction in the wild within 5–10 years. Demographic monitoring methods, including territory mapping, nest monitoring, mist-netting, and mark-recapture studies, provide direct evidence of survivorship and reproductive output. When combined with disease surveillance, these approaches could provide the most robust evidence of increased survivorship and productivity resulting from avian malaria suppression via IIT. However, demographic studies require several years of monitoring to achieve statistically robust BACI comparisons of survivorship and are more difficult to implement relative to other approaches. Given that these field efforts are labor-intensive and heavily reliant on personnel availability and funding, demographic monitoring could be conducted when adequate resources permit. On both Maui and Kauaʻi, passive acoustic monitoring (PAM) was identified as a priority method for monitoring the range, occupancy, and relative abundance of focal species. Autonomous recording units (ARUs) can record bird vocalizations in remote areas for several months. Innovative machine learning techniques permit rapid and semi-autonomous identification of most endemic honeycreepers on each island, maximizing sampling efficiencies and minimizing data processing costs. We predict mosquito suppression could support expansion of focal species into areas where disease transmission is currently excluding these species and expect acoustic monitoring data of focal species to reflect these spatial patterns. Additionally, the relative occupancy and call densities can be monitored temporally and spatially to assess the efficacy of IIT for supporting positive growth in vulnerable bird species. It is not yet clear if PAM is more effective than other methods, such as distance sampling, for detecting trends in the densities of rare species. However, the increased detections resulting from the larger sample size per observation point using ARUs will likely improve accuracy in detecting changes in species’ ranges. Collection of during and after treatment data within the BACI design could help to provide critical information to track avian population response, recovery, and potential range expansion related to IIT efforts. Point-transect distance sampling (point-counts) was prioritized as a method for monitoring population densities of focal species. Extensive historical sampling across focal species’ ranges provides a robust baseline for detecting change. These counts provide updated population densities and can be used to assess the distribution of focal species within IIT treatment areas. However, detecting subtle population changes with traditional distance sampling requires intensive spatial and temporal effort and may be less effective for rare species. To improve resolution, density surface modeling can integrate multiple data sources (e.g., point-counts, PAM, spot-mapping, and resightings) to estimate species-specific densities at finer spatial scales, including within and outside IIT treatment areas. This integrated modeling approach allows for detailed comparisons and may reveal early signs of recovery, including recolonization of formerly occupied sites. A coordinated monitoring strategy can allow managers to evaluate the success of mosquito suppression as a conservation intervention and support adaptive management in the face of emerging challenges.

Hawaii↗

USGS2026

How hunters and non-hunters view barriers to allowing hunting access in an urban county

Barriers to allowing hunting of white-tailed deer ( Odocoileus virginianus ) on private land shape hunter recruitment, retention, and reactivation efficacy as well as the ability of wildlife management agencies to use hunting as a management tool. Understanding perceptions of these barriers is crucial in urbanizing landscapes where there are increased challenges to allowing hunting access, and deer may persist in relatively high numbers. We compared barriers to allowing hunting access on one’s property among hunters (n = 281) and non-hunters (n = 874) who did not have hunting occur on their property across urban, suburban, and rural groups in Durham County, North Carolina. (i.e., six groups). Rural landowners tended to perceive geographic barriers (e.g., property size) as less problematic than suburban and urban landowners, irrespective of personal participation in hunting, but landowners who hunted tended to view all barriers as less problematic than those who did not. Small property size, human population density, and housing density were viewed as important barriers to allowing hunting access for all groups, but suburban and urban non-hunters perceived the challenges as greater barriers compared to other groups. Conversely, the complexity of hunting regulations was viewed as a minor barrier to allowing hunting among all landowners. Safety concerns, not knowing other hunters, and disagreement with hunting as a practice showed the greatest contrasts between landowners who hunted and those who did not, with the latter group reporting the barriers as more important. Barriers to hunting identified in this study aligned with variables that predicted whether land is huntable (e.g., property size, housing density) in prior research. Our results indicate that developing public outreach highlighting hunting safety and creating landowner-hunter partnership programs may help facilitate hunting access in urbanizing areas.

North Carolina↗

USGS1996

A model for field toxicity tests

Toxicity tests conducted under field conditions present an interesting challenge for statistical modelling. In contrast to laboratory tests, the concentrations of potential toxicants are not held constant over the test. In addition, the number and identity of toxicants that belong in a model as explanatory factors are not known and must be determined through a model selection process. We present one model to deal with these needs. This model takes the record of mortalities to form a multinomial distribution in which parameters are modelled as products of conditional daily survival probabilities. These conditional probabilities are in turn modelled as logistic functions of the explanatory factors. The model incorporates lagged values of the explanatory factors to deal with changes in the pattern of mortalities over time. The issue of model selection and assessment is approached through the use of generalized information criteria and power divergence goodness-of-fit tests. These model selection criteria are applied in a cross-validation scheme designed to assess the ability of a model to both fit data used in estimation and predict data deleted from the estimation data set. The example presented demonstrates the need for inclusion of lagged values of the explanatory factors and suggests that penalized likelihood criteria may not provide adequate protection against overparameterized models in model selection.

Environmetrics↗

USGS2000

What is “natural”? : Yellowstone elk population - A case study

Ecology analyzes the structure and function of ecosystems at all points along the continuum of human disturbance, from so-called pristine forests to urban backyards. Undisturbed systems provide reference points at one end of the spectrum, and nature reserves and parks are highly valued because they can provide unique examples of such ecosystems. Unfortunately the concept of “natural” or pristine is not that easy to define. Indeed, although ecologists have considered pre-Columbian, western-hemisphere ecosystems to have been largely unaltered by human action, and have termed their state “natural” or “pristine,” evidence from archaeology challenges this view. U.S. and Canadian national parks are charged with preserving the “natural,” and thus need to be able to understand and manage for the “natural.” A pivotal “natural” question in Yellowstone National Park management is the size of the northern-range, wintering elk population at Park establishment in 1872, argued both to have been small and large. Integrating and quantifying several sources of evidence provides a consistent picture of a low population (ca. 5,000–6,000), largely migrating out of the northern range in winter, with little vegetation impact. If we accept this conclusion about what is natural for the Yellowstone ecosystem, then it dramatically alters how we view management alternatives for the Park, which currently supports a northern wintering herd of up to ˜ 25,000 elk.

Wyoming↗

USGS2023

Addressing a potential weakness in indices of predation, herbivory, and parasitism

Quantification of predation, herbivory, and parasitism is critical to understanding the dynamics and trophic interactions of populations in an ecosystem. Such quantification can be challenging if the availability or consumption of the taxa are difficult to assess. Sometimes the consumption of a single prey, forage, or host is used as an overall index of the predation, herbivory, or parasitism for a population of interest. Occasionally, human-manipulated baits are used to derive similar indices. However, all such indices are susceptible to influence by variation in the abundance of the preferred taxon relative to other taxa as the result of preference switching. In this article, I describe a test for preference switching (and an adjustment, if detected) that does not require availability and consumption of the prey (forage, or host) to be measured on the same scale. The ability to detect and adjust for preference switching in such situations may advance the understanding of biological preference in taxa not previously studied in this respect.

Population Ecology↗

USGS2026

A fresh perspective - Advancing fish immunotoxicology in a complex world

Understanding how environmental changes affect the health of organisms and ecosystems is complex, but recent interdisciplinary advances and the recognition of immune function as a dynamic mediator offer exciting progress. Environmental immunotoxicology in teleost fishes is evolving beyond cataloguing stressors towards a mechanistic, integrative framework that leverages omics, in vivo tracking and cross-disciplinary modelling. However, knowledge gaps in immune mechanisms, toxicokinetics and multi-stressor interactions remain. The present work highlights these gaps, advocating for immune function as both a mechanistic lens and an integrative health indicator. Such a framework can improve predictive risk assessments, management strategies and our understanding of contaminant effects on resilience, disease susceptibility and population viability. While challenges remain, the field is poised for significant growth through collaborative innovation and advancing technology.

FEBS Letters↗

USGS2013

Working with strainmeter data

The Plate Boundary Observatory (PBO), the geodetic component of the U.S. National Science Foundation–funded Earthscope program, includes 75 borehole and 6 laser strainmeters ( http://pbo.unavco.org ). The strainmeters are installed at several locations: on the Cascadia forearc in Washington state and on Vancouver Island, Canada; in arrays of two to nine instruments along the North American–Pacific plate boundary in California; at Mount St. Helens; and in Yellowstone National Park. For deformation signals seconds to weeks in duration, strainmeters have a resolution and a signal-to-noise ratio superior to those of seismometers and GPS. However, this high sensitivity can introduce nontectonic signals into strain data, presenting data interpretation challenges, especially for borehole strainmeters.

Eos, Earth and Space Science News↗

USGS2014

Transport of fine sediment over a coarse, immobile riverbed

Sediment transport in cobble-boulder rivers consists mostly of fine sediment moving over a coarse, immobile bed. Transport rate depends on several interrelated factors: boundary shear stress, the grain size and volume of fine sediment, and the configuration of fine sediment into interstitial deposits and bed forms. Existing models do not incorporate all of these factors. Approaches that partition stress face a daunting challenge because most of the boundary shear is exerted on immobile grains. We present an alternative approach that divides the bed into sand patches and interstitial deposits and is well constrained by two clear end-member cases: full sand cover and absence of sand. Entrainment from sand patches is a function of their aerial coverage. Entrainment from interstices among immobile grains is a function of sand elevation relative to the size of the immobile grains. The bed-sand coverage function is used to predict the ratio of the rate of entrainment from a partially covered bed to the rate of entrainment from a completely sand-covered bed, which is determined using a standard sand transport model. We implement the bed-sand coverage function in a morphodynamic routing model and test it against observations of sand bed elevation and suspended sand concentration for conditions of nonuniform fine sediment transport in a large flume with steady uniform flow over immobile hemispheres. The results suggest that this approach may provide a simple and robust method for predicting the transport and migration of fine sediment through rivers with coarse, immobile beds.

Journal of Geophysical Research F: Earth Surface↗

USGS2013

Seasonal changes in peatland surface elevation recorded at GPS stations in the Red Lake Peatlands, northern Minnesota, USA

Northern peatlands appear to hold large volumes of free‐phase gas (e.g., CH 4 and CO 2 ), which has been detected by surface deformations, pore pressure profiles, and electromagnetic surveys. Determining the gas content and its impact in peat is challenging because gas storage depends on both the elastic properties of the peat matrix and the buoyant forces exerted by pore fluids. We therefore used a viscoelastic deformation model to estimate these variables by adjusting model runs to reproduce observed changes in peat surface elevation within a 1300 km 2 peatland. A local GPS network documented significant changes in surface elevations throughout the year with the greatest vertical displacements associated with rapid changes in peat water content and unloadings due to melting of the winter snowpack. These changes were coherent with changes in water table elevation and also abnormal pore pressure changes measured by nests of instrumented piezometers. The deformation model reproduced these changes when the gas content was adjusted to 10% of peat volume, and Young's modulus was varied between 5 and 100 kPa as the peat profile shifted from tension to compression. In contrast, the model predicted little peat deformation when the gas content was 3% or lower. These model simulations are consistent with previous estimates of gas volume in northern peatlands and suggest an upper limit of gas storage controlled by the elastic moduli of the peat fabric.

Minnesota↗

USGS2014

Parameter optimization, sensitivity, and uncertainty analysis of an ecosystem model at a forest flux tower site in the United States

Ecosystem models are useful tools for understanding ecological processes and for sustainable management of resources. In biogeochemical field, numerical models have been widely used for investigating carbon dynamics under global changes from site to regional and global scales. However, it is still challenging to optimize parameters and estimate parameterization uncertainty for complex process-based models such as the Erosion Deposition Carbon Model (EDCM), a modified version of CENTURY, that consider carbon, water, and nutrient cycles of ecosystems. This study was designed to conduct the parameter identifiability, optimization, sensitivity, and uncertainty analysis of EDCM using our developed EDCM-Auto, which incorporated a comprehensive R package—Flexible Modeling Framework (FME) and the Shuffled Complex Evolution (SCE) algorithm. Using a forest flux tower site as a case study, we implemented a comprehensive modeling analysis involving nine parameters and four target variables (carbon and water fluxes) with their corresponding measurements based on the eddy covariance technique. The local sensitivity analysis shows that the plant production-related parameters (e.g., PPDF1 and PRDX) are most sensitive to the model cost function. Both SCE and FME are comparable and performed well in deriving the optimal parameter set with satisfactory simulations of target variables. Global sensitivity and uncertainty analysis indicate that the parameter uncertainty and the resulting output uncertainty can be quantified, and that the magnitude of parameter-uncertainty effects depends on variables and seasons. This study also demonstrates that using the cutting-edge R functions such as FME can be feasible and attractive for conducting comprehensive parameter analysis for ecosystem modeling.

Massachusetts↗

USGS2014

Characterizing riverbed sediment using high-frequency acoustics 1: spectral properties of scattering

Bed-sediment classification using high-frequency hydro-acoustic instruments is challenging when sediments are spatially heterogeneous, which is often the case in rivers. The use of acoustic backscatter to classify sediments is an attractive alternative to analysis of topography because it is potentially sensitive to grain-scale roughness. Here, a new method is presented which uses high-frequency acoustic backscatter from multibeam sonar to classify heterogeneous riverbed sediments by type (sand, gravel,rock) continuously in space and at small spatial resolution. In this, the first of a pair of papers that examine the scattering signatures from a heterogeneous riverbed, methods are presented to construct spatially explicit maps of spectral properties from geo-referenced point clouds of geometrically and radiometrically corrected echoes. Backscatter power spectra are computed to produce scale and amplitude metrics that collectively characterize the length scales of stochastic measures of riverbed scattering, termed ‘stochastic geometries’. Backscatter aggregated over small spatial scales have spectra that obey a power-law. This apparently self-affine behavior could instead arise from morphological- and grain-scale roughnesses over multiple overlapping scales, or riverbed scattering being transitional between Rayleigh and geometric regimes. Relationships exist between stochastic geometries of backscatter and areas of rough and smooth sediments. However, no one parameter can uniquely characterize a particular substrate, nor definitively separate the relative contributions of roughness and acoustic impedance (hardness). Combinations of spectral quantities do, however, have the potential to delineate riverbed sediment patchiness, in a data-driven approach comparing backscatter with bed-sediment observations (which is the subject of part two of this manuscript).

Journal of Geophysical Research F: Earth Surface↗

USGS2014

A mechanistic modeling and data assimilation framework for Mojave Desert ecohydrology

This study demonstrates and addresses challenges in coupled ecohydrological modeling in deserts, which arise due to unique plant adaptations, marginal growing conditions, slow net primary production rates, and highly variable rainfall. We consider model uncertainty from both structural and parameter errors and present a mechanistic model for the shrub Larrea tridentata (creosote bush) under conditions found in the Mojave National Preserve in southeastern California (USA). Desert-specific plant and soil features are incorporated into the CLM-CN model by Oleson et al. (2010). We then develop a data assimilation framework using the ensemble Kalman filter (EnKF) to estimate model parameters based on soil moisture and leaf-area index observations. A new implementation procedure, the “multisite loop EnKF,” tackles parameter estimation difficulties found to affect desert ecohydrological applications. Specifically, the procedure iterates through data from various observation sites to alleviate adverse filter impacts from non-Gaussianity in small desert vegetation state values. It also readjusts inconsistent parameters and states through a model spin-up step that accounts for longer dynamical time scales due to infrequent rainfall in deserts. Observation error variance inflation may also be needed to help prevent divergence of estimates from true values. Synthetic test results highlight the importance of adequate observations for reducing model uncertainty, which can be achieved through data quality or quantity.

California↗

USGS2015

Quantifying stream thermal regimes at management-pertinent scales: combining thermal infrared and stationary stream temperature data in a novel modeling framework.

Accurately quantifying stream thermal regimes can be challenging because stream temperatures are often spatially and temporally heterogeneous. In this study, we present a novel modeling framework that combines stream temperature data sets that are continuous in either space or time. Specifically, we merged the fine spatial resolution of thermal infrared (TIR) imagery with hourly data from 10 stationary temperature loggers in a 100 km portion of the Big Hole River, MT, USA. This combination allowed us to estimate summer thermal conditions at a relatively fine spatial resolution (every 100 m of stream length) over a large extent of stream (100 km of stream) during during the warmest part of the summer. Rigorous evaluation, including internal validation, external validation with spatially continuous instream temperature measurements collected from a Langrangian frame of reference, and sensitivity analyses, suggests the model was capable of accurately estimating longitudinal patterns in summer stream temperatures for this system Results revealed considerable spatial and temporal heterogeneity in summer stream temperatures and highlighted the value of assessing thermal regimes at relatively fine spatial and temporal scales. Preserving spatial and temporal variability and structure in abiotic stream data provides a critical foundation for understanding the dynamic, multiscale habitat needs of mobile stream organisms. Similarly, enhanced understanding of spatial and temporal variation in dynamic water quality attributes, including temporal sequence and spatial arrangement, can guide strategic placement of monitoring equipment that will subsequently capture variation in environmental conditions directly pertinent to research and management objectives.

Montana↗

USGS2015

A random-walk algorithm for modeling lithospheric density and the role of body forces in the evolution of the Midcontinent Rift

This paper develops a Monte Carlo algorithm for extracting three-dimensional lithospheric density models from geophysical data. Empirical scaling relationships between velocity and density create a 3D starting density model, which is then iteratively refined until it reproduces observed gravity and topography. This approach permits deviations from uniform crustal velocity-density scaling, which provide insight into crustal lithology and prevent spurious mapping of crustal anomalies into the mantle. We test this algorithm on the Proterozoic Midcontinent Rift (MCR), north-central U.S. The MCR provides a challenge because it hosts a gravity high overlying low shear-wave velocity crust in a generally flat region. Our initial density estimates are derived from a seismic velocity/crustal thickness model based on joint inversion of surface-wave dispersion and receiver functions. By adjusting these estimates to reproduce gravity and topography, we generate a lithospheric-scale model that reveals dense middle crust and eclogitized lowermost crust within the rift. Mantle lithospheric density beneath the MCR is not anomalous, consistent with geochemical evidence that lithospheric mantle was not the primary source of rift-related magmas and suggesting that extension occurred in response to far-field stress rather than a hot mantle plume. Similarly, the subsequent inversion of normal faults resulted from changing far-field stress that exploited not only warm, recently faulted crust but also a gravitational potential energy low in the MCR. The success of this density modeling algorithm in the face of such apparently contradictory geophysical properties suggests that it may be applicable to a variety of tectonic and geodynamic problems.

Iowa, Kansas, Michigan, Minnesota, Nebraska, Wisco↗

USGS2015

Surface melt dominates Alaska glacier mass balance

Mountain glaciers comprise a small and widely distributed fraction of the world's terrestrial ice, yet their rapid losses presently drive a large percentage of the cryosphere's contribution to sea level rise. Regional mass balance assessments are challenging over large glacier populations due to remote and rugged geography, variable response of individual glaciers to climate change, and episodic calving losses from tidewater glaciers. In Alaska, we use airborne altimetry from 116 glaciers to estimate a regional mass balance of −75 ± 11 Gt yr −1 (1994–2013). Our glacier sample is spatially well distributed, yet pervasive variability in mass balances obscures geospatial and climatic relationships. However, for the first time, these data allow the partitioning of regional mass balance by glacier type. We find that tidewater glaciers are losing mass at substantially slower rates than other glaciers in Alaska and collectively contribute to only 6% of the regional mass loss.

Alaska, British Columbia, Yukon Territory↗

USGS2015

Ocean circulation and biogeochemistry moderate interannual and decadal surface water pH changes in the Sargasso Sea

The oceans absorb anthropogenic CO 2 from the atmosphere, lowering surface ocean pH, a concern for calcifying marine organisms. The impact of ocean acidification is challenging to predict as each species appears to respond differently and because our knowledge of natural changes to ocean pH is limited in both time and space. Here we reconstruct 222 years of biennial seawater pH variability in the Sargasso Sea from a brain coral, Diploria labyrinthiformis . Using hydrographic data from the Bermuda Atlantic Time-series Study and the coral-derived pH record, we are able to differentiate pH changes due to surface temperature versus those from ocean circulation and biogeochemical changes. We find that ocean pH does not simply reflect atmospheric CO 2 trends but rather that circulation/biogeochemical changes account for >90% of pH variability in the Sargasso Sea and more variability in the last century than would be predicted from anthropogenic uptake of CO 2 alone.

Geophysical Research Letters↗

USGS2015

Pore-pressure sensitivities to dynamic strains: observations in active tectonic regions

Triggered seismicity arising from dynamic stresses is often explained by the Mohr-Coulomb failure criterion, where elevated pore pressures reduce the effective strength of faults in fluid-saturated rock. The seismic response of a fluid-rock system naturally depends on its hydro-mechanical properties, but accurately assessing how pore-fluid pressure responds to applied stress over large scales in situ remains a challenging task; hence, spatial variations in response are not well understood, especially around active faults. Here I analyze previously unutilized records of dynamic strain and pore-pressure from regional and teleseismic earthquakes at Plate Boundary Observatory (PBO) stations from 2006 through 2012 to investigate variations in response along the Pacific/North American tectonic plate boundary. I find robust scaling-response coefficients between excess pore pressure and dynamic strain at each station that are spatially correlated: around the San Andreas and San Jacinto fault systems, the response is lowest in regions of the crust undergoing the highest rates of secular shear strain. PBO stations in the Parkfield instrument cluster are at comparable distances to the San Andreas fault (SAF), and spatial variations there follow patterns in dextral creep rates along the fault, with the highest response in the actively creeping section, which is consistent with a narrowing zone of strain accumulation seen in geodetic velocity profiles. At stations in the San Juan Bautista (SJB) and Anza instrument clusters, the response depends non-linearly on the inverse fault-perpendicular distance, with the response decreasing towards the fault; the SJB cluster is at the northern transition from creeping-to-locked behavior along the SAF, where creep rates are at moderate to low levels, and the Anza cluster is around the San Jacinto fault, where to date there have been no statistically significant creep rates observed at the surface. These results suggest that the strength of the pore pressure response in fluid-saturated rock near active faults is controlled by shear strain accumulation associated with tectonic loading, which implies a strong feedback between fault strength and permeability: dynamic triggering susceptibilities may vary in space and also in time.

Journal of Geophysical Research B: Solid Earth↗