Search USGS⌕ Search

SEARCH · Search USGS

Results for “Journal of Applied Statistics”

Search indexed USGS publications on groundwater, aquifers, geologic maps, mineral resources and earthquakes. Explore source records by subject and place.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 109 records · Page 6Linked to original sources
USGS1997

Detecting changes in the spatial distribution of nitrate contamination in ground water

Many studies of ground water pollution in general and nitrate contamination in particular have often relied on a one-time investigation, tracking of individual wells, or aggregate summaries. Studies of changes in spatial distribution of contaminants over time are lacking. This paper presents a method to compare spatial distributions for possible changes over time. The large-scale spatial distribution at a given time can be considered as a surface over the area (a trend surface). The changes in spatial distribution from period to period can be revealed by the differences in the shape and/or height of surfaces. If such a surface is described by a polynomial function, changes in surfaces can be detected by testing statistically for differences in their corresponding polynomial functions. This method was applied to nitrate concentration in a population of wells in an agricultural drainage basin in Iowa, sampled in three different years. For the period of 1981-1992, the large-scale spatial distribution of nitrate concentration did not show significant change in the shape of spatial surfaces; while the magnitude of nitrate concentration in the basin, or height of the computed surfaces showed significant fluctuations. The change in magnitude of nitrate concentration is closely related to climatic variations, especially in precipitation. The lack of change in the shape of spatial surfaces means that either the influence of land use/nitrogen management was overshadowed by climatic influence, or the changes in land use/management occurred in a random fashion.

Journal of the American Water Resources Associatio↗
USGS2021

Compositional evolution of organic matter in Boquillas Shale across a thermal gradient at the single particle level

The molecular composition of petroliferous organic matter and its compositional evolution throughout thermal maturation provides insight for understanding petroleum generation. This information is critical for understanding hydrocarbon resources in unconventional reservoirs, as source rock organic matter is highly dispersed, in contact with the surrounding mineral matrix, and may occur as multiple organic matter maceral types. Here, Raman spectroscopy and optical microscopy approaches were applied to a marginally mature (vitrinite reflectance ~0.5%) sample of the Late Cretaceous Boquillas Shale before and after hydrous pyrolysis (HP) at 300 °C and 330 °C for 72 h. This analytical approach allowed for correlative examination of micro-scale changes in organic matter compositional properties (e.g., aromaticity) for a variety of organic matter macerals across a thermal gradient (from marginally mature into the late oil/wet gas window) at the single particle level. Results indicate that while the examined amorphous organic matter, solid bitumen, and vitrinite particles exhibit different aromatic signatures in the unheated shale, they effectively progress along a similar trend through composition space with thermal maturation. Examined inertinite fragments were generally insensitive to the applied thermal stress, reinforcing the idea that reservoir temperature may be secondary for dictating the molecular composition of inertinite. Additional analysis of Raman spectra for individual organic matter macerals was performed using multivariate curve resolution (MCR) and correlation of standard Raman and reflectance-derived thermal maturity proxies against MCR parameters shows consistent trends. This trend suggests that MCR may be a fast and statistically robust method for extracting compositional information from Raman spectra of sedimentary organic matter, and can be used to construct thermal maturity relationships. These findings inform our understanding of how different petroliferous organic matter maceral types evolve throughout thermal reactions and further demonstrate that Raman spectroscopy combined with petrographic analysis can provide complementary estimates of organic matter composition and thermal maturity.

International Journal of Coal Geology↗
USGS2007

A global search inversion for earthquake kinematic rupture history: Application to the 2000 western Tottori, Japan earthquake

[1] We present a two-stage nonlinear technique to invert strong motions records and geodetic data to retrieve the rupture history of an earthquake on a finite fault. To account for the actual rupture complexity, the fault parameters are spatially variable peak slip velocity, slip direction, rupture time and risetime. The unknown parameters are given at the nodes of the subfaults, whereas the parameters within a subfault are allowed to vary through a bilinear interpolation of the nodal values. The forward modeling is performed with a discrete wave number technique, whose Green's functions include the complete response of the vertically varying Earth structure. During the first stage, an algorithm based on the heat-bath simulated annealing generates an ensemble of models that efficiently sample the good data-fitting regions of parameter space. In the second stage (appraisal), the algorithm performs a statistical analysis of the model ensemble and computes a weighted mean model and its standard deviation. This technique, rather than simply looking at the best model, extracts the most stable features of the earthquake rupture that are consistent with the data and gives an estimate of the variability of each model parameter. We present some synthetic tests to show the effectiveness of the method and its robustness to uncertainty of the adopted crustal model. Finally, we apply this inverse technique to the well recorded 2000 western Tottori, Japan, earthquake ( Mw 6.6); we confirm that the rupture process is characterized by large slip (3-4 m) at very shallow depths but, differently from previous studies, we imaged a new slip patch (2-2.5 m) located deeper, between 14 and 18 km depth.

Tottori↗
USGS2021

Long-term year-round observations of magmatic CO2 emissions on Mammoth Mountain, California, USA

Diffuse emission of magmatic CO 2 is one of the main indicators of volcanic unrest at Mammoth Mountain, but the presence of deep seasonal snowpack at the site has hindered year-round CO 2 flux observations. A permanent eddy covariance station was established at the largest area of diffuse CO 2 degassing on Mammoth Mountain (Horseshoe Lake tree kill) that measured CO 2 fluxes ( F c ) and meteorological parameters on a half-hourly basis. From July 22, 2014 to May 24, 2020, F c ranged from −35 to 10,546 g m −2 d −1 . F c decreased on average by 53% over the study period, tracking the long-term decline in CO 2 emissions following the last major increase that occurred at the Horseshoe Lake tree kill area from 2009 to 2011. Statistical and spectral analyses were applied to the F c and ancillary meteorological parameter time series to understand (1) relationships between these parameters, (2) their dominant periodicities, and (3) changes in F c that may be unexplained by meteorological forcing. Variations in detrended F c ( F cdt ) were most strongly correlated with wind direction and atmospheric temperature, followed by atmospheric pressure on diurnal to annual time scales, but wind direction likely exerted the most direct control on F cdt . Comparison of the smoothed (180-d span) F cdt time series to the time series of average-daily snow water equivalent measured ~1 km away suggested that snowpack may have suppressed CO 2 emissions. No evidence of a change in CO 2 emissions related to the last major seismic swarm beneath Mammoth Mountain on February 2–18, 2014 was observed.

California↗
USGS1990

Conducting field studies for testing pesticide leaching models

A variety of predictive models are being applied to evaluate the transport and transformation of pesticides in the environment. These include well known models such as the Pesticide Root Zone Model (PRZM), the Risk of Unsaturated-Saturated Transport and Transformation Interactions for Chemical Concentrations Model (RUSTIC) and the Groundwater Loading Effects of Agricultural Management Systems Model (GLEAMS). The potentially large impacts of using these models as tools for developing pesticide management strategies and regulatory decisions necessitates development of sound model validation protocols. This paper offers guidance on many of the theoretical and practical problems encountered in the design and implementation of field-scale model validation studies. Recommendations are provided for site selection and characterization, test compound selection, data needs, measurement techniques, statistical design considerations and sampling techniques. A strategy is provided for quantitatively testing models using field measurements.

International Journal of Environmental Analytical ↗
USGS2013

Consideration of vertical uncertainty in elevation-based sea-level rise assessments: Mobile Bay, Alabama case study

The accuracy with which coastal topography has been mapped directly affects the reliability and usefulness of elevationbased sea-level rise vulnerability assessments. Recent research has shown that the qualities of the elevation data must be well understood to properly model potential impacts. The cumulative vertical uncertainty has contributions from elevation data error, water level data uncertainties, and vertical datum and transformation uncertainties. The concepts of minimum sealevel rise increment and minimum planning timeline, important parameters for an elevation-based sea-level rise assessment, are used in recognition of the inherent vertical uncertainty of the underlying data. These concepts were applied to conduct a sea-level rise vulnerability assessment of the Mobile Bay, Alabama, region based on high-quality lidar-derived elevation data. The results that detail the area and associated resources (land cover, population, and infrastructure) vulnerable to a 1.18-m sea-level rise by the year 2100 are reported as a range of values (at the 95% confidence level) to account for the vertical uncertainty in the base data. Examination of the tabulated statistics about land cover, population, and infrastructure in the minimum and maximum vulnerable areas shows that these resources are not uniformly distributed throughout the overall vulnerable zone. The methods demonstrated in the Mobile Bay analysis provide an example of how to consider and properly account for vertical uncertainty in elevation-based sea-level rise vulnerability assessments, and the advantages of doing so.

Alabama↗
USGS2006

Characterization of unsaturated zone hydrogeologic units using matrix properties and depositional history in a complex volcanic environment

Characterization of the physical and unsaturated hydrologic properties of subsurface materials is necessary to calculate flow and transport for land use practices and to evaluate subsurface processes such as perched water or lateral diversion of water, which are influenced by features such as faults, fractures, and abrupt changes in lithology. Input for numerical flow models typically includes parameters that describe hydrologic properties and the initial and boundary conditions for all materials in the unsaturated zone, such as bulk density, porosity, and particle density, saturated hydraulic conductivity, moisture-retention characteristics, and field water content. We describe an approach for systematically evaluating the site features that contribute to water flow, using physical and hydraulic data collected at the laboratory scale, to provide a representative set of physical and hydraulic parameters for numerically calculating flow of water through the materials at a site. An example case study from analyses done for the heterogeneous, layered, volcanic rocks at Yucca Mountain is presented, but the general approach for parameterization could be applied at any site where depositional processes follow deterministic patterns. Hydrogeologic units at this site were defined using (i) a database developed from 5320 rock samples collected from the coring of 23 shallow (<100 m) and 10 deep (500–1000 m) boreholes, (ii) lithostratigraphic boundaries and corresponding relations to porosity, (iii) transition zones with pronounced changes in properties over short vertical distances, (iv) characterization of the influence of mineral alteration on hydrologic properties such as permeability and moisture-retention characteristics, and (v) a statistical analysis to evaluate where boundaries should be adjusted to minimize the variance within layers. Model parameters developed in this study, and the relation of flow properties to porosity, can be used to produce detailed and accurate representations of the core-scale hydrologic processes ongoing at Yucca Mountain.

Vadose Zone Journal↗
USGS2018

Landsat time series analysis of fractional plant cover changes on abandoned energy development sites

Oil and natural gas development in the western United States has increased substantially in recent decades as technological advances like horizontal drilling and hydraulic fracturing have made extraction more commercially viable. Oil and gas pads are often developed for production, and then capped, reclaimed, and left to recover when no longer productive. Understanding the rates, controls, and degree of recovery of these reclaimed well sites to a state similar to pre-development conditions is critical for energy development and land management decision processes. Here we use a multi-decadal time series of satellite imagery (Landsat 5, 1984–2011) to assess vegetation regrowth on 365 abandoned well pads located across the Colorado Plateau in Utah, Colorado, and New Mexico. We developed high-frequency time series of the Soil-Adjusted Total Vegetation Index (SATVI) for each well pad using the Google Earth Engine cloud computing platform. BFAST time-series models were used to fit temporal trends, identifying when vegetation was cleared from the site and the magnitudes and rates of vegetation change after abandonment. The time series metrics are used to calculate the relative fractional vegetation cover (RFVC) of each pad, a measure of post-abandonment vegetation cover relative to pre-drilling condition. Mean and median RFVC were 36% (s.d. 33%) and 26%, respectively, five years after abandonment, with one third of well pads having RFVC greater than 50%. Statistical analyses suggest that much of the high vegetation cover is associated with weedy invasive annual species such as cheatgrass (Bromus tectorum) and Russian thistle (Salsola spp.). Climate conditions and the year of abandonment also play a role, with increased cover in later years associated with a wetter period. Non-linear change at many pads suggests longer recovery times than would be estimated by linear extrapolation. New techniques implemented here address a complex response of cover change to soils, management, and climate over time, and can be extended to the operational monitoring of energy development across large areas.

International Journal of Applied Earth Observation↗
USGS2013

Circuit theory and model-based inference for landscape connectivity

Circuit theory has seen extensive recent use in the field of ecology, where it is often applied to study functional connectivity. The landscape is typically represented by a network of nodes and resistors, with the resistance between nodes a function of landscape characteristics. The effective distance between two locations on a landscape is represented by the resistance distance between the nodes in the network. Circuit theory has been applied to many other scientific fields for exploratory analyses, but parametric models for circuits are not common in the scientific literature. To model circuits explicitly, we demonstrate a link between Gaussian Markov random fields and contemporary circuit theory using a covariance structure that induces the necessary resistance distance. This provides a parametric model for second-order observations from such a system. In the landscape ecology setting, the proposed model provides a simple framework where inference can be obtained for effects that landscape features have on functional connectivity. We illustrate the approach through a landscape genetics study linking gene flow in alpine chamois (Rupicapra rupicapra) to the underlying landscape.

Journal of the American Statistical Association↗
USGS2013

Radiometric cross-calibration of EO-1 ALI with L7 ETM+ and Terra MODIS sensors using near-simultaneous desert observations

The Earth Observing-1 (EO-1) satellite was launched on November 21, 2000, as part of a one-year technology demonstration mission. The mission was extended because of the value it continued to add to the scientific community. EO-1 has now been operational for more than a decade, providing both multispectral and hyperspectral measurements. As part of the EO-1 mission, the Advanced Land Imager (ALI) sensor demonstrates a potential technological direction for the next generation of Landsat sensors. To evaluate the ALI sensor capabilities as a precursor to the Operational Land Imager (OLI) onboard the Landsat Data Continuity Mission (LDCM, or Landsat 8 after launch), its measured top-of-atmosphere (TOA) reflectances were compared to the well-calibrated Landsat 7 (L7) Enhanced Thematic Mapper Plus (ETM+) and the Terra Moderate Resolution Imaging Spectroradiometer (MODIS) sensors in the reflective solar bands (RSB). These three satellites operate in a near-polar, sun-synchronous orbit 705 km above the Earth's surface. EO-1 was designed to fly one minute behind L7 and approximately 30 minutes in front of Terra. In this configuration, all the three sensors can view near-identical ground targets with similar atmospheric, solar, and viewing conditions. However, because of the differences in the relative spectral response (RSR), the measured physical quantities can be significantly different while observing the same target. The cross-calibration of ALI with ETM+ and MODIS was performed using near-simultaneous surface observations based on image statistics from areas observed by these sensors over four desert sites (Libya 4, Mauritania 2, Arabia 1, and Sudan 1). The differences in the measured TOA reflectances due to RSR mismatches were compensated by using a spectral band adjustment factor (SBAF), which takes into account the spectral profile of the target and the RSR of each sensor. For this study, the spectral profile of the target comes from the near-simultaneous EO-1 Hyperion data over these sites. The results indicate that the TOA reflectance measurements for ALI agree with those of ETM+ and MODIS to within 5% after the application of SBAF.

Arabia↗
USGS2015

Mapping of coal quality using stochastic simulation and isometric logratio transformation with an application to a Texas lignite

Coal is a chemically complex commodity that often contains most of the natural elements in the periodic table. Coal constituents are conventionally grouped into four components (proximate analysis): fixed carbon, ash, inherent moisture, and volatile matter. These four parts, customarily measured as weight losses and expressed as percentages, share all properties and statistical challenges of compositional data. Consequently, adequate modeling should be done in terms of a logratio transformation, a requirement that is commonly overlooked by modelers. The transformation of choice is the isometric logratio transformation because of its geometrical and statistical advantages. The modeling is done through a series of realizations prepared by applying sequential simulation for the purpose of displaying the parts in maps incorporating uncertainty. The approach makes realistic assumptions and the results honor the data and basic considerations, such as percentages between 0 and 100, all four parts adding to 100% at any location in the study area, and a style of spatial fluctuation in the realizations equal to that of the data. The realizations are used to prepare different results, including probability distributions across a deposit, E-type maps displaying average properties, and probability maps summarizing joint fluctuations of several parts. Application of these maps to a lignite bed clearly delineates the deposit boundary, reveals a channel cutting across, and shows that the most favorable coal quality is to the north and deteriorates toward the southeast.

International Journal of Coal Geology↗
USGS2016

Probabilistic assessment of erosion and flooding risk in the northern Gulf of Mexico

We assess erosion and flooding risk in the northern Gulf of Mexico by identifying interdependencies among oceanographic drivers and probabilistically modeling the resulting potential for coastal change. Wave and water level observations are used to determine relationships between six hydrodynamic parameters that influence total water level and therefore erosion and flooding, through consideration of a wide range of univariate distribution functions and multivariate elliptical copulas. Using these relationships, we explore how different our interpretation of the present-day erosion/flooding risk could be if we had seen more or fewer extreme realizations of individual and combinations of parameters in the past by simulating 10,000 physically and statistically consistent sea-storm time series. We find that seasonal total water levels associated with the 100 year return period could be up to 3 m higher in summer and 0.6 m higher in winter relative to our best estimate based on the observational records. Impact hours of collision and overwash—where total water levels exceed the dune toe or dune crest elevations—could be on average 70% (collision) and 100% (overwash) larger than inferred from the observations. Our model accounts for non-stationarity in a straightforward, non-parametric way that can be applied (with little adjustments) to many other coastlines. The probabilistic model presented here, which accounts for observational uncertainty, can be applied to other coastlines where short record lengths limit the ability to identify the full range of possible wave and water level conditions that coastal mangers and planners must consider to develop sustainable management strategies.

Journal of Geophysical Research C: Oceans↗
USGS2002

Predictive evaluation of size restrictions as management strategies for tennessee reservoir crappie fisheries

We evaluated the potential effect of minimum size restrictions on crappies Pomoxis spp. in 12 large Tennessee reservoirs. A Beverton-Holt equilibrium yield model was used to predict and compare the response of these fisheries to three minimum size restrictions: 178 mm (i.e., pragmatically, no size limit), 229 mm, and the current statewide limit of 254 mm. The responses of crappie fisheries to size limits differed among reservoirs and varied with rates of conditional natural mortality (CM). Based on model results, crappie fisheries fell into one of three response categories: (1) In some reservoirs (N = 5), 254-mm and 229-mm limits would benefit the fishery in terms of yield if CM were low (30%); the associated declines in the number of crappies harvested would be significant but modest when compared with those in other reservoirs. (2) In other reservoirs (N = 6), little difference in yield existed among size restrictions at low to intermediate rates of CM (30-40%). In these reservoirs, a 229-mm limit was predicted to be a more beneficial regulation than the current 254-mm limit. (3) In the remaining reservoir, Tellico, size limits negatively affected all three harvest statistics. Generally, yield was negatively affected by size limits in all populations at a CM of 50%. The number of crappies reaching 300 mm was increased by size limits in most model scenarios: however, associated declines in the total number of crappies harvested often outweighed the benefits to size structure when CM was 40% or higher. When crappie growth was fast (reaching 254 mm in less than 3 years) and CM was low (30%), size limits were most effective in balancing increases in yield and size structure against declines in the total number of crappies harvested. The variability in predicted size-limit responses observed among Tennessee reservoirs suggests that using a categorical approach to applying size limits to crappie fisheries within a state or region would likely be a more effective management strategy than implementing a single, areawide regulation.

North American Journal of Fisheries Management↗
USGS2004

Assessing the fit of site-occupancy models

Few species are likely to be so evident that they will always be detected at a site when present. Recently a model has been developed that enables estimation of the proportion of area occupied, when the target species is not detected with certainty. Here we apply this modeling approach to data collected on terrestrial salamanders in the Plethodon glutinosus complex in the Great Smoky Mountains National Park, USA, and wish to address the question 'how accurately does the fitted model represent the data?' The goodness-of-fit of the model needs to be assessed in order to make accurate inferences. This article presents a method where a simple Pearson chi-square statistic is calculated and a parametric bootstrap procedure is used to determine whether the observed statistic is unusually large. We found evidence that the most global model considered provides a poor fit to the data, hence estimated an overdispersion factor to adjust model selection procedures and inflate standard errors. Two hypothetical datasets with known assumption violations are also analyzed, illustrating that the method may be used to guide researchers to making appropriate inferences. The results of a simulation study are presented to provide a broader view of the methods properties.

North Carolina, Tennessee↗
USGS2009

Mineral Commodity Summaries 2009

Each chapter of the 2009 edition of the U.S. Geological Survey (USGS) Mineral Commodity Summaries (MCS) includes information on events, trends, and issues for each mineral commodity as well as discussions and tabular presentations on domestic industry structure, Government programs, tariffs, 5-year salient statistics, and world production and resources. The MCS is the earliest comprehensive source of 2008 mineral production data for the world. More than 90 individual minerals and materials are covered by two-page synopses. For mineral commodities for which there is a Government stockpile, detailed information concerning the stockpile status is included in the two-page synopsis. Because specific information concerning committed inventory was no longer available from the Defense Logistics Agency, National Defense Stockpile Center, that information, which was included in earlier Mineral Commodity Summaries publications, has been deleted from Mineral Commodity Summaries 2009. National reserves and reserve base information for most mineral commodities found in this report, including those for the United States, are derived from a variety of sources. The ideal source of such information would be comprehensive evaluations that apply the same criteria to deposits in different geographic areas and report the results by country. In the absence of such evaluations, national reserves and reserve base estimates compiled by countries for selected mineral commodities are a primary source of national reserves and reserve base information. Lacking national assessment information by governments, sources such as academic articles, company reports, common business practice, presentations by company representatives, and trade journal articles, or a combination of these, serve as the basis for national reserves and reserve base information reported in the mineral commodity sections of this publication. A national estimate may be assembled from the following: historically reported reserves and reserve base information carried for years without alteration because no new information is available; historically reported reserves and reserve base reduced by the amount of historical production; and company reported reserves. International minerals availability studies conducted by the U.S. Bureau of Mines, before 1996, and estimates of identified resources by an international collaborative effort (the International Strategic Minerals Inventory) are the basis for some reserves and reserve base estimates. The USGS collects information about the quantity and quality of mineral resources but does not directly measure reserves, and companies or governments do not directly report reserves or reserve base to the USGS. Reassessment of reserves and reserve base is a continuing process, and the intensity of this process differs for mineral commodities, countries, and time period. Abbreviations and units of measure, and definitions of selected terms used in the report, are in Appendix A and Appendix B, respectively. A resource/reserve classification for minerals, based on USGS Circular 831 (published with the U.S. Bureau of Mines) is Appendix C, and a directory of USGS minerals information country specialists and their responsibilities is Appendix D. The USGS continually strives to improve the value of its publications to users. Constructive comments and suggestions by readers of the MCS 2009 are welcomed.

Mineral Commodity Summaries↗
USGS2010

Hierarchical spatial models for predicting pygmy rabbit distribution and relative abundance

Conservationists routinely use species distribution models to plan conservation, restoration and development actions, while ecologists use them to infer process from pattern. These models tend to work well for common or easily observable species, but are of limited utility for rare and cryptic species. This may be because honest accounting of known observation bias and spatial autocorrelation are rarely included, thereby limiting statistical inference of resulting distribution maps. We specified and implemented a spatially explicit Bayesian hierarchical model for a cryptic mammal species (pygmy rabbit Brachylagus idahoensis). Our approach used two levels of indirect sign that are naturally hierarchical (burrows and faecal pellets) to build a model that allows for inference on regression coefficients as well as spatially explicit model parameters. We also produced maps of rabbit distribution (occupied burrows) and relative abundance (number of burrows expected to be occupied by pygmy rabbits). The model demonstrated statistically rigorous spatial prediction by including spatial autocorrelation and measurement uncertainty. We demonstrated flexibility of our modelling framework by depicting probabilistic distribution predictions using different assumptions of pygmy rabbit habitat requirements. Spatial representations of the variance of posterior predictive distributions were obtained to evaluate heterogeneity in model fit across the spatial domain. Leave-one-out cross-validation was conducted to evaluate the overall model fit. Synthesis and applications. Our method draws on the strengths of previous work, thereby bridging and extending two active areas of ecological research: species distribution models and multi-state occupancy modelling. Our framework can be extended to encompass both larger extents and other species for which direct estimation of abundance is difficult. ?? 2010 The Authors. Journal compilation ?? 2010 British Ecological Society.

Journal of Applied Ecology↗
USGS2013

Seismicity around Parkfield correlates with static shear stress changes following the 2003 M w 6.5 San Simeon earthquake

Earthquakes trigger other earthquakes, but the physical mechanism of the triggering is currently debated. Most studies of earthquake triggering rely on earthquakes listed in catalogs, which are known to be incomplete around the origin times of large earthquakes and therefore missing potentially triggered events. Here we apply a waveform matched-filter technique to systematically detect earthquakes along the Parkfield section of the San Andreas Fault from 46 days before to 31 days after the nearby 2003 M w 6.5 San Simeon earthquake. After removing all possible false detections, we identify ~8 times more earthquakes than in the Northern California Seismic Network catalog. The newly identified events along the creeping section of the San Andreas Fault show a statistically significant decrease following the San Simeon main shock, which correlates well with the negative static stress changes (i.e., stress shadow) cast by the main shock. In comparison, the seismicity rate around Parkfield increased moderately where the static stress changes are positive. The seismicity rate changes correlate well with the static shear stress changes induced by the San Simeon main shock, suggesting a low friction in the seismogenic zone along the Parkfield section of the San Andreas Fault.

California↗
USGS2002

Impacts of off-road vehicles on nitrogen cycles in biological soil crusts: Resistance in different U.S. deserts

Biological soil crusts are an important component of desert ecosystems, as they influence soil stability and fertility. This study examined and compared the short-term vehicular impacts on lichen cover and nitrogenase activity (NA) of biological soil crusts. Experimental disturbance was applied to different types of soil in regions throughout the western U.S. (Great Basin, Colorado Plateau, Sonoran, Chihuahuan, and Mojave deserts). Results show that pre-disturbance cover of soil lichens is significantly correlated with the silt content of soils, and negatively correlated with sand and clay. While disturbance appeared to reduce NA at all sites, differences were statistically significant at only 12 of the 26 sites. Cool desert sites showed a greater decline than hot desert sites, which may indicate non-heterocystic cyanobacterial species are more susceptible to disturbance than non-heterocystic species. Sandy soils showed greater reduction of NA as sand content increased, while fine-textured soils showed a greater decline as sand content increased. At all sites, higher NA before the disturbance resulted in less impact to NA post-disturbance. These results may be useful in predicting the impacts of off-road vehicles in different regions and different soils.

Journal of Arid Environments↗