SEARCH · USGS Science

Results for “Spatial Statistics”

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

SourceResearch connectionFrom yearThrough year

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

At least 379 records · Page 21Linked to original sources

USGS2004

Using counts to simultaneously estimate abundance and detection probabilities in a salamander community

A critical variable in both ecological and conservation field studies is determining how many individuals of a species are present within a defined sampling area. Labor intensive techniques such as capture-mark-recapture and removal sampling may provide estimates of abundance, but there are many logistical constraints to their widespread application. Many studies on terrestrial and aquatic salamanders use counts as an index of abundance, assuming that detection remains constant while sampling. If this constancy is violated, determination of detection probabilities is critical to the accurate estimation of abundance. Recently, a model was developed that provides a statistical approach that allows abundance and detection to be estimated simultaneously from spatially and temporally replicated counts. We adapted this model to estimate these parameters for salamanders sampled over a six vear period in area-constrained plots in Great Smoky Mountains National Park. Estimates of salamander abundance varied among years, but annual changes in abundance did not vary uniformly among species. Except for one species, abundance estimates were not correlated with site covariates (elevation/soil and water pH, conductivity, air and water temperature). The uncertainty in the estimates was so large as to make correlations ineffectual in predicting which covariates might influence abundance. Detection probabilities also varied among species and sometimes among years for the six species examined. We found such a high degree of variation in our counts and in estimates of detection among species, sites, and years as to cast doubt upon the appropriateness of using count data to monitor population trends using a small number of area-constrained survey plots. Still, the model provided reasonable estimates of abundance that could make it useful in estimating population size from count surveys.

Herpetologica↗

USGS1992

A technique for the reduction of banding in Landsat Thematic Mapper Images

The radiometric difference between forward and reverse scans in Landsat thematic mapper (TM) images, referred to as "banding," can create problems when enhancing the image for interpretation or when performing quantitative studies. Recent research has led to the development of a method that reduces the banding in Landsat TM data sets. It involves passing a one-dimensional spatial kernel over the data set. This kernel is developed from the statistics of the banding pattern and is based on the Wiener filter. It has been implemented on both a DOS-based microcomputer and several UNIX-based computer systems. The algorithm has successfully reduced the banding in several test data sets.

Photogrammetric Engineering and Remote Sensing↗

USGS2015

Differentiating induced and natural seismicity using space-time-magnitude statistics applied to the Coso Geothermal field

A remarkable characteristic of earthquakes is their clustering in time and space, displaying their self-similarity. It remains to be tested if natural and induced earthquakes share the same behavior. We study natural and induced earthquakes comparatively in the same tectonic setting at the Coso Geothermal Field. Covering the preproduction and coproduction periods from 1981 to 2013, we analyze interevent times, spatial dimension, and frequency-size distributions for natural and induced earthquakes. Individually, these distributions are statistically indistinguishable. Determining the distribution of nearest neighbor distances in a combined space-time-magnitude metric, lets us identify clear differences between both kinds of seismicity. Compared to natural earthquakes, induced earthquakes feature a larger population of background seismicity and nearest neighbors at large magnitude rescaled times and small magnitude rescaled distances. Local stress perturbations induced by field operations appear to be strong enough to drive local faults through several seismic cycles and reactivate them after time periods on the order of a year.

California↗

USGS2008

Identification of spectral units on Phoebe

We apply a multivariate statistical method to the Phoebe spectra collected by the VIMS experiment onboard the Cassini spacecraft during the flyby of June 2004. The G-mode clustering method, which permits identification of the most important features in a spectrum, is used on a small subset of data, characterized by medium and high spatial resolution, to perform a raw spectral classification of the surface of Phoebe. The combination of statistics and comparative analysis of the different areas using both the VIMS and ISS data is explored in order to highlight possible correlations with the surface geology. In general, the results by Clark et al. [Clark, R.N., Brown, R.H., Jaumann, R., Cruikshank, D.P., Nelson, R.M., Buratti, B.J., McCord, T.B., Lunine, J., Hoefen, T., Curchin, J.M., Hansen, G., Hibbitts, K., Matz, K.-D., Baines, K.H., Bellucci, G., Bibring, J.-P., Capaccioni, F., Cerroni, P., Coradini, A., Formisano, V., Langevin, Y., Matson, D.L., Mennella, V., Nicholson, P.D., Sicardy, B., Sotin, C., 2005. Nature 435, 66-69] are confirmed; but we also identify new signatures not reported before, such as the aliphatic CH stretch at 3.53 ??m and the ???4.4 ??m feature possibly related to cyanide compounds. On the basis of the band strengths computed for several absorption features and for the homogeneous spectral types isolated by the G-mode, a strong correlation of CO2 and aromatic hydrocarbons with exposed water ice, where the uniform layer covering Phoebe has been removed, is established. On the other hand, an anti-correlation of cyanide compounds with CO2 is suggested at a medium resolution scale. ?? 2007 Elsevier Inc. All rights reserved.

Icarus↗

USGS2019

Characterizing groundwater/surface-water interaction using hydrograph-separation techniques and groundwater-level data throughout the Mississippi Delta, USA

The Mississippi Delta, located in northwest Mississippi, is an area dense with industrial-level agriculture sustained by groundwater-dependent irrigation supplied by the Mississippi River Valley Alluvial aquifer (alluvial aquifer). The Delta provides agricultural commodities across the United States and around the world. Observed declines in groundwater altitudes and streamflow contemporaneous with increases in irrigation have raised concerns about future groundwater availability and the effects of groundwater withdrawals on streamflow. To quantify the impacts of groundwater withdrawals on streamflow and increase understanding of groundwater and surface-water interaction, hydrograph-separation techniques were used to estimate baseflow and identify statistical streamflow trends. The analysis was conducted using the U.S. Geological Survey Groundwater Toolbox open-source software and daily hydrologic data provided by a spatially-distributed network of paired groundwater wells and streamgaging sites. This study found that effects of groundwater withdrawals on streamflow were observed as statistically significant reductions in baseflow in areas with substantial groundwater-altitude declines. Hydrograph-separation and trend analyses may be applicable to assess the impacts of groundwater withdrawals in altered environments and streamflow may be used as a proxy for changes in groundwater availability. Characterizing and defining hydrologic relations between groundwater and surface water will help scientists and water-resource managers refine a regional groundwater-flow model that includes the Mississippi Delta that will be used to aid water-resource managers in future decisions concerning the alluvial aquifer.

Arkansas, Illinois, Kentucky, Louisiana, Mississip↗

USGS2012

Seismicity and detection/location threshold in the southern Great Basin seismic network

A spatially varying model of the detection/location capabilities of the Southern Great Basin seismic network (SGBSN) has been derived that is based on simple empirical relations and statistics. This permits use of almost all the catalog data gathered; instead of ignoring data that are below the threshold of completeness, a spatially varying threshold model is developed so that subregions having lower completeness levels than the network as a whole can be outlined and the completeness level of each sub-region determined. Such a model is required to unambiguously identify regions that are aseismic due to natural processes rather than to limited detection and/or location capabilities. Accounting for spatial variations in detection/location threshold is also important for studies in which magnitude-frequency distributions are interpreted in terms of source scaling properties. The characteristics of the spatial distribution of earthquakes, where earthquake clusters and aseismic regions locate, appear to be stable at all magnitude levels so that inferences about where strain is being accommodated will be the same whether numbers of earthquakes or strain estimated from seismic moments are examined. For the southern Great Basin region these principal characteristics include clusters at the northern end of the Furnace Creek fault and in the Pahranagat Shear Zone, and a relatively large number of earthquakes in the northern and southeastern portions of the Nevada Test Site. These clusters cover regions much larger than the surface projections of any of the mapped faults. The extent to which seismicity is induced by nuclear testing is unclear. The predominantly aseismic regions include the area west of the Death Valley/Furnace Creek fault system and an almost complete absence of events at Yucca Mountain. Finally, a considerable number of isolated events in the SGBSN catalog cannot be correlated with mapped faults.

Journal of Geophysical Research↗

USGS2013

Status and understanding of groundwater quality in the Madera, Chowchilla Study Unit, 2008: California GAMA Priority Basin Project

Groundwater quality in the approximately 860-square-mile Madera and Chowchilla Subbasins (Madera-Chowchilla study unit) of the San Joaquin Valley Basin was investigated as part of the Priority Basin Project of the Groundwater Ambient Monitoring and Assessment (GAMA) Program. The study unit is located in California's Central Valley region in parts of Madera, Merced, and Fresno Counties. The GAMA Priority Basin Project is being conducted by the California State Water Resources Control Board in collaboration with the U.S. Geological Survey (USGS) and the Lawrence Livermore National Laboratory. The Project was designed to provide statistically robust assessments of untreated groundwater quality within the primary aquifer systems in California. The primary aquifer system within each study unit is defined by the depth of the perforated or open intervals of the wells listed in the California Department of Public Health (CDPH) database of wells used for municipal and community drinking-water supply. The quality of groundwater in shallower or deeper water-bearing zones may differ from that in the primary aquifer system; shallower groundwater may be more vulnerable to contamination from the surface. The assessments for the Madera-Chowchilla study unit were based on water-quality and ancillary data collected by the USGS from 35 wells during April-May 2008 and water-quality data reported in the CDPH database. Two types of assessments were made: (1) status , assessment of the current quality of the groundwater resource, and (2) understanding , identification of natural factors and human activities affecting groundwater quality. The primary aquifer system is represented by the grid wells, of which 90 percent (%) had depths that ranged from about 200 to 800 feet (ft) below land surface and had depths to the top of perforations that ranged from about 140 to 400 ft below land surface. Relative-concentrations (sample concentrations divided by benchmark concentrations) were used for evaluating groundwater quality for those constituents that have Federal or California regulatory or non-regulatory benchmarks for drinking-water quality. A relative-concentration (RC) greater than 1.0 indicates a concentration above a benchmark. RCs for organic constituents (volatile organic compounds and pesticides) and special-interest constituents (perchlorate) were classified as "high" (RC is greater than 1.0), "moderate" (RC is less than or equal to 1.0 and greater than 0.1), or "low" (RC is less than or equal to 0.1). For inorganic constituents (major and minor ions, trace elements, nutrients, and radioactive constituents), the boundary between low and moderate RCs was set at 0.5. The assessments characterize untreated groundwater quality, not the quality of treated drinking water delivered to consumers by water purveyors; drinking-water benchmarks, and thus relative-concentrations, are used to provide context for the concentrations of constituents measured in groundwater. Aquifer-scale proportion was used in the status assessment as the primary metric for evaluating regional-scale groundwater quality. High aquifer-scale proportion is defined as the percentage of the area of the primary aquifer system with RCs greater than 1.0 for a particular constituent or class of constituents; moderate and low aquifer-scale proportions are defined as the percentages of the area of the primary aquifer system with moderate and low RCs, respectively. Percentages are based on an areal, rather than a volumetric basis. Two statistical approaches--grid-based, which used one value per grid cell, and spatially weighted, which used multiple values per grid cell--were used to calculate aquifer-scale proportions for individual constituents and classes of constituents. The spatially weighted estimates of high aquifer-scale proportions were within the 90% confidence intervals of the grid-based estimates for all constituents except iron. The status assessment showed that inorganic constituents had greater high and moderate aquifer-scale proportions in the Madera-Chowchilla study unit than did organic constituents. RCs for inorganic constituents with health-based benchmarks were high in 37% of the primary aquifer system, moderate in 30%, and low in 33%. The inorganic constituents contributing most to the high aquifer-scale proportion were arsenic (13%), uranium (17%), gross alpha particle activity (20%), nitrate (6.7%), and vanadium (3.3%). RCs for inorganic constituents with non-health-based benchmarks were high in 6.7% of the primary aquifer system, and the constituent contributing most to the high aquifer-scale proportion was total dissolved solids (TDS). RCs for organic constituents with health-based benchmarks were high in 10% of the primary aquifer system, moderate in 3.3%, and low in 40%; organic constituents were not detected in 47% of the primary aquifer system. The fumigant 1,2-dibromo-3-chloropropane (DBCP) was the only organic constituent detected at high RCs. Seven organic constituents were detected in 10% or more of the primary aquifer system: DBCP; the fumigant additive 1,2,3-trichloropropane; the herbicides simazine, atrazine, and diuron; the trihalomethane chloroform; and the solvent tetrachloroethene (PCE). RCs for the special-interest constituent perchlorate were moderate in 20% of the primary aquifer system. The second component of this study, the understanding assessment , identified the natural and human factors that may affect groundwater quality by evaluating statistical correlations between water-quality constituents and potential explanatory factors, such as land use, position relative to important geologic features, groundwater age, well depth, and geochemical conditions in the aquifer. Results of the statistical evaluations were used to explain the distribution of constituents in the study unit. Depth to the top of perforations in the well and groundwater age were the most important explanatory factors for many constituents. High and moderate RCs of nitrate, uranium, and TDS and the presence of herbicides, trihalomethanes, and solvents were all associated with depths to the top of perforations less than 235 ft and modern- and mixed-age groundwater. Positive correlations between uranium, bicarbonate, TDS, and the proportion of calcium and magnesium in the total cations suggest that downward movement of recharge from irrigation water contributed to the elevated concentrations of these constituents in the primary aquifer system. High and moderate RCs of arsenic were associated with depths to the top of perforations greater than 235 ft, mixed- and pre-modern-age groundwater, and location in sediments from the Chowchilla River alluvial fan, suggesting that increased residence time and appropriate aquifer materials were needed for arsenic to accumulate in the groundwater. High and moderate RCs of fumigants were associated with depths to the top of perforations of less than 235 ft and location south of the city of Madera; low RCs of fumigants were detected in wells dispersed across the study unit with a range of depths to top of perforations.

California↗

USGS2022

Hydrologic recovery after wildfire: A framework of approaches, metrics, criteria, trajectories, and timescales

Deviations in hydrologic processes due to wildfire can alter streamflows across the hydrograph, spanning peak flows to low flows. Fire-enhanced changes in hydrologic processes, including infiltration, interception, and evapotranspiration, and the resulting streamflow responses can affect water supplies, through effects on the quantity, quality, and timing of water availability. Post-fire shifts in hydrologic processes can also alter the timing and magnitude of floods and debris flows. The duration of hydrologic deviations from a pre-fire condition or function, sometimes termed hydrologic recovery, is a critical concern for land, water, and emergency managers. We reviewed and summarized terminology and approaches for defining and assessing hydrologic recovery after wildfire, focusing on statistical and functional definitions. We critically examined advantages and drawbacks of current recovery assessment methods, outline challenges to determining recovery, and call attention to selected opportunities for advancement of post-fire hydrologic recovery assessment. Selected challenges included hydroclimatic variability, post-fire land management, and spatial and temporal variability. The most promising opportunities for advancing assessment of hydrologic recovery include: (1) combining statistical and functional recovery approaches, (2) using a greater diversity of post-fire observations complemented with hydrologic modeling, and (3) defining optimal assemblages of recovery metrics and criteria for common hydrologic concerns and regions.

Journal of Hydrology and Hydromechanics↗

USGS2013

Computationally efficient statistical differential equation modeling using homogenization

Statistical models using partial differential equations (PDEs) to describe dynamically evolving natural systems are appearing in the scientific literature with some regularity in recent years. Often such studies seek to characterize the dynamics of temporal or spatio-temporal phenomena such as invasive species, consumer-resource interactions, community evolution, and resource selection. Specifically, in the spatial setting, data are often available at varying spatial and temporal scales. Additionally, the necessary numerical integration of a PDE may be computationally infeasible over the spatial support of interest. We present an approach to impose computationally advantageous changes of support in statistical implementations of PDE models and demonstrate its utility through simulation using a form of PDE known as “ecological diffusion.” We also apply a statistical ecological diffusion model to a data set involving the spread of mountain pine beetle (Dendroctonus ponderosae) in Idaho, USA.

Journal of Agricultural, Biological, and Environme↗

USGS2012

Status and understanding of groundwater quality in the Tahoe-Martis, Central Sierra, and Southern Sierra study units, 2006-2007--California GAMA Priority Basin Project

Groundwater quality in the Tahoe-Martis, Central Sierra, and Southern Sierra study units was investigated as part of the Priority Basin Project of the California Groundwater Ambient Monitoring and Assessment (GAMA) Program. The three study units are located in the Sierra Nevada region of California in parts of Nevada, Placer, El Dorado, Madera, Tulare, and Kern Counties. The GAMA Priority Basin Project is being conducted by the California State Water Resources Control Board, in collaboration with the U.S. Geological Survey (USGS) and the Lawrence Livermore National Laboratory. The project was designed to provide statistically robust assessments of untreated groundwater quality within the primary aquifer systems used for drinking water. The primary aquifer systems (hereinafter, primary aquifers) for each study unit are defined by the depth of the screened or open intervals of the wells listed in the California Department of Public Health (CDPH) database of wells used for municipal and community drinking-water supply. The quality of groundwater in shallower or deeper water-bearing zones may differ from that in the primary aquifers; shallower groundwater may be more vulnerable to contamination from the surface. The assessments for the Tahoe-Martis, Central Sierra, and Southern Sierra study units were based on water-quality and ancillary data collected by the USGS from 132 wells in the three study units during 2006 and 2007 and water-quality data reported in the CDPH database. Two types of assessments were made: (1) status, assessment of the current quality of the groundwater resource, and (2) understanding, identification of the natural and human factors affecting groundwater quality. The assessments characterize untreated groundwater quality, not the quality of treated drinking water delivered to consumers by water purveyors. Relative-concentrations (sample concentrations divided by benchmark concentrations) were used for evaluating groundwater quality for those constituents that have Federal or California regulatory or non-regulatory benchmarks for drinking-water quality. A relative-concentration (RC) greater than (>) 1.0 indicates a concentration above a benchmark. RCs for organic constituents (volatile organic compounds and pesticides) and special-interest constituents were classified as "high" (RC > 1.0), "moderate" (1.0 ≥ RC > 0.1), or "low" (RC ≤ 0.1). For inorganic constituents (major ions, trace elements, nutrients, and radioactive constituents), the boundary between low and moderate RCs was set at 0.5. A new metric, aquifer-scale proportion, was used in the status assessment as the primary metric for evaluating regional-scale groundwater quality. High aquifer-scale proportion is defined as the percentage of the area of the primary aquifers with RC > 1.0 for a particular constituent or class of constituents; moderate and low aquifer-scale proportions are defined as the percentages of the area of the primary aquifer with moderate and low RCs, respectively. Percentages are based on an areal rather than a volumetric basis. Two statistical approaches—grid-based, which used one value per grid cell, and spatially weighted, which used multiple values per grid cell—were used to calculate aquifer-scale proportions for individual constituents and classes of constituents. The spatially weighted estimates of high aquifer-scale proportions were within the 90-percent (%) confidence intervals of the grid-based estimates in all cases. The status assessment showed that inorganic constituents had greater high and moderate aquifer-scale proportions than did organic constituents in all three study units. In the Tahoe-Martis study unit, RCs for inorganic constituents with health-based benchmarks (primarily arsenic) were high in 20% of the primary aquifer, moderate in 13%, and low in 67%. In the Central Sierra study unit, aquifer-scale proportions for inorganic constituents with health-based benchmarks (primarily arsenic, uranium, fluoride, and molybdenum) were 41% high, 36% moderate, and 23% low. In the Southern Sierra study unit, 32, 34, and 34% of the primary aquifer had high, moderate, and low RCs of inorganic constituents with health-based benchmarks (primarily arsenic, uranium, fluoride, boron, and nitrate). The high aquifer-scale proportions for inorganic constituents with non-health-based benchmarks were 14, 34, and 24% for the Tahoe-Martis, Central Sierra, and Southern Sierra study units, respectively, and the primary constituent was manganese for all three study units. Organic constituents with health-based benchmarks were not present at high RCs in the primary aquifers of the Central Sierra and Southern Sierra study units, and were present at high RCs in only 1% of the Tahoe-Martis study unit. Moderate aquifer-scale proportions for organic constituents were < 5% in all three study units. Of the 173 organic constituents analyzed, 22 were detected, and of those 22, 17 have health-based benchmarks. Organic constituents were detected in 20, 27, and 40% of the primary aquifers in the Tahoe-Martis, Central Sierra, and Southern Sierra study units, respectively. Four organic constituents had study-unit detection frequencies of > 10%: the trihalomethane chloroform in the Tahoe-Martis study unit; chloroform and the herbicide simazine in the Central Sierra study unit; and chloroform, simazine, the herbicide atrazine, and the solvent perchloroethene in the Southern Sierra study unit. The second component of this study, the understanding assessment, identified the natural and human factors that may have affected groundwater quality in the three study units by evaluating statistical correlations between water-quality constituents and potential explanatory factors. The potential explanatory factors evaluated were land use, septic tank density, climate, relative position in the regional flow system, aquifer lithology, geographic location, well depth and depth to the top of the screened or open interval in the well, groundwater age distribution, pH, and dissolved oxygen concentration. Results of the statistical evaluations were used to explain the occurrence and distribution of constituents in the study units. Aquifer lithology (granitic, metamorphic, sedimentary, or volcanic rocks), groundwater age distribution [modern (recharged since 1952), pre-modern (recharged before 1952), or mixed (containing both modern and pre-modern recharge)], geographic location, pH, and dissolved oxygen were the most significant factors explaining the occurrence patterns of most inorganic constituents. High and moderate RCs of arsenic were associated with pre-modern and mixed-age groundwater and two distinct sets of geochemical conditions: (1) oxic, high-pH conditions, particularly in volcanic rocks, and (2) low-oxygen to anoxic conditions and low- to neutral-pH conditions, particularly in granitic rocks. In granitic and metamorphic rocks, high and moderate RCs of uranium were associated with pre-modern and mixed-age groundwater, low-oxygen to anoxic conditions, and location within parts of the Central Sierra and Southern Sierra study units known to have rocks with anomalously high uranium content compared to other parts of the Sierra Nevada. High and moderate RCs of uranium in sedimentary rocks were associated with pre-modern-age groundwater, oxic and high-pH conditions, and location in the Tahoe Valley South subbasin within the Tahoe-Martis study unit. Land use within 500 meters of the well and groundwater age were the most significant factors explaining occurrence patterns of organic constituents. Herbicide detections were most strongly associated with modern- and mixed-age groundwater from wells with agricultural land use. Trihalomethane detections were most strongly associated with modern- and mixed-age groundwater from wells with > 10% urban land use and (or) septic tank density > 7 tanks per square kilometer. Solvent detections were not significantly related to groundwater age. Eighty-three percent of the wells with modern- or mixed-age groundwater, and 86% of wells with detections of herbicides and (or) THMs had depths to the top of the screened or open interval of < 170 feet. These observations suggest that modern groundwater has infiltrated to depths of approximately 170 feet below land surface. Land use and occurrence of herbicides and solvents were the most significant factors explaining the occurrence of nitrate. Wells with > 5% agricultural land use and detection of a herbicide or solvent had the highest nitrate concentrations. Comparison between observed and predicted detection frequencies of perchlorate suggests that the perchlorate detected at concentrations < 1 microgram per liter likely reflects the distribution of perchlorate under natural conditions, and that the perchlorate detected at higher concentrations may reflect redistribution of originally natural perchlorate salts by irrigation in the agricultural areas of the Southern Sierra study unit.

California↗

USGS2021

Modeling at-sea density of marine birds to support renewable energy planning on the Pacific outer continental shelf of the contiguous United States

This report describes the at-sea spatial distributions of marine birds in Pacific OCS waters off the contiguous U.S. (Figure 1.1) to inform marine spatial planning in the region. The goal was to estimate long-term average spatial distributions for marine bird species using all available science-quality transect survey data and numerous bathymetric, oceanographic, and atmospheric predictor variables. We developed seasonal habitat-based spatial models of the at-sea distribution for 33 individual species and 13 taxonomic groups of marine birds throughout the study region. A statistical modeling framework was used to estimate numerical relationships between bird sighting data (i.e., standardized counts) and a range of temporal (e.g., Pacific Decadal Oscillation [PDO] index), spatially static (e.g., depth), and spatially dynamic (e.g., sea surface chlorophyll-a concentration) environmental variables. The estimated relationships were then used to predict spatially explicit long-term average density (individuals per km 2 ) throughout the study area for each species/group in each of four seasons. Bird sighting data came from multiple scientific survey programs and consisted of at-sea counts of birds collected between 1980 and 2017 using boat-based and fixed-wing aerial transect survey methods. Spatial environmental variables were derived from remote sensing satellite data and an ocean dynamics model.

California, Oregon, Washington↗

USGS2021

Revisiting the declustering of spatial data with preferential sampling

Preferential sampling is a form of data collection that may significantly distort the histogram and the semivariogram of spatially correlated data . Typical situations are a higher sampling density at high-valued areas favorable for mining, and highly contaminated areas in need of environmental remediation. Multiple statistical procedures are devoted to obtaining representative statistics, whose magnitudes should be close to the respective population values. This paper proposes a resampling method that can compensate for preferential sampling of spatially correlated data without using declustering weights. The application of the method herein generates a dataset of median estimates of quantiles of multiple stratified resamples that is free of preferential sampling. The methodology is illustrated with two examples. The first one involves values actually measured in the field and has the advantage of representing a real scenario of spatial fluctuations and preferential sampling. A second dataset is synthetic and has the main benefit of a priori knowledge of the underlying spatial distribution, thus allowing a satisfactory evaluation of the results against the known baseline. Access to computer code is offered for practical application of the method.

Computers & Geosciences↗

USGS2005

Desert potholes: Ephemeral aquatic microsystems

An enigma of the Colorado Plateau high desert is the "pothole", which ranges from shallow ephemeral puddles to deeply carved pools. The existence of prokaryotic to eukaryotic organisms within these pools is largely controlled by the presence of collected rainwater. Multivariate statistical analysis of physical and chemical limnologic data variables measured from potholes indicates spatial and temporal variations, particularly in water depth, manganese, iron, nitrate and sulfate concentrations and salinity. Variation in water depth and salinity are likely related to the amount of time since the last precipitation, whereas the other variables may be related to redox potential. The spatial and temporal variations in water chemistry affect the distribution of organisms, which must adapt to daily and seasonal extremes of fluctuating temperature (0-60 ??C), pH changes of as much as 5 units over 12 days, and desiccation. For example, many species become dormant when potholes dry, in order to endure intense heat, UV radiation, desiccation and freezing, only to flourish again upon rehydration. But the pothole organisms also have a profound impact on the potholes. Through photosynthesis and respiration, pothole organisms affect redox potential, and indirectly alter the water chemistry. Laboratory examination of dried biofilm from the potholes revealed that within 2 weeks of hydration, the surface of the desiccated, black biofilm became green from cyanobacterial growth, which supported significant growth in heterotrophic bacterial populations. This complex biofilm is persumably responsible for dissolving the cement between the sandstone grains, allowing the potholes to enlarge, and for sealing the potholes, enabling them to retain water longer than the surrounding sandstone. Despite the remarkable ability of life in potholes to persist, desert potholes may be extremely sensitive to anthropogenic effects. The unique limnology and ecology of Utah potholes holds great scientific value for understanding water-rock-biological interactions with possible applications to life on other planetary bodies. ?? Springer 2005.

Aquatic Geochemistry↗

USGS2009

Chapter 3 - Phenomenology of tsunamis: Statistical properties from generation to runup

Observations related to tsunami generation, propagation, and runup are reviewed and described in a phenomenological framework. In the three coastal regimes considered (near-field broadside, near-field oblique, and far field), the observed maximum wave amplitude is associated with different parts of the tsunami wavefield. The maximum amplitude in the near-field broadside regime is most often associated with the direct arrival from the source, whereas in the near-field oblique regime, the maximum amplitude is most often associated with the propagation of edge waves. In the far field, the maximum amplitude is most often caused by the interaction of the tsunami coda that develops during basin-wide propagation and the nearshore response, including the excitation of edge waves, shelf modes, and resonance. Statistical distributions that describe tsunami observations are also reviewed, both in terms of spatial distributions, such as coseismic slip on the fault plane and near-field runup, and temporal distributions, such as wave amplitudes in the far field. In each case, fundamental theories of tsunami physics are heuristically used to explain the observations.

Advances in Geophysics↗

USGS2017

Examining the occupancy–density relationship for a low-density carnivore

The challenges associated with monitoring low-density carnivores across large landscapes have limited the ability to implement and evaluate conservation and management strategies for such species. Non-invasive sampling techniques and advanced statistical approaches have alleviated some of these challenges and can even allow for spatially explicit estimates of density, one of the most valuable wildlife monitoring tools. For some species, individual identification comes at no cost when unique attributes (e.g. pelage patterns) can be discerned with remote cameras, while other species require viable genetic material and expensive laboratory processing for individual assignment. Prohibitive costs may still force monitoring efforts to use species distribution or occupancy as a surrogate for density, which may not be appropriate under many conditions. Here, we used a large-scale monitoring study of fisher Pekania pennanti to evaluate the effectiveness of occupancy as an approximation to density, particularly for informing harvest management decisions. We combined remote cameras with baited hair snares during 2013–2015 to sample across a 70 096-km 2 region of western New York, USA. We fit occupancy and Royle–Nichols models to species detection–non-detection data collected by cameras, and spatial capture–recapture (SCR) models to individual encounter data obtained by genotyped hair samples. Variation in the state variables within 15-km 2 grid cells was modelled as a function of landscape attributes known to influence fisher distribution. We found a close relationship between grid cell estimates of fisher state variables from the models using detection–non-detection data and those from the SCR model, likely due to informative spatial covariates across a large landscape extent and a grid cell resolution that worked well with the movement ecology of the species. Fisher occupancy and density were both positively associated with the proportion of coniferous-mixed forest and negatively associated with road density. As a result, spatially explicit management recommendations for fisher were similar across models, though relative variation was dampened for the detection–non-detection data. Synthesis and applications . Our work provides empirical evidence that models using detection–non-detection data can make similar inferences regarding relative spatial variation of the focal population to models using more expensive individual encounters when the selected spatial grain approximates or is marginally smaller than home range size. When occupancy alone is chosen as a cost-effective state variable for monitoring, simulation and sensitivity analyses should be used to understand how inferences from detection–non-detection data will be affected by aspects of study design and species ecology.

Journal of Applied Ecology↗

USGS2002

Movements of Florida apple snails in relation to water levels and drying events

Florida apple snails ( Pomacea paludosa ) apparently have only a limited tolerance to wetland drying events (although little direct evidence exists), but their populations routinely face dry downs under natural and managed water regimes. In this paper, we address speculation that apple snails respond to decreasing water levels and potential drying events by moving toward refugia that remain inundated. We monitored the movements of apple snails in central Florida, USA during drying events at the Blue Cypress Marsh (BC) and at Lake Kissimmee (LK). We monitored the weekly movements of 47 BC snails and 31 LK snails using radio-telemetry. Snails tended to stop moving when water depths were <10 cm; however, there was no apparent effect of water depth on distance traveled in water depths >10 cm. Snails moved along the greatest positive depth gradient (i.e., towards deeper water) when they encountered water depths between 10 and 20 cm. Snails tended to move toward shallower water in water depths ≥50 cm, suggesting that snails were avoiding deep water areas such as canals and sloughs. Of the 11 BC snails originally located in the area that eventually went dry, three (27%) were found in deep water refugia by the end of the study. Only one of the 31 LK snails escaped the drying event by moving to deeper water. Our results indicate that some snails may opportunistically escape drying events through movement. The tendency to move toward deeper water was statistically significant and indicates that this behavioral trait might enhance survival when the spatial extent of a dry down is limited. However, as water level falls below 10 cm, snails stop moving and become stranded. As the spatial extent of a dry down increases, we predict that the number of snails stranded would increase proportionally. Stranded Pomacea paludosa must contend with dry marsh conditions, possibly by aestivation. Little more than anecdotal information has been published on P. paludosa aestivation, but it is a common adaptation among other apple snails (Caenogastropoda: Ampullaridae).

Florida↗

USGS2023

Distribution of large boulders on the deposit of the West Salt Creek rock avalanche, western Colorado

On May 25, 2014, a 54.5-million cubic meter rock avalanche in the West Salt Creek valley, Mesa County, Colorado, traveled 4.6 kilometers, leaving a deposit that covers about 2.2 square kilometers. To check the particle-size distribution of the deposit for information about the high mobility of the avalanche, we estimated boulder distribution density for the entire deposit by counting 1-meter (m) or larger diameter boulders of sedimentary rock derived from the Green River Formation that are visible in high-resolution imagery collected from the area in July 2014. Basalt boulders were excluded from the count because field observations indicated that they generally stayed intact as the avalanche moved downslope, whereas sedimentary boulders showed evidence of fragmentation during downslope movement. Variable clarity, contrast, and resolution of the imagery precluded mapping smaller boulders. Experimentation with 5-, 10-, and 20-m resolution grids indicated that a 20-m resolution grid showed the spatial pattern of boulder density across the deposit at a scale that allowed statistically meaningful variations to be determined. In addition to counting the boulders in each 20×20-m grid cell, six categories of successively increasing boulder distribution density were created to help visualize variations in the distribution of 1 meter or larger boulders across the avalanche deposit. Analysis indicates that boulder distribution density gradually decreases with increasing distance from the avalanche source.

Colorado↗

USGS2017

Downscaling wind and wavefields for 21st century coastal flood hazard projections in a region of complex terrain

While global climate models (GCMs) provide useful projections of near-surface wind vectors into the 21st century, resolution is not sufficient enough for use in regional wave modeling. Statistically downscaled GCM projections from Multivariate Adaptive Constructed Analogues provide daily averaged near-surface winds at an appropriate spatial resolution for wave modeling within the orographically complex region of San Francisco Bay, but greater resolution in time is needed to capture the peak of storm events. Short-duration high wind speeds, on the order of hours, are usually excluded in statistically downscaled climate models and are of key importance in wave and subsequent coastal flood modeling. Here we present a temporal downscaling approach, similar to constructed analogues, for near-surface winds suitable for use in local wave models and evaluate changes in wind and wave conditions for the 21st century. Reconstructed hindcast winds (1975–2004) recreate important extreme wind values within San Francisco Bay. A computationally efficient method for simulating wave heights over long time periods was used to screen for extreme events. Wave hindcasts show resultant maximum wave heights of 2.2 m possible within the Bay. Changes in extreme over-water wind speeds suggest contrasting trends within the different regions of San Francisco Bay, but 21th century projections show little change in the overall magnitude of extreme winds and locally generated waves.

California↗