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At least 631 records · Page 35Linked to original sources
USGS2018

Turing-style tests for UCERF3 synthetic catalogs

Epidemic-Type Aftershock Sequence (ETAS) catalogs generated from the 3rd Uniform California Earthquake Rupture Forecast (UCERF3) model are unique in that they are the first to combine a complex, fault-based long-term forecast with short-term earthquake clustering statistics. We present Turing-style tests to examine whether these synthetic catalogs can successfully imitate observed earthquake behavior in California. We find that UCERF3-ETAS is more spatially diffuse than the observed historic catalog in California and that it is lacking quiet periods that are present in the real catalog. While mean aftershock productivity of the observed catalog is matched closely by UCERF3-ETAS, the real catalog has more inter-sequence productivity variability and small mainshocks have more foreshocks. In sum, we find that UCERF3-ETAS differs from the observed catalog in ways that are foreseeable from its modeling simplifications. The tests we present here can be used on any model which produces suites of synthetic catalogs; as such, in addition to providing avenues for future improvements to the model, they could also be incorporated into testing platforms such as Collaboratory for the Study of Earthquake Predictability (CSEP).

Bulletin of the Seismological Society of America↗
USGS2023

Declining American Goshawk (Accipiter atricapillus) nest site habitat suitability in a timber production landscape: Effects of abiotic, biotic, and forest management factors

Conservation of the American Goshawk ( Accipiter atricapillus ; hereafter goshawk) has been contentious in relation to forest management. Higher quality goshawk nesting habitat is generally considered to consist of contiguous tracts of mature forest, due to goshawks' large home ranges, territoriality, and food requirements. The large trees of mature forest have the greatest economic value to timber companies. We used long-term (1965–2019) data from 281 goshawk nest site locations in the Black Hills National Forest (BHNF), South Dakota, and Wyoming, USA, to evaluate (1) abiotic and biotic factors associated with goshawk nest site habitat suitability (hereafter habitat suitability); (2) changes in habitat suitability over time; and (3) the effect of anthropogenic activities and natural disturbances on habitat suitability. We evaluated forest attributes across five spatial scales relevant to goshawks, used information-theoretic methods to rank and select models, and assessed the predictive capability of the best-approximating models using the concordance statistic. The best-approximating model had excellent predictive capability (concordance = 0.821). Forest attributes at the 12-ha scale were a better predictor of goshawk habitat suitability than covariates evaluated at the point or >12-ha scales, indicating the importance of managing goshawk habitat beyond the nest tree, but within the nest stand. Goshawk habitat suitability was positively related to mean percent canopy cover and median canopy base height, and negatively related to variability in canopy base height within 12 ha of the location. As mean percent canopy cover within 12 ha of a location increased, goshawk habitat suitability increased more slowly in burned compared to unburned areas. Commercial thinning treatments were more likely to occur in closed canopy forest that already had a higher likelihood of goshawk nesting, and we documented a positive relationship between habitat suitability and the interaction of canopy cover with commercial thinning. Goshawk habitat suitability was negatively related to slope and distance to drainage bottoms, and positively related to distance to ridges, which may be related to microclimatic factors. Our results indicate goshawk habitat suitability decreased across the BHNF over the past three decades and much high-quality nesting habitat was lost during this period due to a combination of unsustainable timber harvest and natural disturbances. Minimizing forest management activities that decrease canopy cover and canopy base height, and increase variability in canopy base height in areas of high- and medium-quality goshawk habitat are likely to slow the loss of higher-quality habitat and allow development of future nesting habitat. In addition to informing management, this study demonstrates the value of using existing long-term legacy datasets in conjunction with time series of remotely sensed habitat attributes to evaluate changes in habitat suitability for raptors in heavily managed landscapes with extensive natural disturbances.

South Dakota, Wyoming↗
USGS2002

Measurement of Turbulence with Acoustic Doppler Current Profilers - Sources of Error and Laboratory Results

Acoustic Doppler current profilers (ADCPs) provide a promising method for measuring surface-water turbulence because they can provide data from a large spatial range in a relatively short time with relative ease. Some potential sources of errors in turbulence measurements made with ADCPs include inaccuracy of Doppler-shift measurements, poor temporal and spatial measurement resolution, and inaccuracy of multi-dimensional velocities resolved from one-dimensional velocities measured at separate locations. Results from laboratory measurements of mean velocity and turbulence statistics made with two pulse-coherent ADCPs in 0.87 meters of water are used to illustrate several of inherent sources of error in ADCP turbulence measurements. Results show that processing algorithms and beam configurations have important effects on turbulence measurements. ADCPs can provide reasonable estimates of many turbulence parameters; however, the accuracy of turbulence measurements made with commercially available ADCPs is often poor in comparison to standard measurement techniques.

Conference Paper↗
USGS2025

Temporal and spatial equivalence in demographic responses of emperor penguins (Aptenodytes forsteri) to environmental change

1. Population ecology and biogeography applications often necessitate the transfer of models across spatial and/or temporal dimensions to make predictions outside the bounds of the data used for model fitting. However, ecological data are often spatiotemporally unbalanced such that the spatial or the temporal dimension tends to contain more data than the other. This unbalance frequently leads model transfers to become substitutions, which are predictions to a different dimension than the predictive model was built on. Despite the prevalence of substitutions in ecology, studies validating their performance and their underlying assumptions are scarce. 2. Here, we present a successful case study demonstrating both space-for-time and time-for-space substitutions using emperor penguins (Aptenodytes forsteri) as the focal species. Using abundance-based species distribution models (aSDM) of adult emperor penguins in attendance during spring across 50 colonies, we predict long-term annual fluctuations in fledgling abundance and breeding success at a single colony, Pointe Géologie. Subsequently, we construct statistical models from time series of extended counts on Pointe Géologie to predict average fledgling abundance across 50 colonies. 3. Our analysis reveals that distance to nearest open water (NOW) exhibits the strongest association with both temporal and spatial data. aSDM’s space-for-time substitution performance, as measured by Pearson correlation coefficient was 0.63 and 0.56 when predicting breeding success and fledgling abundance time series, respectively. Linear regression of fledgling abundance on NOW yields similar time-for-space substitution performance when predicting abundance distribution of emperor penguin colonies with a correlation coefficient of 0.58. 4. We posit that such space-time equivalence arises because: 1) emperor penguins colonies conform to their existing fundamental niche; 2) there is not yet any environmental novelty when comparing the spatial vs temporal variation of distance to nearest open water; and 3) models of more specific components of life histories, such as fledgling abundance, rather than occurrence or total population abundance, are more transferable. Identifying these conditions empirically can enhance the qualitative validation of substitutions in cases where direct validation data are lacking.

Journal of Animal Ecology↗
USGS2004

N-mixture models for estimating population size from spatially replicated counts

Spatial replication is a common theme in count surveys of animals. Such surveys often generate sparse count data from which it is difficult to estimate population size while formally accounting for detection probability. In this article, I describe a class of models (n-mixture models) which allow for estimation of population size from such data. The key idea is to view site-specific population sizes, n, as independent random variables distributed according to some mixing distribution (e.g., Poisson). Prior parameters are estimated from the marginal likelihood of the data, having integrated over the prior distribution for n. Carroll and Lombard (1985, Journal of American Statistical Association 80, 423-426) proposed a class of estimators based on mixing over a prior distribution for detection probability. Their estimator can be applied in limited settings, but is sensitive to prior parameter values that are fixed a priori. Spatial replication provides additional information regarding the parameters of the prior distribution on n that is exploited by the n-mixture models and which leads to reasonable estimates of abundance from sparse data. A simulation study demonstrates superior operating characteristics (bias, confidence interval coverage) of the n-mixture estimator compared to the Caroll and Lombard estimator. Both estimators are applied to point count data on six species of birds illustrating the sensitivity to choice of prior on p and substantially different estimates of abundance as a consequence.

Biometrics↗
USGS2006

Chlorophyll a and inorganic suspended solids in backwaters of the upper Mississippi River system: Backwater lake effects and their associations with selected environmental predictors

The Long Term Resource Monitoring Program (LTRMP) uses a stratified random sampling design to obtain water quality statistics within selected study reaches of the Upper Mississippi River System (UMRS). LTRMP sampling strata are based on aquatic area types generally found in large rivers (e.g., main channel, side channel, backwater, and impounded areas). For hydrologically well-mixed strata (i.e., main channel), variance associated with spatial scales smaller than the strata scale is a relatively minor issue for many water quality parameters. However, analysis of LTRMP water quality data has shown that within-strata variability at the strata scale is high in off-channel areas (i.e., backwaters). A portion of that variability may be associated with differences among individual backwater lakes (i.e., small and large backwater regions separated by channels) that cumulatively make up the backwater stratum. The objective of the statistical modeling presented here is to determine if differences among backwater lakes account for a large portion of the variance observed in the backwater stratum for selected parameters. If variance associated with backwater lakes is high, then inclusion of backwater lake effects within statistical models is warranted. Further, lakes themselves may represent natural experimental units where associations of interest to management may be estimated.

Open-File Report↗
USGS2012

Social values for ecosystem services (SolVES): Documentation and user manual, version 2.0

In response to the need for incorporating quantified and spatially explicit measures of social values into ecosystem services assessments, the Rocky Mountain Geographic Science Center (RMGSC), in collaboration with Colorado State University, developed a geographic information system (GIS) application, Social Values for Ecosystem Services (SolVES). With version 2.0 (SolVES 2.0), RMGSC has improved and extended the functionality of SolVES, which was designed to assess, map, and quantify the perceived social values of ecosystem services. Social values such as aesthetics, biodiversity, and recreation can be evaluated for various stakeholder groups as distinguished by their attitudes and preferences regarding public uses, such as motorized recreation and logging. As with the previous version, SolVES 2.0 derives a quantitative, 10-point, social-values metric, the Value Index, from a combination of spatial and nonspatial responses to public attitude and preference surveys and calculates metrics characterizing the underlying environment, such as average distance to water and dominant landcover. Additionally, SolVES 2.0 integrates Maxent maximum entropy modeling software to generate more complete social value maps and to produce robust statistical models describing the relationship between the social values maps and explanatory environmental variables. The performance of these models can be evaluated for a primary study area, as well as for similar areas where primary survey data are not available but where social value mapping could potentially be completed using value-transfer methodology. SolVES 2.0 also introduces the flexibility for users to define their own social values and public uses, model any number and type of environmental variable, and modify the spatial resolution of analysis. With these enhancements, SolVES 2.0 provides an improved public domain tool for decisionmakers and researchers to evaluate the social values of ecosystem services and to facilitate discussions among diverse stakeholders regarding the tradeoffs among different ecosystem services in a variety of physical and social contexts ranging from forest and rangeland to coastal and marine.

Open-File Report↗
USGS2018

Increasing connectivity between metapopulation ecology and landscape ecology

Metapopulation ecology and landscape ecology aim to understand how spatial structure influences ecological processes, yet these disciplines address the problem using fundamentally different modeling approaches. Metapopulation models describe how the spatial distribution of patches affects colonization and extinction, but often do not account for the heterogeneity in the landscape between patches. Models in landscape ecology use detailed descriptions of landscape structure, but often without considering colonization and extinction dynamics. We present a novel spatially explicit modeling framework for narrowing the divide between these disciplines to advance understanding of the effects of landscape structure on metapopulation dynamics. Unlike previous efforts, this framework allows for statistical inference on landscape resistance to colonization using empirical data. We demonstrate the approach using 11 yr of data on a threatened amphibian in a desert ecosystem. Occupancy data for Lithobates chiricahuensis (Chiricahua leopard frog) were collected on the Buenos Aires National Wildlife Refuge (BANWR), Arizona, USA from 2007 to 2017 following a reintroduction in 2003. Results indicated that colonization dynamics were influenced by both patch characteristics and landscape structure. Landscape resistance increased with increasing elevation and distance to the nearest streambed. Colonization rate was also influenced by patch quality, with semi‐permanent and permanent ponds contributing substantially more to the colonization of neighboring ponds relative to intermittent ponds. Ponds that only hold water intermittently also had the highest extinction rate. Our modeling framework can be widely applied to understand metapopulation dynamics in complex landscapes, particularly in systems in which the environment between habitat patches influences the colonization process

Ecology↗
USGS2007

Paleoecology of the Late Pennsylvanian-age Calhoun coal bed and implications for long-term dynamics of wetland ecosystems

Quantitative plant assemblage data from coal balls, miospores, megaspores, and compression floras from the Calhoun coal bed (Missourian) of the Illinois Basin (USA) are used to interpret spatial and temporal changes in plant communities in the paleo-peat swamp. Coal-ball and miospore floras from the Calhoun coal bed are dominated strongly by tree ferns, and pteridosperms and sigillarian lycopsids are subdominant, depending on geographic location within the coal bed. Although the overall composition of Calhoun peat-swamp assemblages is consistent both temporally and spatially, site-to-site differences and short-term shifts in species dominance indicate local topographic and hydrologic control on species composition within the broader context of the swamp. Statistical comparison of the Calhoun miospore assemblages with those from other Late Pennsylvanian coal beds suggests that the same basic species pool was represented in each peat-swamp landscape and that the relative patterns of dominance and diversity were persistent from site to site. Therefore, it appears that the relative patterns of proportional dominance stayed roughly the same from one coal bed to the next during Late Pennsylvanian glacially-driven climatic oscillations.

International Journal of Coal Geology↗
USGS2018

Landscape-scale variation in canopy water content of giant sequoias during drought

Recent drought (2012–2016) caused unprecedented foliage dieback in giant sequoias ( Sequoiadendron giganteum ), a species endemic to the western slope of the southern Sierra Nevada in central California. As part of an effort to understand and map sequoia response to droughts, we studied the patterns of remotely sensed canopy water content (CWC), both within and among sequoia groves in two successive years during the drought period (2015 and 2016). Our aims were: (1) to quantify giant sequoia responses to severe drought stress at a landscape scale using CWC as an indicator of crown foliage status, and (2) to estimate the effect of environmental correlates that mediate CWC change within and among giant sequoia groves. We utilized airborne high fidelity imaging spectroscopy (HiFIS) and light detection and ranging (LiDAR) data from the Carnegie Airborne Observatory to assess giant sequoia foliage status during 2015 and 2016 of the 2012–2016 droughts. A series of statistical models were generated to classify giant sequoias and to map their location in Sequoia and Kings Canyon National Parks (SEKI) and vicinity. We explored the environmental correlates and the spatial patterns of CWC change at the landscape scale. The mapped CWC was highly variable throughout the landscape during the two observation years, and proved to be most closely related to geological substrates, topography, and site-specific water balance. While there was an overall net gain in sequoia CWC between 2015 and 2016, certain locations (lower elevations, steeper slopes, areas more distant from surface water sources, and areas with greater climate water deficit) showed CWC losses. In addition, we found greater CWC loss in shorter sequoias and those growing in areas with lower sequoia stem densities. Our results suggest that CWC change indicates sequoia response to droughts across landscapes. Long-term monitoring of giant sequoia CWC will likely be useful for modeling and predicting their population-level response to future climate change.

California↗
USGS2021

Stable oxygen isotopes in shallow marine ostracodes from the northern Bering and Chukchi Seas

Stable oxygen isotope measurements on calcitic valves of benthic ostracodes (δ18Oost) from the northern Bering and Chukchi Seas were used to examine ecological and hydrographic processes governing ostracode and associated seawater δ18O values. Five cryophilic taxa were analyzed for δ18Oost values: Sarsicytheridea bradii; Paracyprideis pseudopunctillata; Heterocyprideis sorbyana; Heterocyprideis fascis; and the subarctic species Normanicythere leioderma. Controls on the stable oxygen isotope composition of ostracode calcite were investigated by first establishing species' vital effects and then comparing δ18Oost to seawater δ18O values (that ranged from −2.7 to −0.5‰), CTD temperature (−1.7 to 8.7 °C) and salinity (30–34) measured at sampling stations in the Bering and Chukchi Seas during the six summers of 2013–2018. Results from 297 δ18Oost measurements from 53 sites on the Bering and Chukchi Sea continental shelves are consistent with the temporal and spatial variation in δ18O values of continental shelf bottom water, as impacted by seasonality, regional hydrography, and physical processes (i.e., sea-ice melt and extent, vertical mixing, precipitation/evaporation). Regression statistics for δ18Oost values of two species, N. leioderma and P. pseudopunctillata, showed correlations to temperature and salinity that may facilitate prediction of water-mass characteristics when applied to sediment core records. Specifically, a significant linear regression relationship was found between δ18Oost values of N. leioderma and P. pseudopunctillata and temperature (R2 = 0.67 and 0.52, respectively). A principal component analysis confirmed temperature as the main controlling factor in the δ18Oost values of all species except S. bradii, with samples of distinct water masses grouping together. The δ18Oost values of S. bradii exhibited a narrow range of values (~3 to 4.5‰) across a temperature range of 10 °C. Due to strong vital effects and possibly other undetermined factors, the incorporation of δ18Oost in S. bradii was not driven by any obvious predominant environmental factors.

Marine Micropaleontology↗
USGS2021

Adaptive monitoring in action: Reconsidering design-based estimators reveals underestimation of whitebark pine disease prevalence in the Greater Yellowstone Ecosystem

Identifying and understanding status and trends in ecological indicators motivates continual monitoring over decades. Many programs rely on probability surveys and their companion design-based estimators for status assessments (e.g. Horvitz–Thompson). Design-based estimators do not easily extend to trend estimation nor situations with observation errors. Field-based monitoring efforts inevitably have turnover of field crew members which may affect consistency and accuracy of data collection over time. Additionally, design-based estimators ignore the complexities of spatial and temporal heterogeneity in an ecological indicator and how this variability may be linked to environmental or biological dynamics. We propose monitoring programs should re-evaluate their prescribed statistical methods, consider model-based approaches and adapt their sampling designs as needed to improve inferences. The Greater Yellowstone Ecosystem, home to two of the most iconic U.S. National Parks, has experienced significant declines in whitebark pine Pinus albicaulis communities due to forest pathogens, insect outbreaks, wildland fires and drought. Whitebark pine is a keystone species found in mountainous environments throughout the Western U.S. and Canada. We assessed the design-based ratio estimator originally recommended for estimating prevalence of white pine blister rust Cronartium ribicola . We compared the design-based estimator to a model-based approach that accounts for the sampling design, imperfect detection and allows for infection probabilities to vary over space and time. Ignoring observation errors led to lower estimated prevalence of white pine blister rust in the general population. Using model-based approaches, we found that the probability of infection has increased since 2004. However, overall prevalence likely has not changed because of the mountain pine beetle Dendroctonus ponderosae -induced shift towards smaller diameter trees that have a lower probability of infection compared to their larger cohorts. Synthesis and Applications . Using a design-based approach to detect change in ecological indicators falls short because of the inability to account for observation errors or to explore environmental or biological factors explaining temporal dynamics. Inherently understanding the mechanisms leading to changes in an ecological indicator over time informs potential management actions. Our assessment underscores the need for continued evaluation and updating of a monitoring program's sampling design and analytical procedures to maintain relevancy.

Wyoming↗
USGS2010

Spatial variation in keystone effects: Small mammal diversity associated with black-tailed prairie dog colonies

Species with extensive geographic ranges may interact with different species assemblages at distant locations, with the result that the nature of the interactions may vary spatially. Black-tailed prairie dogs Cynomys ludovicianus occur from Canada to Mexico in grasslands of the western Great Plains of North America. Black-tailed prairie dogs alter vegetation and dig extensive burrow systems that alter grassland habitats for plants and other animal species. These alterations of habitat justify the descriptor " ecological engineer," and the resulting changes in species composition have earned them status as a keystone species. We examined the impact of black-tailed prairie dogs on small mammal assemblages by trapping at on- and off-colony locations at eight study areas across the species' geographic range. We posed 2 nested hypotheses: 1) prairie dogs function as a keystone species for other rodent species; and 2) the keystone role varies spatially. Assuming that it does, we asked what are the sources of the variation? Black-tailed prairie dogs consistently functioned as a keystone species in that there were strong statistically significant differences in community composition on versus off prairie dog colonies across the species range in prairie grassland. Small mammal species composition varied along both latitudinal and longitudinal gradients, and species richness varied from 4 to 11. Assemblages closer together were more similar; such correlations approximately doubled when including only on- or off-colony grids. Black-tailed prairie dogs had a significant effect on associated rodent assemblages that varied regionally, dependent upon the composition of the local rodent species pool. Over the range of the black-tailed prairie dog, on-colony rodent richness and evenness were less variable, and species composition was more consistent than off-colony assemblages. ?? 2010 The Authors.

Ecography↗
USGS2003

Spatial variability of groundwater recharge and its effect on shallow groundwater quality in southern New Jersey

Point estimates of groundwater recharge at 48 sediment-coring locations vary substantially (−18.5–1840 cm yr −1 ) in a 930-km 2 area of southern New Jersey. Darcian estimates of steady, long-term recharge made at depth in the unsaturated zone were estimated using pedotransfer functions of soil texture and interpolated (mapped) with nonparametric methods to assess aquifer vulnerability in the area. The probability of exceeding the median recharge (29.1 cm yr −1 ) is low in the southwestern and northeastern portions of the study area and high in the eastern and southeastern portions. Estimated recharge is inversely related to measured percentage clay and positively related to the percentage of well-drained soils near wells. Spatial patterns of recharge estimates, exceedance probabilities, and clay content indicate that sediment texture controls recharge in the study area. Relations with land elevation and a topographic wetness index were statistically insignificant. Nitrate concentration and atrazine (6-chloro- N 2 -ethyl- N 4 -isopropyl-1,3,5-triazine-2,4-diamine) percentage detection in samples of shallow groundwater (typically <10 m) are higher for low recharge sites (≤29.1 cm yr −1 ) than for high recharge sites (>29.1 cm yr −1 ) in agricultural and urban areas. Differences between high and low recharge sites in these areas are highly significant for NO 3 concentration, but not for atrazine concentration.

New Jersey↗
USGS2005

Simulation of ground-water flow in coastal Georgia and adjacent parts of South Carolina and Florida-predevelopment, 1980, and 2000

A digital model was developed to simulate steady-state ground-water flow in a 42,155-square-mile area of coastal Georgia and adjacent parts of South Carolina and Florida. The model was developed to (1) understand and refine the conceptual model of regional ground-water flow, (2) serve as a framework for the development of digital subregional ground-water flow and solute-transport models, and (3) serve as a tool for future evaluations of hypothetical pumping scenarios used to facilitate water management in the coastal area. Single-density ground-water flow was simulated using the U.S. Geological Survey finite-difference code MODFLOW-2000 for mean-annual conditions during predevelopment (pre?1900) and the years 1980 and 2000. The model comprises seven layers: the surficial aquifer system, the Brunswick aquifer system, the Upper Floridan aquifer, the Lower Floridan aquifer, and the intervening confining units. A combination of boundary conditions was applied, including a general-head boundary condition on the top active cells of the model and a time-variable fixed-head boundary condition along part of the southern lateral boundary. Simulated heads for 1980 and 2000 conditions indicate a good match to observed values, based on a plus-or-minus 10-foot (ft) calibration target and calibration statistics. The root-mean square of residual water levels for the Upper Floridan aquifer was 13.0 ft for the 1980 calibration and 9.94 ft for the 2000 calibration. Some spatial patterns of residuals were indicated for the 1980 and 2000 simulations, and are likely a result of model-grid cell size and insufficiently detailed hydraulic-property and pumpage data in some areas. Simulated potentiometric surfaces for predevelopment, 1980, and 2000 conditions all show major flow system features that are indicated by estimated peotentiometric maps. During 1980?2000, simulated water levels at the centers of pumping at Savannah and Brunswick rose more than 20 ft and 8 ft, respectively, in response to decreased pumping. Simulated drawdown exceeded 10 ft in the Upper Floridan aquifer across much of the western half of the model area, with drawdown exceeding 20 ft along parts of the western, northern, and southern boundaries where irrigation pumping increased during this period. From predevelopment to 2000 conditions, the simulated water budget showed an increase in inflow from, and decrease in outflow to, the general-head boundaries, and a reversal from net seaward flow to net landward flow across the coastline. Simulated changes in recharge and discharge distribution from predevelopment to 2000 conditions showed an increase in extent and magnitude of net recharge cells in the northern part of the model area, and a decrease in discharge or change to recharge in cells containing major streams and beneath major pumping centers. The model is relatively sensitive to pumping and the controlling head at the fixed-head boundary and less sensitive to the distribution of aquifer properties in general. Model limitations include: (1) its spatial scale and discretization, (2) the extent to which data are available to physically define the flow system, (3) the type of boundary conditions and controlling parameters used, (4) uncertainty in the distribution of pumping, and (5) uncertainty in field-scale hydraulic properties. The model could be improved with more accurate estimates of ground-water pumpage and better characterization of recharge and discharge.

Florida, Georgia, South Carolina↗
USGS2010

Land Disturbance Associated with Oil and Gas Development and Effects of Development-Related Land Disturbance on Dissolved-Solids Loads in Streams in the Upper Colorado River Basin, 1991, 2007, and 2025

Oil and gas resource development in the Upper Colorado River Basin (UCRB) has increased substantially since the year 2000. The UCRB encompasses several significant oil and gas producing areas that have the potential for continued oil and gas resource development. Land disturbance associated with oil and gas resource development is caused by activities related to constructing drill pads to contain drilling and well maintenance equipment and roads to access the drill pad. Land disturbed by oil and gas development has the potential to cause increased erosion, stream degradation, habitat fragmentation and alteration, and increase public use of areas that may be environmentally sensitive. Land disturbance resulting from oil and gas resource development has not been monitored and mapped on a regional scale in the UCRB. However, information on the location and age of oil and gas wells in the UCRB is available. These data combined with geographic data analysis and modeling techniques were used to estimate the total area of disturbed land associated with oil and gas resource development in 1991 and in 2007 in the UCRB. Additional information about anticipated oil and gas development in the UCRB was used to project land disturbance to the year 2025. Results of the analysis indicate that approximately 117,500 acres (183 mi2) of total land disturbance was associated with drill pads and related roads in the UCRB in 1991. The estimated area of disturbed land associated with oil and gas development increased 53 percent to 179,400 acres (280 mi2) in 2007. Projecting oil and gas development through 2025 results in a potential near doubling of the land surface disturbance to approximately 319,300 acres (500 mi2). Estimated land disturbance for 1991 and 2007 were input to a contaminant transport model developed for the UCRB to assess the statistical significance of energy-related land disturbance to contributing dissolved solids to basin streams. The statistical assessment was an observational study based on an existing model and available water-quality monitoring data for the basin. No new data were collected for the analysis. The source coefficient calibrated for the disturbed lands associated with oil and gas development in 2007 was zero, which indicated that estimated land disturbance from oil and gas development is not statistically significant in explaining dissolved solids in UCRB streams. The lack of significance in the contaminant transport modeling framework may be due to the amount of available monitoring data, the spatial distribution of monitoring sites with respect to land disturbance, or the overall quantity of land disturbance associated with oil and gas development basin wide. Finally, dissolved-solids loads derived from natural landscapes may be similar to loads derived from lands disturbed by oil and gas resource development. The model recalibration done for this study confirms calibration results from Kenney and others (2009): the most significant contributor to dissolved solids in the UCRB is irrigated agricultural land, which covers an area substantially larger than the estimated area disturbed by oil and gas development and is subjected to artificially applied water.

Scientific Investigations Report↗
USGS2013

Investigation of the structure and lithology of bedrock concealed by basin fill, using ground-based magnetic-field-profile data acquired in the San Rafael Basin, southeastern Arizona

Data on the Earth’s total-intensity magnetic field acquired near ground level and at measurement intervals as small as 1 m include information on the spatial distribution of nearsurface magnetic dipoles that in many cases are unique to a specific lithology. Such spatial information is expressed in the texture (physical appearance or characteristics) of the data at scales of hundreds of meters to kilometers. These magnetic textures are characterized by several descriptive statistics, their power spectrum, and their multifractal spectrum. On the basis of a graphical comparison and textural characterization, ground-based magnetic-field profile data can be used to estimate bedrock lithology concealed by as much as 100 m of basin fill in some cases, information that is especially important in assessing and exploring for concealed mineral deposits. I demonstrate that multifractal spectra of ground-based magnetic-field-profile data can be used to differentiate exposed lithologies and that the shape and position of the multifractal spectrum of the ground-based magnetic-field-profile of concealed lithologies can be matched to the upward-continued multifractal spectrum of an exposed lithology to help distinguish the concealed lithology. In addition, ground-based magnetic-field-profile data also detect minute differences in the magnetic susceptibility of rocks over small horizontal and vertical distances and so can be used for precise modeling of bedrock geometry and structure, even when that bedrock is concealed by 100 m or more of nonmagnetic basin fill. Such data contain valuable geologic information on the bedrock concealed by basin fill that may not be so visible in aeromagnetic data, including areas of hydrothermal alteration, faults, and other bedrock structures. Interpretation of these data in the San Rafael Basin, southeastern Arizona, has yielded results for estimating concealed lithologies, concealed structural geology, and a concealed potential mineral-resource target.

Arizona↗
USGS2013

Influence of estuarine processes on spatiotemporal variation in bioavailable selenium

Dynamic processes (physical, chemical and biological) challenge our ability to quantify and manage the ecological risk of chemical contaminants in estuarine environments. Selenium (Se) bioavailability (defined by bioaccumulation), stable isotopes and molar carbon-tonitrogen ratios in the benthic clam Potamocorbula amurensis, an important food source for predators, were determined monthly for 17 yr in northern San Francisco Bay. Se concentrations in the clams ranged from a low of 2 to a high of 22 &mu;g g -1 over space and time. Little of that variability was stochastic, however. Statistical analyses and preliminary hydrodynamic modeling showed that a constant mid-estuarine input of Se, which was dispersed up- and down-estuary by tidal currents, explained the general spatial patterns in accumulated Se among stations. Regression of Se bioavailability against river inflows suggested that processes driven by inflows were the primary driver of seasonal variability. River inflow also appeared to explain interannual variability but within the range of Se enrichment established at each station by source inputs. Evaluation of risks from Se contamination in estuaries requires the consideration of spatial and temporal variability on multiple scales and of the processes that drive that variability.

Marine Ecology Progress Series↗