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

USGS2014

Habitat used by juvenile lake sturgeon ( Acipenser fulvescens ) in the North Channel of the St. Clair River (Michigan, USA)

Lake sturgeon ( Acipenser fulvescens ) occupy the St. Clair River, part of a channel connecting lakes Huron and Erie in the Laurentian Great Lakes. In the North Channel of the St. Clair River, juvenile lake sturgeon (3–7 years old and 582–793 mm in length) were studied to determine movement patterns and habitat usage. Fourteen juveniles were implanted with ultrasonic transmitters and tracked June–August of 2004, 2005 and 2006. Telemetry data, Geographic Information System software, side-scan sonar, video images of the river bottom, scuba diving, and benthic substrate samples were used to determine the extent and composition of habitats they occupied. Juvenile lake sturgeon habitat selection was strongly related to water depth. No fish were found in <6 m of water and over 97% of the relocations were found at depths greater than 9 m. Available water depths exceeding 18 m only represented 3.5% of the available habitat, however 34.9% of the relocations were found at depths exceeding 18 m. Juvenile lake sturgeon did not use most areas in proportion to their availability. Sturgeon avoided clay ledges and shallow areas with silt or soft clay, which comprised approximately 39% of the benthic habitat in the North Channel. A total of 300 out of 351 documented locations were on sand and gravel habitat types mixed with clay. Lake sturgeon > 700 mm in length selected sand and gravel areas mixed with zebra mussels and areas dominated by zebra mussels, while fish < 700 mm used these habitat types in proportion to their availability.

Michigan↗

USGS2006

Estimating recharge using relations between precipitation and yield in a mountainous area with large variability in precipitation

Estimates of recharge to bedrock aquifers from infiltration of precipitation can be difficult to obtain, especially in areas with large spatial and temporal variability in precipitation. In the Black Hills area of western South Dakota and eastern Wyoming, streamflow yield is highly influenced by annual precipitation, with yield efficiency (annual yield divided by annual precipitation) increasing with increasing annual precipitation. Spatial variability in annual yield characteristics for Black Hills streams is predictably influenced by precipitation patterns. Relations between precipitation and yield efficiency were used to estimate annual recharge from long-term records of annual precipitation. A series of geographic information system algorithms was used to derive annual estimates for 1000- by 1000-m grid cells. These algorithms were composited to derive estimates of annual recharge rates to the Madison and Minnelusa aquifers in the Black Hills area of western South Dakota and eastern Wyoming during water years 1931-1998 and an estimate of average recharge for water years 1950-1998. This approach provides a systematic method of obtaining consistent and reproducible estimates of recharge from infiltration of precipitation. Resulting estimates of average annual recharge (water years 1950-1998) ranged from 1 cm in the southern Black Hills to 22 cm in the northwestern Black Hills. Recharge rates to these aquifers from infiltration of precipitation on outcrops was estimated to range from 0.9 m 3/s in 1936 to 18.8 m3/s in 1995.

Journal of Hydrology↗

USGS2018

Metamodeling and mapping of nitrate flux in the unsaturated zone and groundwater, Wisconsin, USA

Nitrate contamination of groundwater in agricultural areas poses a major challenge to the sustainability of water resources. Aquifer vulnerability models are useful tools that can help resource managers identify areas of concern, but quantifying nitrogen (N) inputs in such models is challenging, especially at large spatial scales. We sought to improve regional nitrate (NO 3 − ) input functions by characterizing unsaturated zone NO 3 − transport to groundwater through use of surrogate, machine-learning metamodels of a process-based N flux model. The metamodels used boosted regression trees (BRTs) to relate mappable landscape variables to parameters and outputs of a previous “vertical flux method” (VFM) applied at sampled wells in the Fox, Wolf, and Peshtigo (FWP) river basins in northeastern Wisconsin. In this context, the metamodels upscaled the VFM results throughout the region, and the VFM parameters and outputs are the metamodel response variables. The study area encompassed the domain of a detailed numerical model that provided additional predictor variables, including groundwater recharge, to the metamodels. We used a statistical learning framework to test a range of model complexities to identify suitable hyperparameters of the six BRT metamodels corresponding to each response variable of interest: NO 3 − source concentration factor (which determines the local NO 3 − input concentration); unsaturated zone travel time; NO 3 − concentration at the water table in 1980, 2000, and 2020 (three separate metamodels); and NO 3 − “extinction depth”, the eventual steady state depth of the NO 3 − front. The final metamodels were trained to 129 wells within the active numerical flow model area, and considered 58 mappable predictor variables compiled in a geographic information system (GIS). These metamodels had training and cross-validation testing R 2 values of 0.52 – 0.86 and 0.22 – 0.38, respectively, and predictions were compiled as maps of the above response variables. Testing performance was reasonable, considering that we limited the metamodel predictor variables to mappable factors as opposed to using all available VFM input variables. Relationships between metamodel predictor variables and mapped outputs were generally consistent with expectations, e.g. with greater source concentrations and NO 3 − at the groundwater table in areas of intensive crop use and well drained soils. Shorter unsaturated zone travel times in poorly drained areas likely indicated preferential flow through clay soils, and a tendency for fine grained deposits to collocate with areas of shallower water table. Numerical estimates of groundwater recharge were important in the metamodels and may have been a proxy for N input and redox conditions in the northern FWP, which had shallow predicted NO 3 − extinction depth. The metamodel results provide proof-of-concept for regional characterization of unsaturated zone NO 3 − transport processes in a statistical framework based on readily mappable GIS input variables.

Wisconsin↗

USGS2019

An ANCOVA model for porosity and its uncertainty for oil reservoirs based on TORIS dataset

Porosity is one of the most important parameters to assess in-place oil or gas in reservoirs, and to evaluate recovery from enhanced production operations. Since it is relatively well-established to determine porosity using different laboratory and field methods, its value is usually determined at many locations across a reservoir as part of the common practice to capture reservoir heterogeneity and the variability in values. This suite of measurements and the distribution of values are most valuable for probabilistic reservoir assessments, and for spatial modeling if the exact data locations are known. Despite the importance of individual measurements to set the range of values for probabilistic studies, it is not always possible to access these data due to confidentiality. In most cases, commercial or publicly available databases that assessments may rely on usually report only mean values of porosity, like any other reservoir data, or they may not report a value at all. This makes both quantifying the mean value and the uncertainty around it difficult for probabilistic assessments. In this study, the TORIS (Tertiary Oil Recovery Information System) dataset of the National Petroleum Council and the U.S. Department of Energy was used to model porosity and the uncertainty around predicted values. TORIS is an integrated dataset of production data, reservoir properties, and project databases of crude oil reservoirs in the United States. The model presented in the paper was based on ANCOVA (Analysis of Co-Variance) of data from 1038 reservoirs from the TORIS dataset for porosity prediction, validation and testing for quantitative and qualitative parameters that may be readily available in most cases, and to estimate uncertainty around the mean values. This model also explored association of porosity values to different parameters, and to different depositional systems and diagenetic overprint conditions. Furthermore, an ANN (Artificial Neural Network) model was created to compare the predicted values of both models. Results showed that the ANN model was able to represent more of the variability, however it lacked the insights that might be gained from the ANCOVA model.

Journal of Petroleum Science and Engineering↗

USGS2014

The digital global geologic map of Mars: Chronostratigraphic ages, topographic and crater morphologic characteristics, and updated resurfacing history

A new global geologic map of Mars has been completed in a digital, geographic information system (GIS) format using geospatially controlled altimetry and image data sets. The map reconstructs the geologic history of Mars, which includes many new findings collated in the quarter century since the previous, Viking-based global maps were published, as well as other discoveries that were made during the course of the mapping using new data sets. The technical approach enabled consistent and regulated mapping that is appropriate not only for the map's 1:20,000,000 scale but also for its widespread use by diverse audiences. Each geologic unit outcrop includes basic attributes regarding identity, location, area, crater densities, and chronostratigraphic age. In turn, units are grouped by geographic and lithologic types, which provide synoptic global views of material ages and resurfacing character for the Noachian, Hesperian, and Amazonian periods. As a consequence of more precise and better quality topographic and morphologic data and more complete crater-density dating, our statistical comparisons identify significant refinements for how Martian geologic terrains are characterized. Unit groups show trends in mean elevation and slope that relate to geographic occurrence and geologic origin. In comparison with the previous global geologic map series based on Viking data, the new mapping consists of half the number of units due to simpler, more conservative and globally based approaches to discriminating units. In particular, Noachian highland surfaces overall have high percentages of their areas now dated as an epoch older than in the Viking mapping. Minimally eroded (i.e., pristine) impact craters ≥3 km in diameter occur in greater proportion on Hesperian surfaces. This observation contrasts with a deficit of similarly sized craters on heavily cratered and otherwise degraded Noachian terrain as well as on young Amazonian surfaces. We interpret these as reflecting the relatively stronger, lava-rich, yet less-impacted materials making up much of the younger units. Reconstructions of resurfacing of Mars by its eight geologic epochs using the Hartmann and Neukum chronology models indicate high rates of highland resurfacing during the Noachian (peaking at 0.3 km 2 /yr during the Middle Noachian), modest rates of volcanism and transition zone and lowland resurfacing during the Hesperian (∼0.1 km 2 /yr), and low rates of mainly volcanic and polar resurfacing (∼0.01 km 2 /yr) for most of the Amazonian. Apparent resurfacing increased in the Late Amazonian (∼0.03 km 2 /yr), perhaps due to better preservation of this latest record.

Planetary and Space Science↗

USGS2016

Near-real-time cheatgrass percent cover in the Northern Great Basin, USA, 2015

Cheatgrass ( Bromus tectorum L.) dramatically changes shrub steppe ecosystems in the Northern Great Basin, United States. Current-season cheatgrass location and percent cover are difficult to estimate rapidly. We explain the development of a near-real-time cheatgrass percent cover dataset and map in the Northern Great Basin for the current year (2015), display the current year’s map, provide analysis of the map, and provide a website link to download the map (as a PDF) and the associated dataset. The near-real-time cheatgrass percent cover dataset and map were consistent with non-expedited, historical cheatgrass percent cover datasets and maps. Having cheatgrass maps available mid-summer can help land managers, policy makers, and Geographic Information Systems personnel as they work to protect socially relevant areas such as critical wildlife habitats.

Rangelands↗

USGS2012

Potential pollutant sources in a Choptank River (USA) subwatershed and the influence of land use and watershed characteristics

Row-crop and poultry production have been implicated as sources of water pollution along the Choptank River, an estuary and tributary of the Chesapeake Bay. This study examined the effects of land use, subwatershed characteristics, and climatic conditions on the water quality parameters of a subwatershed in the Choptank River watershed. The catchments within the subwatershed were defined using advanced remotely-sensed data and current geographic information system processing techniques. Water and sediment samples were collected in May–October 2009 and April–June 2010 under mostly baseflow conditions and analyzed for select bacteria, nitrate-N, ammonium-N, total arsenic, total phosphorus (TP), orthophosphate (ortho-P), and particle-phase phosphorus (PP); n = 96 for all analytes except for arsenic, n = 136, and for bacteria, n = 89 (aqueous) and 62 (sediment). Detections of Enterococci and Escherichia coli concentrations were ubiquitous in this subwatershed and showed no correlation to location or land use, however larger bacterial counts were observed shortly after precipitation. Nitrate-N concentrations were not correlated with agricultural lands, which may reflect the small change in percent agriculture and/or the similarity of agronomic practices and crops produced between catchments. Concentration data suggested that ammonia emission and possible deposition to surface waters occurred and that these processes may be influenced by local agronomic practices and climatic conditions. The negative correlation of PP and arsenic concentrations with percent forest was explained by the stronger signal of the head waters and overland flow of particulate phase analytes versus dissolved phase inputs from groundwater. Service roadways at some poultry production facilities were found to redirect runoff from the facilities to neighboring catchment areas, which affected water quality parameters. Results suggest that in this subwatershed, catchments with poultry production facilities are possible sources for arsenic and PP as compared to catchment areas where these facilities were not present.

Choptank River↗

USGS2014

A GIS-based vulnerability assessment of brine contamination to aquatic resources from oil and gas development in eastern Sheridan County, Montana

Water (brine) co-produced with oil in the Williston Basin is some of the most saline in the nation. The Prairie Pothole Region (PPR), characterized by glacial sediments and numerous wetlands, covers the northern and eastern portion of the Williston Basin. Sheridan County, Montana, lies within the PPR and has a documented history of brine contamination. Surface water and shallow groundwater in the PPR are saline and sulfate dominated while the deeper brines are much more saline and chloride dominated. A Contamination Index (CI), defined as the ratio of chloride concentration to specific conductance in a water sample, was developed by the Montana Bureau of Mines and Geology to delineate the magnitude of brine contamination in Sheridan County. Values > 0.035 indicate contamination. Recently, the U.S. Geological Survey completed a county level geographic information system (GIS)-based vulnerability assessment of brine contamination to aquatic resources in the PPR of the Williston Basin based on the age and density of oil wells, number of wetlands, and stream length per county. To validate and better define this assessment, a similar approach was applied in eastern Sheridan County at a greater level of detail (the 2.59 km 2 Public Land Survey System section grid) and included surficial geology. Vulnerability assessment scores were calculated for the 780 modeled sections and these scores were divided into ten equal interval bins representing similar probabilities of contamination. Two surface water and two groundwater samples were collected from the section with the greatest acreage of Federal land in each bin. Nineteen of the forty water samples, and at least one water sample from seven of the ten selected sections, had CI values indicating contamination. Additionally, CI values generally increased with increasing vulnerability assessment score, with a stronger correlation for groundwater samples (R 2 = 0.78) than surface water samples (R 2 = 0.53).

Montana↗

USGS1997

Coal quality trends and distribution of potentially hazardous trace elements in eastern Kentucky coals

Coal in the Eastern Kentucky coalfield has been, and continues to be, a valuable energy resource, especially for the electric utility industry. However, Federal mandates in Titles III and IV of the Clean Air Act Amendments of 1990 have placed increasingly stringent demands on the type and grade of coal that can be burnt in an environmentally acceptable manner. Therefore, a greater understanding of the spatial and temporal distribution of thickness and quality parameters, and the geologic factors that control their distribution, is critical if the Eastern Kentucky coalfield is to continue to be a major producer of high-quality coal. Information from the Kentucky Geological Survey's Coal Resource Information System database is used in this paper to document the geographic and stratigraphic distribution of important factors such as bed thickness, calorific value, ash yield and total sulfur content. The distribution of 15 elements that naturally occur in trace amounts in Kentucky coal is also discussed, as these elements may require monitoring with passage of Title III of the Clean Air Act Amendments of 1990.

Kentucky↗

USGS1997

Statistical modeling of agricultural chemical occurrence in midwestern rivers

Agricultural chemicals in surface water may constitute a human health risk or have adverse effects on aquatic life. Recent research on unregulated rivers in the midwestern USA documents that elevated concentrations of herbicides occur for 1-4 months following application in late spring and early summer. In contrast, nitrate concentrations in unregulated rivers are elevated during fall, winter, and spring months. Natural and anthropogenic variables of fiver drainage basins, such as soil permeability, amount of agricultural chemicals applied, or percentage of land planted in corn, affect agricultural chemical concentration and mass transport in rivers. Presented is an analysis of selected data on agricultural chemicals collected for three regional studies conducted by the US Geological Survey. Statistical techniques such as multiple linear and logistic regression were used to identify natural and anthropogenic variables of drainage basins that have strong relations to agricultural chemical concentrations and mass transport measured in rivers. A geographic information system (GIS) was used to manage and analyze spatial data. Statistical models were developed that estimated the concentration, annual transport, and annual mean concentration of selected agricultural chemicals in midwestern rivers. Multiple linear regression models were not very successful (R2 from 0.162 to 0.517) in explaining the variance in observed agricultural chemical concentrations during post-planting runoff. Logistic regression models were somewhat more successful, correctly matching the observed concentration category in 61-80% of observations. Linear and multiple linear regression models were moderately successful (R2 from 0.522 to 0.995) in explaining the variance in observed annual transport and annual mean concentration of agricultural chemicals. Explanatory variables that were commonly significant in the regression models include estimates of agricultural chemical use, crop acreage, soil characteristics, and basin topography.

Journal of Hydrology↗

USGS2002

Long-term cliff retreat and erosion hotspots along the central shores of the Monterey Bay National Marine Sanctuary

Quantification of cliff retreat rates for the southern half of Santa Cruz County, CA, USA, located within the Monterey Bay National Marine Sanctuary, using the softcopy/geographic information system (GIS) methodology results in average cliff retreat rates of 7–15 cm/yr between 1953 and 1994. The coastal dunes at the southern end of Santa Cruz County migrate seaward and landward through time and display net accretion between 1953 and 1994, which is partially due to development. In addition, three critically eroding segments of coastline with high average erosion rates ranging from 20 to 63 cm/yr are identified as erosion ‘hotspots’. These locations include: Opal Cliffs, Depot Hill and Manresa. Although cliff retreat is episodic, spatially variable at the scale of meters, and the factors affecting cliff retreat vary along the Santa Cruz County coastline, there is a compensation between factors affecting retreat such that over the long-term the coastline maintains a relatively smooth configuration. The softcopy/GIS methodology significantly reduces errors inherent in the calculation of retreat rates in high-relief areas (e.g. erosion rates generated in this study are generally correct to within 10 cm) by removing errors due to relief displacement. Although the resulting root mean squared error for erosion rates is relatively small, simple projections of past erosion rates are inadequate to provide predictions of future cliff position. Improved predictions can be made for individual coastal segments by using a mean erosion rate and the standard deviation as guides to future cliff behavior in combination with an understanding of processes acting along the coastal segments in question. This methodology can be applied on any high-relief coast where retreat rates can be measured.

California↗

USGS2001

A geostatistical approach to predicting sulfur content in the Pittsburgh coal bed

The US Geological Survey (USGS) is completing a national assessment of coal resources in the five top coal-producing regions in the US. Point-located data provide measurements on coal thickness and sulfur content. The sample data and their geologic interpretation represent the most regionally complete and up-to-date assessment of what is known about top-producing US coal beds. The sample data are analyzed using a combination of geologic and Geographic Information System (GIS) models to estimate tonnages and qualities of the coal beds. Traditionally, GIS practitioners use contouring to represent geographical patterns of "similar" data values. The tonnage and grade of coal resources are then assessed by using the contour lines as references for interpolation. An assessment taken to this point is only indicative of resource quantity and quality. Data users may benefit from a statistical approach that would allow them to better understand the uncertainty and limitations of the sample data. To develop a quantitative approach, geostatistics were applied to the data on coal sulfur content from samples taken in the Pittsburgh coal bed (located in the eastern US, in the southwestern part of the state of Pennsylvania, and in adjoining areas in the states of Ohio and West Virginia). Geostatistical methods that account for regional and local trends were applied to blocks 2.7 mi (4.3 km) on a side. The data and geostatistics support conclusions concerning the average sulfur content and its degree of reliability at regional- and economic-block scale over the large, contiguous part of the Pittsburgh outcrop, but not to a mine scale. To validate the method, a comparison was made with the sulfur contents in sample data taken from 53 coal mines located in the study area. The comparison showed a high degree of similarity between the sulfur content in the mine samples and the sulfur content represented by the geostatistically derived contours. Published by Elsevier Science B.V.

International Journal of Coal Geology↗

USGS2000

Scaling up from field to region for wind erosion prediction using a field-scale wind erosion model and GIS

Factors that affect wind erosion such as surface vegetative and other cover, soil properties and surface roughness usually change spatially and temporally at the field-scale to produce important field-scale variations in wind erosion. Accurate estimation of wind erosion when scaling up from fields to regions, while maintaining meaningful field-scale process details, remains a challenge. The objectives of this study were to evaluate the feasibility of using a field-scale wind erosion model with a geographic information system (GIS) to scale up to regional levels and to quantify the differences in wind erosion estimates produced by different scales of soil mapping used as a data layer in the model. A GIS was used in combination with the revised wind erosion equation (RWEQ), a field-scale wind erosion model, to estimate wind erosion for two 50 km2 areas. Landsat Thematic Mapper satellite imagery from 1993 with 30 m resolution was used as a base map. The GIS database layers included land use, soils, and other features such as roads. The major land use was agricultural fields. Data on 1993 crop management for selected fields of each crop type were collected from local government agency offices and used to 'train' the computer to classify land areas by crop and type of irrigation (agroecosystem) using commercially available software. The land area of the agricultural land uses was overestimated by 6.5% in one region (Lubbock County, TX, USA) and underestimated by about 21% in an adjacent region (Terry County, TX, USA). The total estimated wind erosion potential for Terry County was about four times that estimated for adjacent Lubbock County. The difference in potential erosion among the counties was attributed to regional differences in surface soil texture. In a comparison of different soil map scales in Terry County, the generalised soil map had over 20% more of the land area and over 15% greater erosion potential in loamy sand soils than did the detailed soil map. As a result, the wind erosion potential determined using the generalised soil map Was about 26% greater than the erosion potential estimated by using the detailed soil map in Terry County. This study demonstrates the feasibility of scaling up from fields to regions to estimate wind erosion potential by coupling a field-scale wind erosion model with GIS and identifies possible sources of error with this approach.

Agriculture, Ecosystems and Environment↗

USGS1997

Estimating millet production for famine early warning: An application of crop simulation modelling using satellite and ground-based data in Burkina Faso

Early warning of impending poor crop harvests in highly variable environments can allow policy makers the time they need to take appropriate action to ameliorate the effects of regional food shortages on vulnerable rural and urban populations. Crop production estimates for the current season can be obtained using crop simulation models and remotely sensed estimates of rainfall in real time, embedded in a geographic information system that allows simple analysis of simulation results. A prototype yield estimation system was developed for the thirty provinces of Burkina Faso. It is based on CERES-Millet, a crop simulation model of the growth and development of millet ( Pennisetum spp.). The prototype was used to estimate millet production in contrasting seasons and to derive production anomaly estimates for the 1986 season. Provincial yields simulated halfway through the growing season were generally within 15% of their final (end-of-season) values. Although more work is required to produce an operational early warning system of reasonable credibility, the methodology has considerable potential for providing timely estimates of regional production of the major food crops in countries of sub-Saharan Africa.

Agricultural and Forest Meteorology↗

USGS2001

Habitat evaluation using GIS a case study applied to the San Joaquin Kit Fox

Concern over the fate of plant and animal species throughout the world has accelerated over recent decades. Habitat loss is considered the main culprit in reducing many species' abundance and range, leading to numerous efforts to plan and manage habitat preservation. Our work uses Geographic Information Systems (GIS) data and modeling to define a spatially explicit analysis of habitat value, using the San Joaquin Kit Fox (Vulpes macrotis mutica) of California (USA) as an example. Over the last 30 years, many field studies and surveys have enhanced our knowledge of the life history, behavior, and needs of the kit fox, which has been proposed as an umbrella or indicator species for grassland habitat in the San Joaquin Valley of California. There has yet been no attempt to convert much of this field knowledge into a model of spatial habitat value useful for planning purposes. This is a significant omission given the importance and visibility of the imperiled kit fox and increasing trends toward spatially explicit modeling and planning. In this paper we apply data from northern California to derive a small-cell GIS raster of habitat value for the kit fox that incorporates both intrinsic habitat quality and neighborhood context, as well the effects of barriers such as roads. Such a product is a useful basis for assessing the presence and amounts of good (and poor) quality habitat and for eventually constructing GIS representations of viable animal territories that could be included in future reserves. ?? 2001 Elsevier Science B.V.

Landscape and Urban Planning↗

USGS1999

Assessing groundwater vulnerability to agrichemical contamination in the Midwest US

Agrichemicals (herbicides and nitrate) are significant sources of diffuse pollution to groundwater. Indirect methods are needed to assess the potential for groundwater contamination by diffuse sources because groundwater monitoring is too costly to adequately define the geographic extent of contamination at a regional or national scale. This paper presents examples of the application of statistical, overlay and index, and process-based modeling methods for groundwater vulnerability assessments to a variety of data from the Midwest U.S. The principles for vulnerability assessment include both intrinsic (pedologic, climatologic, and hydrogeologic factors) and specific (contaminant and other anthropogenic factors) vulnerability of a location. Statistical methods use the frequency of contaminant occurrence, contaminant concentration, or contamination probability as a response variable. Statistical assessments are useful for defining the relations among explanatory and response variables whether they define intrinsic or specific vulnerability. Multivariate statistical analyses are useful for ranking variables critical to estimating water quality responses of interest. Overlay and index methods involve intersecting maps of intrinsic and specific vulnerability properties and indexing the variables by applying appropriate weights. Deterministic models use process-based equations to simulate contaminant transport and are distinguished from the other methods in their potential to predict contaminant transport in both space and time. An example of a one-dimensional leaching model linked to a geographic information system (GIS) to define a regional metamodel for contamination in the Midwest is included.

Water Science and Technology↗

USGS2003

Potential effects on grassland birds of converting marginal cropland to switchgrass biomass production

Habitat loss is a major reason for the decline of grassland birds in North America. Five habitats (pastures, hayfields, rowcrop fields, small-grain fields, Conservation Reserve Program fields) compose most of the habitat used by grassland birds in the Midwest United States. Growing and harvesting switchgrass (Panicum virgatum) as a biomass fuel would create another habitat for grassland birds. Bird abundance information from studies conducted in Iowa and adjacent states and land-use data for the Rathbun Lake Watershed in southern Iowa were used in a Geographic Information System to model the potential effects on bird abundances of converting rowcrop fields to biomass production. Abundances of bird species that are management priorities increased in both biomass scenarios. Common yellowthroat (Geothlypis trichas) abundance in the watershed also increased greatly in both scenarios. Other species (e.g., homed lark [Eremophila alpestris], killdeer [Charadrius vociferous]) were more abundant in the existing land use than in the biomass scenarios, and conversion of fields from rowcrop to biomass production could be detrimental to these species. In general, biomass fields will provide habitat for grassland birds that are management priorities, but future monitoring of birds in such fields is needed as conversion of rowcrop fields to biomass production continues. ?? 2002 Elsevier Science Ltd. All rights reserved.

Biomass and Bioenergy↗

USGS2026

Luminescence dating of hydrothermal explosions in the Yellowstone Plateau volcanic field

Hydrothermal explosions are a significant geological hazard in some active volcanic systems; however, the timing and triggering mechanisms of these explosions are poorly constrained. This study applies luminescence dating techniques to hydrothermal explosion deposits in the Yellowstone Plateau volcanic field to constrain explosion chronologies and evaluate potential triggering mechanisms. We tested four luminescence dating techniques: K-feldspar post-infrared infrared stimulated luminescence (pIRIR225), quartz blue light optically stimulated luminescence (BLOSL), quartz blue thermoluminescence (BTL), and quartz red thermoluminescence (RTL). The pIRIR225 and RTL protocols produce consistent age estimates that agree with independent radiocarbon ages and with the timing of the Pinedale deglaciation. This study focuses on two craters, Mary Bay, along the northern shore of Yellowstone Lake, and Pocket Basin in Lower Geyser Basin. The mean pIRIR225 ages from Mary Bay deposits (11.99 ± 0.68 ka) agree with previous radiocarbon constraints. The mean pIRIR225 results from Pocket Basin deposits (13.44 ± 1.06 ka) suggest a history of explosion following Pinedale deglaciation, followed by recent hydrothermal alteration. Luminescence dating techniques are a promising tool for reconstructing the timing of hydrothermal explosions in the Late Pleistocene and Holocene, helping to constrain recurrence intervals of the largest hydrothermal systems, informing risk, and improving hazard assessments.

Idaho, Montana, Wyoming↗