Search USGSSearch

SEARCH · Search USGS

Results for “Environmental Data Science”

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

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

At least 433 records · Page 24Linked to original sources

Quantifying uncertainty and tradeoffs in resilience assessments

Several frameworks have been developed to assess the resilience of social-ecological systems, but most require substantial data inputs, time, and technical expertise. Stakeholders and practitioners often lack the resources for such intensive efforts. Furthermore, most end with problem framing and fail to explicitly address trade-offs and uncertainty. To remedy this gap, we developed a rapid survey assessment that compares the relative resilience of social-ecological systems with respect to a number of resilience properties. This approach generates large amounts of information relative to stakeholder inputs. We targeted four stakeholder categories: government (policy, regulation, management), end users (farmers, ranchers, landowners, industry), agency/public science (research, university, extension), and NGOs (environmental, citizen, social justice) in four North American watersheds, to assess social-ecological resilience through surveys. Conceptually, social-ecological systems are comprised of components ranging from strictly human to strictly ecological, but that relate directly or indirectly to one another. They have soft boundaries and several important dimensions or axes that together describe the nature of social-ecological interactions, e.g., variability, diversity, modularity, slow variables, feedbacks, capital, innovation, redundancy, and ecosystem services. There is no absolute measure of resilience, so our design takes advantage of cross-watershed comparisons and therefore focuses on relative resilience. Our approach quantifies and compares the relative resilience across watershed systems and potential trade-offs among different aspects of the social-ecological system, e.g., between social, economic, and ecological contributions. This approach permits explicit assessment of several types of uncertainty (e.g., self-assigned uncertainty for stakeholders; uncertainty across respondents, watersheds, and subsystems), and subjectivity in perceptions of resilience among key actors and decision makers and provides an efficient way to develop the mental models that inform our stakeholders and stakeholder categories.

Ecology and Society

Revisiting the cape cod bacteria injection experiment using a stochastic modeling approach

Bromide and resting-cell bacteria tracer tests conducted in a sandy aquifer at the U.S. Geological Survey Cape Cod site in 1987 were reinterpreted using a three-dimensional stochastic approach. Bacteria transport was coupled to colloid filtration theory through functional dependence of local-scale colloid transport parameters upon hydraulic conductivity and seepage velocity in a stochastic advection - dispersion/attachment - detachment model. Geostatistical information on the hydraulic conductivity (K) field that was unavailable at the time of the original test was utilized as input. Using geostatistical parameters, a groundwater flow and particle-tracking model of conservative solute transport was calibrated to the bromide-tracer breakthrough data. An optimization routine was employed over 100 realizations to adjust the mean and variance ofthe natural-logarithm of hydraulic conductivity (InK) field to achieve best fit of a simulated, average bromide breakthrough curve. A stochastic particle-tracking model for the bacteria was run without adjustments to the local-scale colloid transport parameters. Good predictions of mean bacteria breakthrough were achieved using several approaches for modeling components of the system. Simulations incorporating the recent Tufenkji and Elimelech (Environ. Sci. Technol. 2004, 38, 529-536) correlation equation for estimating single collector efficiency were compared to those using the older Rajagopalan and Tien (AIChE J. 1976, 22, 523-533) model. Both appeared to work equally well at predicting mean bacteria breakthrough using a constant mean bacteria diameter for this set of field conditions. Simulations using a distribution of bacterial cell diameters available from original field notes yielded a slight improvement in the model and data agreement compared to simulations using an average bacterial diameter. The stochastic approach based on estimates of local-scale parameters for the bacteria-transport process reasonably captured the mean bacteria transport behavior and calculated an envelope of uncertainty that bracketed the observations in most simulation cases.

Massachusetts

Correlation of soil and sediment organic matter polarity to aqueous sorption of nonionic compounds

Polarities of the soiL/sediment organic matter (SOM) in 19 soil and 9 freshwater sediment sam pies were determined from solid-state 13C-CP/MAS NMR spectra and compared with published partition coefficients (K(oc)) of carbon tetrachloride (CT) from aqueous solution. Nondestructive analysis of whole samples by solid-state NMR permits a direct assessment of the polarity of SOM that is not possible by elemental analysis. The percent of organic carbon associated with polar functional groups was estimated from the combined fraction of carbohydrate and carboxylamide-ester carbons. A plot of the measured partition coefficients (K(oc)) of carbon tetrachloride (CT) vs. percent polar organic carbon (POC) shows distinctly different populations of soils and sediments as well as a roughly inverse trend among the soil/sediment populations. Plots of K(oc) values for CT against other structural group carbon fractions did not yield distinct populations. The results indicate that the polarity of SOM is a significant factor in accounting for differences in K(oc) between the organic matter in soils and sediments. The alternate direct correlation of the sum of aliphatic and aromatic structural carbons with K(oc) illustrates the influence of nonpolar hydrocarbon on solute partition interaction. Additional elemental analysis data of selected samples further substantiate the effect of the organic matter polarity on the partition efficiency of nonpolar solutes. The separation between soil and sediment samples based on percent POC reflects definite differences of the properties of soil and sediment organic matters that are attributable to diagenesis.Polarities of the soil/sediment organic matter (SOM) in 19 soil and 9 freshwater sediment samples were determined from solid-state 13C-CP/MAS NMR spectra and compared with published partition coefficients (Koc) of carbon tetrachloride (CT) from aqueous solution. Nondestructive analysis of whole samples by solid-state NMR permits a direct assessment of the polarity of SOM that is not possible by elemental analysis. The percent of organic carbon associated with polar functional groups was estimated from the combined fraction of carbohydrate and carboxyl-amide-ester carbons. A plot of the measured partition coefficients (Koc) of carbon tetrachloride (CT) vs. percent polar organic carbon (POC) shows distinctly different populations of soils and sediments as well as a roughly inverse trend among the soil/sediment populations. Plots of Koc values for CT against other structural group carbon fractions did not yield distinct populations. The results indicate that the polarity of SOM is a significant factor in accounting for differences in Koc between the organic matter in soils and sediments. The alternate direct correlation of the sum of aliphatic and aromatic structural carbons with Koc illustrates the influence of nonpolar hydrocarbon on solute partition interaction. Additional elemental analysis data of selected samples further substantiate the effect of the organic matter polarity on the partition efficiency of nonpolar solutes. The separation between soil and sediment samples based on percent POC reflects definite differences of the properties of soil and sediment organic matters that are attributable to diagenesis.

Environmental Science & Technology

Improving gas-derived parameterization of groundwater using free phase gas measurements

Dissolved atmogenic gasses in groundwater provide significant information about recharge conditions, flowpath, and age. Free phase gas in aquifers is largely ignored in these analyses and there is a lack of quantitative analysis for gas flux mechanisms. Many related fields encountering multiphase flow acknowledge that the presence of bubbles allows for the rapid exsolution of dissolved gasses and volatile compounds through diffusive and polar forces. By measuring the mass flow of the exsolved gas at a spring, coupled with compositional analysis in the free and dissolved phases, we show that not incorporating the effects of the free gas phase of bubbling springs introduces error in the estimation of total gas quantities, particularly light noble gasses. This can significantly affect the corresponding estimation of noble gas temperature (NGT) and apparent age. We examine the transport of free and dissolved gas from the recharge zone, using water level variation data, to the discharge location where the gases are measured. This technique of using the free gas phase for assessing aquifer dynamics will improve groundwater conceptual models, particularly in karstic aquifers where rapid fluctuations in the water table facilitate the development of excess air, generating multiphase spring discharge.

Environmental Science: Water Research & Technology

EAARL-B submerged topography: Barnegat Bay, New Jersey, post-Hurricane Sandy, 2012-2013

These remotely sensed, geographically referenced elevation measurements of lidar-derived submerged topography datasets were produced by the U.S. Geological Survey (USGS), St. Petersburg Coastal and Marine Science Center, St. Petersburg, Florida. This project provides highly detailed and accurate datasets for part of Barnegat Bay, New Jersey, acquired post-Hurricane Sandy on November 1, 5, 16, 20, and 30, 2012; December 5, 6, and 21, 2012; and January 10, 2013. The datasets are made available for use as a management tool to research scientists and natural-resource managers. An innovative airborne lidar system, known as the second-generation Experimental Advanced Airborne Research Lidar (EAARL-B), was used during data acquisition. The EAARL-B system is a raster-scanning, waveform-resolving, green-wavelength (532-nm) lidar designed to map nearshore bathymetry, topography, and vegetation structure simultaneously. The EAARL-B sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive lidar, down-looking red-green-blue (RGB) and infrared (IR) digital cameras, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit, which provide for sub-meter georeferencing of each laser sample. The nominal EAARL-B platform is a twin-engine Cessna 310 aircraft, but the instrument may be deployed on a range of light aircraft. A single pilot, a lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. Elevation measurements were collected over the survey area using the EAARL-B system. The resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed originally in a NASA-USGS collaboration. The exploration and processing of lidar data in an interactive or batch mode is supported using ALPS. Modules for presurvey flight-line definition, flight-path plotting, lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. The Airborne Lidar Processing System (ALPS) is used routinely to create maps that represent submerged or sub-aerial topography. Specialized filtering algorithms have been implemented to determine the "bare earth" under vegetation from a point cloud of last return elevations. For more information about similar projects, please visit the Lidar for Science and Resource Management Web site .

New Jersey

EAARL Coastal Topography-Mississippi and Alabama Barrier Islands, Post-Hurricane Gustav, 2008

These remotely sensed, geographically referenced elevation measurements of lidar-derived bare-earth (BE) and first-surface (FS) topography datasets were produced collaboratively by the U.S. Geological Survey (USGS), St. Petersburg Coastal and Marine Science Center, St. Petersburg, FL; the National Park Service (NPS), Gulf Coast Network, Lafayette, LA; and the National Aeronautics and Space Administration (NASA), Wallops Flight Facility, VA. This project provides highly detailed and accurate datasets of a portion of the Mississippi and Alabama barrier islands, acquired post-Hurricane Gustav (September 2008 hurricane) on September 8, 2008. The datasets are made available for use as a management tool to research scientists and natural-resource managers. An innovative airborne lidar instrument originally developed at the NASA Wallops Flight Facility, and known as the Experimental Advanced Airborne Research Lidar (EAARL), was used during data acquisition. The EAARL system is a raster-scanning, waveform-resolving, green-wavelength (532-nanometer) lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive lidar, a down-looking red-green-blue (RGB) digital camera, a high-resolution multispectral color infrared (CIR) camera, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit, which provide for sub-meter georeferencing of each laser sample. The nominal EAARL platform is a twin-engine Cessna 310 aircraft, but the instrument may be deployed on a range of light aircraft. A single pilot, a lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. Elevation measurements were collected over the survey area using the EAARL system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of lidar data in an interactive or batch mode. Modules for presurvey flight-line definition, flight-path plotting, lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is used routinely to create maps that represent submerged or sub-aerial topography. Specialized filtering algorithms have been implemented to determine the 'bare earth' under vegetation from a point cloud of last return elevations. For more information about similar projects, please visit the Decision Support for Coastal Science and Management website.

Data Series

EAARL coastal topography-Cape Hatteras National Seashore, North Carolina, post-Nor'Ida, 2009: first surface

These remotely sensed, geographically referenced elevation measurements of lidar-derived first-surface (FS) topography datasets were produced collaboratively by the U.S. Geological Survey (USGS), St. Petersburg Coastal and Marine Science Center, St. Petersburg, FL, and the National Park Service (NPS), Northeast Coastal and Barrier Network, Kingston, RI. This project provides highly detailed and accurate datasets of a portion of the National Park Service Southeast Coast Network's Cape Hatteras National Seashore in North Carolina, acquired post-Nor'Ida (November 2009 nor'easter) on November 27 and 29 and December 1, 2009. The datasets are made available for use as a management tool to research scientists and natural-resource managers. An innovative airborne lidar instrument originally developed at the NASA Wallops Flight Facility, and known as the Experimental Advanced Airborne Research Lidar (EAARL), was used during data acquisition. The EAARL system is a raster-scanning, waveform-resolving, green-wavelength (532-nanometer) lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive lidar, a down-looking red-green-blue (RGB) digital camera, a high-resolution multispectral color-infrared (CIR) camera, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit, which provide for sub-meter georeferencing of each laser sample. The nominal EAARL platform is a twin-engine aircraft, but the instrument was deployed on a Pilatus PC-6. A single pilot, a lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. Elevation measurements were collected over the survey area using the EAARL system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of lidar data in an interactive or batch mode. Modules for presurvey flight-line definition, flight-path plotting, lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is used routinely to create maps that represent submerged or sub-aerial topography. Specialized filtering algorithms have been implemented to determine the 'bare earth' under vegetation from a point cloud of last return elevations. For more information about similar projects, please visit the Decision Support for Coastal Science and Management website.

Data Series

A regional classification scheme for estimating reference water quality in streams using land-use-adjusted spatial regression-tree analysis

Various approaches are used to subdivide large areas into regions containing streams that have similar reference or background water quality and that respond similarly to different factors. For many applications, such as establishing reference conditions, it is preferable to use physical characteristics that are not affected by human activities to delineate these regions. However, most approaches, such as ecoregion classifications, rely on land use to delineate regions or have difficulties compensating for the effects of land use. Land use not only directly affects water quality, but it is often correlated with the factors used to define the regions. In this article, we describe modifications to SPARTA (spatial regression-tree analysis), a relatively new approach applied to water-quality and environmental characteristic data to delineate zones with similar factors affecting water quality. In this modified approach, land-use-adjusted (residualized) water quality and environmental characteristics are computed for each site. Regression-tree analysis is applied to the residualized data to determine the most statistically important environmental characteristics describing the distribution of a specific water-quality constituent. Geographic information for small basins throughout the study area is then used to subdivide the area into relatively homogeneous environmental water-quality zones. For each zone, commonly used approaches are subsequently used to define its reference water quality and how its water quality responds to changes in land use. SPARTA is used to delineate zones of similar reference concentrations of total phosphorus and suspended sediment throughout the upper Midwestern part of the United States. ?? 2006 Springer Science+Business Media, Inc.

Environmental Management

From eDNA to decisions using a multi-method approach to restoration planning in streams

Reintroduction efforts are increasingly used to mitigate biodiversity losses, but are frequently challenged by inadequate planning and uncertainty. High quality information about population status and threats can be used to prioritize reintroduction and restoration efforts and can transform ad hoc approaches into opportunities for improving conservation outcomes at a landscape scale. We conducted comprehensive environmental DNA (eDNA) and visual encounter surveys to determine the distribution of native and non-native aquatic species in two high-priority watersheds to address key uncertainties—such as the distribution of threats and the status of existing populations—inherent in restoration planning. We then used these occurrence data to develop a menu of potential conservation actions and a decision framework to benefit an endangered vertebrate (foothill yellow-legged frog, Rana boylii ) in dynamic stream systems. Our framework combines the strengths of multiple methods, allowing managers and conservation scientists to incorporate conservation science and site-specific knowledge into the planning process to increase the likelihood of achieving conservation goals.

Scientific Reports

Developing fish trophic interaction indicators of climate change for the Great Lakes

This project addressed regional climate change effects on aquatic food webs in the Great Lakes. We sought insights by examining Lake Erie as a representative system with a high level of anthropogenic impacts, strong nutrient gradients, seasonal hypoxia, and spatial overlap of cold- and cool-water fish guilds. In Lake Erie and in large embayments throughout the Great Lakes basin, this situation is a concern for fishery managers, as climate change may exacerbate hypoxia and reduce habitat volume for some species. We examined fish community composition, fine-scale distribution, prey availability, diets, and biochemical tracers for dominant fishes from study areas with medium-high nutrient levels (mesotrophic, Fairport study area), and low nutrient levels (oligotrophic, Erie study area). This multi-year database (2011-2013) provides the ability to contrast years with wide variation in rainfall, winter ice-cover, and thermal stratification. In addition, multiple indicators of dietary and distributional responses to environmental variability will allow resource managers to select the most informative approach for addressing specific climate change questions. Our results support the incorporation of some relatively simple and cost-efficient approaches into existing agency monitoring programs to track the near-term condition status of fish and fish community composition by functional groupings. Other metrics appear better suited for understanding longer-term changes, and may take more resources to implement on an ongoing basis. Although we hypothesized that dietary overlap and similarity in selected species would be sharply different during thermal stratification and hypoxic episodes, we found little evidence of this. Instead, to our surprise, this study found that fish tended to aggregate at the edges of hypoxia, highlighting potential spatial changes in catch efficiency of the fishery. This work has had several positive impacts on a wide range of resource management and stakeholder activities, most notably in Lake Erie. The results were instrumental in the development of an interim decision rule for dealing with data collected during hypoxic events to improve stock assessment of Yellow Perch. In addition, novel findings from this study regarding spatial and temporal variability in hypoxia have aided US-Environmental Protection Agency in the development of a modified sampling protocol to more accurately quantify the central basin hypoxic zone, and this directly addressed a goal of the Great Lakes Water Quality Agreement of 2012 to reduce the extent and severity of hypoxia. Finally, the study areas developed in this project formed the basis for food web sampling in the 2014 bi-national Coordinated Science and Monitoring Initiative work in Lake Erie.

Report

The USGS Land Cover Institute

The U.S. Geological Survey (USGS) Land Cover Institute (LCI) is located at the Center for Earth Resources Observation and Science (EROS) in Sioux Falls, South Dakota. It provides a focal point for advancing USGS land cover studies and applications. Satellite images and other remotely sensed data play an important role in this research. Land Cover scientists investigate new ways to use satellite images and other data to map land cover. They assess national and global land cover characteristics and monitor how - and how rapidly - land cover changes. They also study the economic impacts of land cover as well as its effects on water quality, the spread of invasive species, habitats and biodiversity, climate variability, and other environmental factors.

Fact Sheet

Combining state-and-transition simulations and species distribution models to anticipate the effects of climate change

State-and-transition simulation models (STSMs) are known for their ability to explore the combined effects of multiple disturbances, ecological dynamics, and management actions on vegetation. However, integrating the additional impacts of climate change into STSMs remains a challenge. We address this challenge by combining an STSM with species distribution modeling (SDM). SDMs estimate the probability of occurrence of a given species based on observed presence and absence locations as well as environmental and climatic covariates. Thus, in order to account for changes in habitat suitability due to climate change, we used SDM to generate continuous surfaces of species occurrence probabilities. These data were imported into ST-Sim, an STSM platform, where they dictated the probability of each cell transitioning between alternate potential vegetation types at each time step. The STSM was parameterized to capture additional processes of vegetation growth and disturbance that are relevant to a keystone species in the Greater Yellowstone Ecosystem—whitebark pine ( Pinus albicaulis ). We compared historical model runs against historical observations of whitebark pine and a key disturbance agent (mountain pine beetle, Dendroctonus ponderosae ), and then projected the simulation into the future. Using this combination of correlative and stochastic simulation models, we were able to reproduce historical observations and identify key data gaps. Results indicated that SDMs and STSMs are complementary tools, and combining them is an effective way to account for the anticipated impacts of climate change, biotic interactions, and disturbances, while also allowing for the exploration of management options.

AIMS Environmental Science

The United States Polar Rock Repository: A geological resource for the Earth science community

The United States Polar Rock Repository (USPRR) is a U. S. national facility designed for the permanent curatorial preservation of rock samples, along with associated materials such as field notes, annotated air photos and maps, raw analytic data, paleomagnetic cores, ground rock and mineral residues, thin sections, and microfossil mounts, microslides and residues from Polar areas. This facility was established by the Office of Polar Programs at the U. S. National Science Foundation (NSF) to minimize redundant sample collecting, and also because the extreme cold and hazardous field conditions make fieldwork costly and difficult. The repository provides, along with an on-line database of sample information, an essential resource for proposal preparation, pilot studies and other sample based research that should make fieldwork more efficient and effective. This latter aspect should reduce the environmental impact of conducting research in sensitive Polar Regions. The USPRR also provides samples for educational outreach. Rock samples may be borrowed for research or educational purposes as well as for museum exhibits.

Open-File Report

Upper Mississippi River system weighted wind fetch analysis (1989, 2000, 2010/2011)

Wind fetch is defined as the unobstructed distance that wind can travel over water in a constant direction. Fetches are limited by landforms surrounding the body of water. Fetch is an important characteristic of open water because longer fetches can result in larger wind-generated waves. The larger waves, in turn, can increase shoreline erosion and sediment resuspension (Rohweder and others 2012). Increases in sediment resuspension lead to increases in water turbidity, which in turn decreases light penetration and, therefore, create conditions less conducive to aquatic plant growth (Giblin and others 2010). A wind fetch model was developed by David Finlayson, U. S. Geological Survey, Pacific Science Center, while he was a Ph.D. student at the University of Washington (Finlayson 2005). This method calculates effective fetch using the recommended procedure of the Shore Protection Manual (USACE 1984). Scientists at the United States Geological Survey, Upper Midwest Environmental Sciences Center (UMESC) and the United States Army Corps of Engineers (USACE) further refined this model (Rohweder and others 2012) and structured it to operate using the most recent version of the ArcMap Geographic Information System platform (Esri, 2019). At the time the analysis was performed, the version of ArcMap used was 10.7.1. The model refined in 2012 was used for the analyses described in this report. Using this model, UMESC performed an analysis to model weighted wind fetch for the Upper Mississippi River System (UMRS) corresponding to three separate time periods of land cover spatial data acquisition (1989, 2000, and 2010/2011). The purpose of the analysis was to examine how fetch varies over time and space within the UMRS for potential management applications. For more detailed information on the wind fetch model, examine the USGS Open-File Report by Rohweder and others (2012).

Illinois, Iowa, Minnesota, Missouri, Wisconsin

Climate science and famine early warning

Food security assessment in sub-Saharan Africa requires simultaneous consideration of multiple socio-economic and environmental variables. Early identification of populations at risk enables timely and appropriate action. Since large and widely dispersed populations depend on rainfed agriculture and pastoralism, climate monitoring and forecasting are important inputs to food security analysis. Satellite rainfall estimates (RFE) fill in gaps in station observations, and serve as input to drought index maps and crop water balance models. Gridded rainfall time-series give historical context, and provide a basis for quantitative interpretation of seasonal precipitation forecasts. RFE are also used to characterize flood hazards, in both simple indices and stream flow models. In the future, many African countries are likely to see negative impacts on subsistence agriculture due to the effects of global warming. Increased climate variability is forecast, with more frequent extreme events. Ethiopia requires special attention. Already facing a food security emergency, troubling persistent dryness has been observed in some areas, associated with a positive trend in Indian Ocean sea surface temperatures. Increased African capacity for rainfall observation, forecasting, data management and modelling applications is urgently needed. Managing climate change and increased climate variability require these fundamental technical capacities if creative coping strategies are to be devised.

Philosophical Transactions of the Royal Society B:

U.S. Geological Survey Mineral Resources Program - Science Supporting Mineral Resource Stewardship

The United States is the world's largest user of mineral resources. We use them to build our homes and cities, fertilize our food crops, and create wealth that allows us to buy goods and services. Individuals rarely use nonfuel mineral resources in their natural state - we buy light bulbs, not the silica, soda ash, lime, coal, salt, tungsten, copper, nickel, molybdenum, iron, manganese, aluminum, and zinc used to convert electricity into light. The USGS Mineral Resources Program (MRP) is the sole Federal source of scientific information and unbiased research on nonfuel mineral potential, production, and consumption, as well as on the environmental effects of minerals. The MRP also provides baseline geochemical, geophysical, and mineral-deposit data used to understand environmental issues related to extraction and use of mineral resources. Understanding how minerals, water, plants, and organisms interact contributes to our understanding of the environment, which is essential for maintaining human and ecosystem health. To support creation of economic and national security policies in a global context, MRP collects and analyzes data on essential mineral commodities from around the world.

Fact Sheet

Citizen science contributes to our knowledge of invasive plant species distributions

Citizen science is commonly cited as an effective approach to expand the scale of invasive species data collection and monitoring. However, researchers often hesitate to use these data due to concerns over data quality. In light of recent research on the quality of data collected by volunteers, we aimed to demonstrate the extent to which citizen science data can increase sampling coverage, fill gaps in species distributions, and improve habitat suitability models compared to professionally generated data sets used in isolation. We combined data sets from professionals and volunteers for five invasive plant species ( Alliaria petiolata , Berberis thunbergii , Cirsium palustre , Pastinaca sativa , Polygonum cuspidatum ) in portions of Wisconsin. Volunteers sampled counties not sampled by professionals for three of the five species. Volunteers also added presence locations within counties not included in professional data sets, especially in southern portions of the state where professional monitoring activities had been minimal. Volunteers made a significant contribution to the known distribution, environmental gradients sampled, and the habitat suitability of P. cuspidatum . Models generated with professional data sets for the other four species performed reasonably well according to AUC values (>0.76). The addition of volunteer data did not greatly change model performance (AUC > 0.79) but did change the suitability surface generated by the models, making them more realistic. Our findings underscore the need to merge data from multiple sources to improve knowledge of current species distributions, and to predict their movement under present and future environmental conditions. The efficiency and success of these approaches require that monitoring efforts involve multiple stakeholders in continuous collaboration via established monitoring networks.

Wisconsin

Summary of the Ground-Water-Level Hydrologic Conditions in New Jersey 2006

Ground water is one of the Nation's most important natural resources. It provides about 40 percent of our Nation's public water supply. Currently, nearly one-half of New Jersey's drinking-water is supplied by over 300,000 wells that serve more than 4.3 million people (John P. Nawyn, U.S. Geological Survey, written commun., 2007). New Jersey's population is projected to grow by more than a million people by 2030 (U.S. Census Bureau, accessed March 2, 2006, at http://www.census.gov). As demand for water increases, managing the development and use of the ground-water resource so that the supply can be maintained for an indefinite time without causing unacceptable environmental, economic, or social consequences is of paramount importance. This report describes the U.S. Geological Survey (USGS) New Jersey Water Science Center Observation Well Networks. Record low ground-water levels during water year 2006 (October 1, 2005 to September 30, 2006) are listed, and water levels in six selected water-table observation wells and three selected confined wells are shown in hydrographs. The report describes the trends in water levels in various confined aquifers in southern New Jersey and in water-table and fracture rock aquifers throughout the State. Web site addresses to access the data also are included. The USGS has operated a network of observation wells in New Jersey since 1923 for the purpose of monitoring ground-water-level changes throughout the State. Long-term systematic measurement of water levels in observation wells provides the data needed to evaluate changes in the ground-water resource over time. Records of ground-water levels are used to evaluate the effects of climate changes and water-supply development, to develop ground-water models, and to forecast trends.

Fact Sheet