Search USGS⌕ Search

SEARCH · Search USGS

Results for “Environmental Software”

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 181 records · Page 10Linked to original sources
USGS1995

Geographic information system data sets of hydrogeologic conditions in Pequea and Mill Creek watersheds, Pennsylvania; Part II, Hydrogeologic interpretations

This report describes Geographic Information System data sets of ground-water levels, unsaturated-zone thickness, and regolith thickness in the Pequea and Mill Creek watersheds, a 210-square-mile area in Lancaster and Chester Counties, Pa. The data sets, which represent hydrogeologic interpretations, were developed by the use of ARC/INFO software during 1990-93 by the U.S. Geological Survey, in cooperation with the Pennsylvania Department of Environmental Resources. The U.S. Environmental Protection Agency proposes to use these interpretive data sets, and those from other sources, to aid in the assessment of ground-water vulnerability to pesticides in the Pequea and Mill Creek watersheds.

Open-File Report↗
USGS2005

The Modular Modeling System (MMS): A toolbox for water- and environmental-resources management

The increasing complexity of water- and environmental-resource problems require modeling approaches that incorporate knowledge from a broad range of scientific and software disciplines. To address this need, the U.S. Geological Survey (USGS) has developed the Modular Modeling System (MMS). MMS is an integrated system of computer software for model development, integration, and application. Its modular design allows a high level of flexibility and adaptability to enable modelers to incorporate their own software into a rich array of built-in models and modeling tools. These include individual process models, tightly coupled models, loosely coupled models, and fully- integrated decision support systems. A geographic information system (GIS) interface, the USGS GIS Weasel, has been integrated with MMS to enable spatial delineation and characterization of basin and ecosystem features, and to provide objective parameter-estimation methods for models using available digital data. MMS provides optimization and sensitivity-analysis tools to analyze model parameters and evaluate the extent to which uncertainty in model parameters affects uncertainty in simulation results. MMS has been coupled with the Bureau of Reclamation object-oriented reservoir and river-system modeling framework, RiverWare, to develop models to evaluate and apply optimal resource-allocation and management strategies to complex, operational decisions on multipurpose reservoir systems and watersheds. This decision support system approach has been developed, tested, and implemented in the Gunnison, Yakima, San Joaquin, Rio Grande, and Truckee River basins of the western United States. MMS is currently being coupled with the U.S. Forest Service model SIMulating Patterns and Processes at Landscape Scales (SIMPPLLE) to assess the effects of alternative vegetation-management strategies on a variety of hydrological and ecological responses. Initial development and testing of the MMS-SIMPPLLE integration is being conducted on the Colorado Plateau region of the western United Sates.

Conference Paper↗
USGS2016

Using inferential sensors for quality control of Everglades Depth Estimation Network water-level data

The Everglades Depth Estimation Network (EDEN), with over 240 real-time gaging stations, provides hydrologic data for freshwater and tidal areas of the Everglades. These data are used to generate daily water-level and water-depth maps of the Everglades that are used to assess biotic responses to hydrologic change resulting from the U.S. Army Corps of Engineers Comprehensive Everglades Restoration Plan. The generation of EDEN daily water-level and water-depth maps is dependent on high quality real-time data from water-level stations. Real-time data are automatically checked for outliers by assigning minimum and maximum thresholds for each station. Small errors in the real-time data, such as gradual drift of malfunctioning pressure transducers, are more difficult to immediately identify with visual inspection of time-series plots and may only be identified during on-site inspections of the stations. Correcting these small errors in the data often is time consuming and water-level data may not be finalized for several months. To provide daily water-level and water-depth maps on a near real-time basis, EDEN needed an automated process to identify errors in water-level data and to provide estimates for missing or erroneous water-level data. The Automated Data Assurance and Management (ADAM) software uses inferential sensor technology often used in industrial applications. Rather than installing a redundant sensor to measure a process, such as an additional water-level station, inferential sensors, or virtual sensors, were developed for each station that make accurate estimates of the process measured by the hard sensor (water-level gaging station). The inferential sensors in the ADAM software are empirical models that use inputs from one or more proximal stations. The advantage of ADAM is that it provides a redundant signal to the sensor in the field without the environmental threats associated with field conditions at stations (flood or hurricane, for example). In the event that a station does malfunction, ADAM provides an accurate estimate for the period of missing data. The ADAM software also is used in the quality assurance and quality control of the data. The virtual signals are compared to the real-time data, and if the difference between the two signals exceeds a certain tolerance, corrective action to the data and (or) the gaging station can be taken. The ADAM software is automated so that, each morning, the real-time EDEN data are compared to the inferential sensor signals and digital reports highlighting potential erroneous real-time data are generated for appropriate support personnel. The development and application of inferential sensors is easily transferable to other real-time hydrologic monitoring networks.

Florida↗
USGS2011

Description and testing of the Geo Data Portal: Data integration framework and Web processing services for environmental science collaboration

Interest in sharing interdisciplinary environmental modeling results and related data is increasing among scientists. The U.S. Geological Survey Geo Data Portal project enables data sharing by assembling open-standard Web services into an integrated data retrieval and analysis Web application design methodology that streamlines time-consuming and resource-intensive data management tasks. Data-serving Web services allow Web-based processing services to access Internet-available data sources. The Web processing services developed for the project create commonly needed derivatives of data in numerous formats. Coordinate reference system manipulation and spatial statistics calculation components implemented for the Web processing services were confirmed using ArcGIS 9.3.1, a geographic information science software package. Outcomes of the Geo Data Portal project support the rapid development of user interfaces for accessing and manipulating environmental data.

Open-File Report↗
USGS2018

Geochemical and Pb isotopic characterization of soil, groundwater, human hair, and corn samples from the Domizio Flegreo and Agro Aversano area (Campania region, Italy)

A geochemical survey was carried out to investigate metal contamination in the Domizio Littoral and Agro Aversano area (Southern Italy) by means of soil, groundwater, human hair and corn samples. Pb isotope ratios were also determined to identify the sources of metals. Specifically, the investigation focused on topsoils ( n = 1064), groundwater ( n = 26), 25 human hair ( n = 24) and corn samples ( n = 13). Topsoils have been sampled and analysed in a previous study for 53 elements (including potentially harmful ones), and determined by ICP-MS after dissolving with aqua regia. Groundwater was analysed for 72 elements by ICP-MS and by ICP-ES. Samples of human hair were prepared and analysed for 16 elements by ICP-MS. Dried corn collected at several farms were also analysed for 53 elements by ICP-MS. The isotopic ratios of 206 Pb/ 207 Pb and 208 Pb/ 207 Pb in selected topsoil ( n = 24), groundwater ( n = 9), human hair ( n = 9) and corn ( n = 4) samples were analysed from both eluates and residues to investigate possible anthropogenic contamination and geogenic contributions. All data were processed and mapped by ArcGis software to produce interpolated maps and contamination factor maps of potentially harmful elements, in accordance with Italian Environmental Law (Legislative Decree 152/06). Results show that soil sampling sites are characterized by As, Cd, Co, Cr, Cu, Hg, Pb, Se, and Zn contents exceeding the action limits established for residential land use (RAL) and, in some cases, also the action limits for industrial land use (IAL) as established by Legislative Decree 152/06. A map of contamination factors and a map showing the degrees of contamination indicate that the areas in the municipalities of Acerra, Casoria and Giugliano have been affected by considerable anthropogenic-related pollution. To interpret the isotopic data and roughly estimate proportion of Pb from an anthropogenic source we broadly defined possible natural and anthropogenic Pb end-member fields based on literature data. For example, we summarized data for Vesuvius and Campi Flegrei volcanic rocks, gasoline, and aerosol deposits. Lead isotope data show mixing between geogenic and anthropogenic sources. Topsoil, groundwater, human hair and corn samples show a greater contribution from geogenic sources like the Yellow Tuff (from Campi Flegrei) and volcanic rocks from Mt. Vesuvius. Aerosols, fly ash and gasoline (anthropogenic sources) have also been contributors. In detail, 46% of the topsoil residues, 96% of topsoil leachates, 88% of groundwater, 90% of human hair, and 25% of corn samples indicate that > 50% percent of the lead in this area can be ascribed to anthropogenic activity.

Campania region↗
USGS2003

Fitting population models from field data

The application of population and community ecology to solving real-world problems requires population and community dynamics models that reflect the myriad patterns of interaction among organisms and between the biotic and physical environments. Appropriate models are not hard to construct, but the experimental manipulations needed to evaluate their defining coefficients are often both time consuming and costly, and sometimes environmentally destructive, as well. In this paper we present an empirical approach for finding the coefficients of broadly inclusive models without the need for environmental manipulation, demonstrate the approach with both an animal and a plant example, and suggest possible applications. Software has been developed, and is available from the senior author, with a manual describing both field and analytic procedures.

Ecological Modelling↗
USGS2006

Hierarchical models of animal abundance and occurrence

Much of animal ecology is devoted to studies of abundance and occurrence of species, based on surveys of spatially referenced sample units. These surveys frequently yield sparse counts that are contaminated by imperfect detection, making direct inference about abundance or occurrence based on observational data infeasible. This article describes a flexible hierarchical modeling framework for estimation and inference about animal abundance and occurrence from survey data that are subject to imperfect detection. Within this framework, we specify models of abundance and detectability of animals at the level of the local populations defined by the sample units. Information at the level of the local population is aggregated by specifying models that describe variation in abundance and detection among sites. We describe likelihood-based and Bayesian methods for estimation and inference under the resulting hierarchical model. We provide two examples of the application of hierarchical models to animal survey data, the first based on removal counts of stream fish and the second based on avian quadrat counts. For both examples, we provide a Bayesian analysis of the models using the software WinBUGS.

Journal of Agricultural, Biological, and Environme↗
USGS1994

Applications of shallow high-resolution seismic reflection to various environmental problems

Shallow seismic reflection has been successfully applied to environmental problems in a variety of geologic settings. Increased dynamic range of recording equipment and decreased cost of processing hardware and software have made seismic reflection a cost-effective means of imaging shallow geologic targets. Seismic data possess sufficient resolution in many areas to detect faulting with displacement of less than 3 m and beds as thin as 1 m. We have detected reflections from depths as shallow as 2 m. Subsurface voids associated with abandoned coal mines at depths of less than 20 m can be detected and mapped. Seismic reflection has been successful in mapping disturbed subsurface associated with dissolution mining of salt. A graben detected and traced by seismic reflection was shown to be a preferential pathway for leachate leaking from a chemical storage pond. As shown by these case histories, shallow high-resolution seismic reflection has the potential to significantly enhance the economics and efficiency of preventing and/or solving many environmental problems.

Journal of Applied Geophysics↗
USGS1991

Use of electronic microprocessor-based instrumentation by the U.S. geological survey for hydrologic data collection

The U.S. Geological Survey is acquiring a new generation of field computers and communications software to support hydrologic data-collection at field locations. The new computer hardware and software mark the beginning of the Survey's transition from the use of electromechanical devices and paper tapes to electronic microprocessor-based instrumentation. Software is being developed for these microprocessors to facilitate the collection, conversion, and entry of data into the Survey's National Water Information System. The new automated data-collection process features several microprocessor-controlled sensors connected to a serial digital multidrop line operated by an electronic data recorder. Data are acquired from the sensors in response to instructions programmed into the data recorder by the user through small portable lap-top or hand-held computers. The portable computers, called personal field computers, also are used to extract data from the electronic recorders for transport by courier to the office computers. The Survey's alternative to manual or courier retrieval is the use of microprocessor-based remote telemetry stations. Plans have been developed to enhance the Survey's use of the Geostationary Operational Environmental Satellite telemetry by replacing the present network of direct-readout ground stations with less expensive units. Plans also provide for computer software that will support other forms of telemetry such as telephone or land-based radio.

Conference Paper↗
USGS2009

Application of the Hydroecological Integrity Assessment Process for Missouri Streams

Natural flow regime concepts and theories have established the justification for maintaining or restoring the range of natural hydrologic variability so that physiochemical processes, native biodiversity, and the evolutionary potential of aquatic and riparian assemblages can be sustained. A synthesis of recent research advances in hydroecology, coupled with stream classification using hydroecologically relevant indices, has produced the Hydroecological Integrity Assessment Process (HIP). HIP consists of (1) a regional classification of streams into hydrologic stream types based on flow data from long-term gaging-station records for relatively unmodified streams, (2) an identification of stream-type specific indices that address 11 subcomponents of the flow regime, (3) an ability to establish environmental flow standards, (4) an evaluation of hydrologic alteration, and (5) a capacity to conduct alternative analyses. The process starts with the identification of a hydrologic baseline (reference condition) for selected locations, uses flow data from a stream-gage network, and proceeds to classify streams into hydrologic stream types. Concurrently, the analysis identifies a set of non-redundant and ecologically relevant hydrologic indices for 11 subcomponents of flow for each stream type. Furthermore, regional hydrologic models for synthesizing flow conditions across a region and the development of flow-ecology response relations for each stream type can be added to further enhance the process. The application of HIP to Missouri streams identified five stream types ((1) intermittent, (2) perennial runoff-flashy, (3) perennial runoff-moderate baseflow, (4) perennial groundwater-stable, and (5) perennial groundwater-super stable). Two Missouri-specific computer software programs were developed: (1) a Missouri Hydrologic Assessment Tool (MOHAT) which is used to establish a hydrologic baseline, provide options for setting environmental flow standards, and compare past and proposed hydrologic alterations; and (2) a Missouri Stream Classification Tool (MOSCT) designed for placing previously unclassified streams into one of the five pre-defined stream types.

Open-File Report↗
USGS2011

A working environment for digital planetary data processing and mapping using ISIS and GRASS GIS

Since the beginning of planetary exploration, mapping has been fundamental to summarize observations returned by scientific missions. Sensor-based mapping has been used to highlight specific features from the planetary surfaces by means of processing. Interpretative mapping makes use of instrumental observations to produce thematic maps that summarize observations of actual data into a specific theme. Geologic maps, for example, are thematic interpretative maps that focus on the representation of materials and processes and their relative timing. The advancements in technology of the last 30 years have allowed us to develop specialized systems where the mapping process can be made entirely in the digital domain. The spread of networked computers on a global scale allowed the rapid propagation of software and digital data such that every researcher can now access digital mapping facilities on his desktop. The efforts to maintain planetary missions data accessible to the scientific community have led to the creation of standardized digital archives that facilitate the access to different datasets by software capable of processing these data from the raw level to the map projected one. Geographic Information Systems (GIS) have been developed to optimize the storage, the analysis, and the retrieval of spatially referenced Earth based environmental geodata; since the last decade these computer programs have become popular among the planetary science community, and recent mission data start to be distributed in formats compatible with these systems. Among all the systems developed for the analysis of planetary and spatially referenced data, we have created a working environment combining two software suites that have similar characteristics in their modular design, their development history, their policy of distribution and their support system. The first, the Integrated Software for Imagers and Spectrometers (ISIS) developed by the United States Geological Survey, represents the state of the art for processing planetary remote sensing data, from the raw unprocessed state to the map projected product. The second, the Geographic Resources Analysis Support System (GRASS) is a Geographic Information System developed by an international team of developers, and one of the core projects promoted by the Open Source Geospatial Foundation (OSGeo). We have worked on enabling the combined use of these software systems throughout the set-up of a common user interface, the unification of the cartographic reference system nomenclature and the minimization of data conversion. Both software packages are distributed with free open source licenses, as well as the source code, scripts and configuration files hereafter presented. In this paper we describe our work done to merge these working environments into a common one, where the user benefits from functionalities of both systems without the need to switch or transfer data from one software suite to the other one. Thereafter we provide an example of its usage in the handling of planetary data and the crafting of a digital geologic map. ?? 2010 Elsevier Ltd. All rights reserved.

Conference Paper↗
USGS1996

Uncertainty of groundwater vulnerability assessments for agricultural regions in Hawaii: Review

There are important challenges associated with assessing potential groundwater vulnerability hazards that may result from regional scale applications of agrochemicals. The increasing availability of Geographic Information System (GIS) software to those involved in assisting with landuse decisions has resulted in the widespread production of multicolored risk management maps for many environmentally sensitive issues. Soil-based GIS's have recently been coupled to various solute-leaching models to make near-surface groundwater vulnerability assessments for guidance in pesticide regulation in several states. In general, these assessments rest on soil, climatic, and chemical data that are extremely sparse and contain considerable uncertainty. It is also important to acknowledge the uncertainty associated with the transport/fate processes that are not accounted for by the modeling approach used to make the assessment. In this paper, we review the results from a series of papers that have focused on characterization of uncertainty in pesticide mobility estimates, using the attenuation and retardation indices (AF and RF), for the Pearl Harbor Basin on the Hawaiian island of Oahu. Relative to data error uncertainties, we discuss the impacts of: (i) soil, climatic, and chemical data base uncertainties, (ii) reductions in data base uncertainties, (iii) extrapolation of soil data base information based on soil taxonomy and soil survey, and (iv) importing information from outside the region of interest. Relative to model error uncertainties, we compare pesticide leaching estimates from the simple AF and RF mobility indices with simulations from the EPA's Pesticide Root Zone Model (PRZM) and field observations. Finally, we outline a Regional Integrated Risk Assessment approach for characterizing regional scale groundwater vulnerability for near-surface nonpoint sources.

Hawaii↗
USGS1999

Environmental issues associated with fossil fuel resources; an evaluation of research opportunities for the U.S. Geological Survey's Energy Resources Program

Fossil fuel consumption in the United States has nearly tripled within the last 50 years (fig. 1), and is expected to continue increasing. As our knowledge and awareness of environmental consequences related to fossil fuel extraction and use grow, we as a nation, face the challenge of balancing our energy requirements with a desire for environmentally cleaner fuel. To help meet this challenge, the Energy Resources Program (ERP) of the Geologic Division (GD), U.S. Geological Survey (USGS) sponsored three internal workshops and a World Wide Web (WWW) workshop. The primary goal of these workshops was to identify those environmental issues that are related to fossil fuels, are national in scope, and are within the purview of the USGS as an earth-science government agency. Those issues so identified will be prioritized according to ERP's future research plan and according to the extent they provide an environmental framework for ERP's petroleum and coal assessments. The purpose of this paper is to provide the results of the internal and WWW workshops as proposed topics of research for future ERP work, delineate studies to answer the questions related to each proposed research area, and link the studies to the seven science goals of the Geologic Division. The information provided herein will be used in preparing the USGS Geologic Division's FY2000 prospectus and ERP's next five-year strategic plan. Acknowledgements. The authors wish to acknowledge information on ERP environmental projects provided by Les Magoon, Paul Lillis, Keith Kvenvolden, Tom Lorenson, and Bob Rosenbauer. Peter Schweitzer was instrumental in providing the software for the WWW workshop, Cheryl Adkisson for constructing the workshop web pages, and Laura Friedrich for constructing the web pages summarizing the internal workshops. Stan Mroczkowski, Jim Otton, Donna Read, and Dorothy Tanti provided notes of or logistical assistance for the internal workshops. This report reflects the collective input of numerous USGS managers and scientists their participation in the workshops is greatly appreciated.

Open-File Report↗
USGS2015

Social Values for Ecosystem Services, version 3.0 (SolVES 3.0): documentation and user manual

The geographic information system (GIS) tool, S ocial V alues for E cosystem S ervices (SolVES), was developed to incorporate quantified and spatially explicit measures of social values into ecosystem service assessments. SolVES 3.0 continues to extend the functionality of SolVES, which was designed to assess, map, and quantify the social values of ecosystem services. Social values—the perceived, nonmarket values the public ascribes to ecosystem services, particularly cultural services, such as aesthetics and recreation—can be evaluated for various stakeholder groups. These groups are distinguishable by their attitudes and preferences regarding public uses, such as motorized recreation and logging. As with previous versions, SolVES 3.0 derives a quantitative 10-point, social-values metric—the value index—from a combination of spatial and nonspatial responses to public value and preference surveys. The tool also calculates metrics characterizing the underlying environment, such as average distance to water and dominant landcover. SolVES 3.0 is integrated with Maxent maximum entropy modeling software to generate more complete social-value maps and offer robust statistical models describing the relationship between the value index and explanatory environmental variables. A model’s goodness of fit to a primary study area and its potential performance in transferring social values to similar areas using value-transfer methodology can be evaluated. SolVES 3.0 provides an improved public-domain tool for decision makers and researchers to evaluate the social values of ecosystem services and to facilitate discussions among diverse stakeholders regarding the tradeoffs among ecosystem services in a variety of physical and social contexts ranging from forest and rangeland to coastal and marine.

Open-File Report↗
USGS2020

Social Values for Ecosystem Services, version 4.0 (SolVES 4.0)—Documentation and user manual

The geographic information system tool, Social Values for Ecosystem Services (SolVES), was developed to incorporate quantified and spatially explicit measures of social values into ecosystem service assessments. SolVES 4.0 provides an open-source version of SolVES, which was designed to assess, map, and quantify the social values of ecosystem services. Social values—the perceived, nonmarket values the public ascribes to ecosystem services, particularly cultural services, such as aesthetics and recreation—can be evaluated for various stakeholder groups. These groups are distinguishable by factors such as their attitudes and preferences regarding public uses (for example, motorized recreation and logging). As with previous versions, SolVES 4.0 derives a quantitative 10-point, social-values metric—the value index—from a combination of spatial and nonspatial responses to public value and preference surveys. The tool also calculates metrics characterizing the underlying environment, such as average distance to water and dominant landcover. SolVES 4.0 has been developed with Python using a QGIS user interface and a PostgreSQL database for required data. SolVES is integrated with Maxent maximum entropy modeling software to generate more complete social-value maps and offer robust statistical models describing the relation between the value index and explanatory environmental variables. A model’s goodness of fit to a primary study area and its potential performance in transferring social values to similar areas using value-transfer methods can be evaluated. SolVES 4.0 provides an improved open-source, public-domain tool for decision makers and researchers to evaluate the social values of ecosystem services and to facilitate discussions among diverse stakeholders regarding the tradeoffs among ecosystem services in a variety of biophysical and social contexts including mountain, forest, coastal, riparian, agricultural, and urban environments around the globe.

Techniques and Methods↗
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↗
USGS2014

Virtual Beach 3: user's guide

Virtual Beach version 3 (VB 3 ) is a decision support tool that constructs site-specific statistical models to predict fecal indicator bacteria (FIB) concentrations at recreational beaches. VB 3 is primarily designed for beach managers responsible for making decisions regarding beach closures or the issuance of swimming advisories due to pathogen contamination. However, researchers, scientists, engineers, and students interested in studying relationships between water quality indicators and ambient environmental conditions will find VB 3 useful. VB 3 reads input data from a text file or Excel document, assists the user in preparing the data for analysis, enables automated model selection using a wide array of possible model evaluation criteria, and provides predictions using a chosen model parameterized with new data. With an integrated mapping component to determine the geographic orientation of the beach, the software can automatically decompose wind/current/wave speed and magnitude information into along-shore and onshore/offshore components for use in subsequent analyses. Data can be examined using simple scatter plots to evaluate relationships between the response and independent variables (IVs). VB 3 can produce interaction terms between the primary IVs, and it can also test an array of transformations to maximize the linearity of the relationship The software includes search routines for finding the "best" models from an array of possible choices. Automated censoring of statistical models with highly correlated IVs occurs during the selection process. Models can be constructed either using previously collected data or forecasted environmental information. VB 3 has residual diagnostics for regression models, including automated outlier identification and removal using DFFITs or Cook's Distances.

Report↗
USGS2007

Coastal Prairie Restoration Information System: Version 1 (Louisiana)

The Coastal Prairie Restoration Information System (CPR) is a Microsoft Access database that allows users to query and view data about Louisiana coastal prairie species. Less than 0.1% of Louisiana's coastal prairie vegetation remains in a relatively undisturbed condition. Encompassing as much as 1 million hectares of land, coastal prairie is a hybrid of coastal wetlands and tall grass prairie. Over 550 plant species have been identified in Louisiana's coastal prairies to date. Efforts to conserve and restore this endangered ecosystem are limited by the ability of workers to identify and access knowledge about this diverse group of plants. In this database, a variety of data are provided for each of 650 coastal prairie species in Louisiana. The database was developed at the U.S. Geological Survey National Wetlands Research Center by Larry Allain, with software development by Myra Silva. Additional funding was provided by the biology department of the University of Louisiana at Lafayette (ULL), the ULL Center for Environmental and Ecological Technology, and the National Science Foundation.

Data Series↗