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USGS2021

Miniature temperature data loggers increase precision and reduce bias when estimating the daily survival rate for bird nests

Demographic studies of many bird species are challenging because their nests are cryptic, resulting in few nests being found. To maximize statistical power, methods are needed that minimize disturbance while yielding as much information per nest as possible. One way to meet these objectives is to use miniature thermal data loggers to precisely date nest fates. Our objectives, therefore, were to (1) examine the possible effect of thermal data loggers on nest success through hatching by grass- and shrub-nesting songbirds that differed in their parasite egg-accepting and -rejecting behavior, (2) examine the effect of using daily temperature data versus less frequent nest-visit data on statistical power, bias, and precision when estimating the daily survival rate (DSR) for nests, and (3) compare these two approaches using a simulation study and field data. We monitored the survival of nests located in agricultural landscapes and used a binomial logistic regression with main effects for data-loggers and parasite-accepting or -rejecting status and their interaction. We also compared maximum likelihood–derived DSR for differences in estimated rates, precision, and sample sizes with both data collected in the field and simulated with varying sample sizes and visit frequencies. We found no evidence that thermal data loggers had any effect on hatching rates either for all species or for parasite egg-accepting and -rejecting species, separately. Both our simulation and analysis of real nest data indicated that use of data loggers increased the statistical power from each nest studied by increasing effective sample sizes and precision of DSR estimates compared to in-person visits. We also found a negative bias in DSR estimates with longer visit intervals, which use of data-loggers removed. Both the results of simulated- and field-data analyses suggest that future studies of nest survival can be improved by automated nest monitoring by removing a source of bias and providing more time to find additional nests.

Iowa↗

USGS2026

Harmonization of aggregated freshwater biotic data to support continental and global assessment

Biodiversity loss and conservation are increasingly coming into focus in global policy fora, requiring information and assessments at wider spatial and temporal scales than previously considered. However, the monitoring framework required to support such data collection and assessment is lacking in many countries and is not harmonized across countries, hampering these efforts. Aggregation of existing freshwater data offers a solution to the problem of assessing status and trends of ecosystems and biodiversity at large spatial scales in the absence of nationally coordinated monitoring efforts. Analysis of aggregated data from different sources, collected using different protocols and with varying levels of metadata and supporting data, can be challenging and requires decisions regarding data comparability. In this paper, we identify the challenges inherent in harmonizing aggregated freshwater data for analysis, including general concerns related to research goals, spatial and temporal scale, sample selection, sampling effort, and site integrity. We also discuss the challenges related to measured parameters, sampled habitats, sample collection and processing methods, and data integrity for phytoplankton, benthic algae, macrophytes, zooplankton, benthic macroinvertebrates, fish, and supporting variables such as water and sediment chemistry. We provide a workflow to evaluate each of these challenges and make decisions about how best to work with the data. Finally, we review a case study from a large-scale analysis of freshwater data from the circumpolar Arctic region that exemplifies the encountered challenges and the chosen solutions. Through the description of the case study, we provide practical solutions to support aggregation and analysis of existing freshwater data. As global conversations about biodiversity status and trends continue, the demand for large-scale analyses of data from different sources will only grow. In the absence of globally harmonized monitoring, we are faced with the need to ensure comparability of data, making expert judgements where needed to support sound conclusions.

PLOS Water↗

USGS2026

Detecting earthquakes in noisy real-time GNSS data with deep learning for improved PGD magnitude estimation

To disseminate accurate and useful warnings, earthquake early warning (EEW) systems must quickly determine the size and location of an earthquake to estimate expected shaking. Traditional seismic‐based algorithms tend to underestimate the true magnitudes of large earthquakes, a phenomenon known as magnitude saturation. This limitation motivated the recent inclusion of Global Navigation Satellite Systems (GNSS) data into the U.S. Geological Survey’s ShakeAlert EEW system with the Geodetic First Approximation of Size and Time (GFAST) algorithm because GNSS data do not saturate with large ground motions. However, the noise levels of GNSS data are very high compared with traditional seismic data, which obscures P ‐wave arrivals and can result in less accurate magnitude estimations if displacement amplitudes are low, such as for lower magnitude earthquakes or large source–station distances. In this study, we develop a deep‐learning model that detects earthquakes in GNSS data and use the Ridgecrest, California, earthquake sequence as a case study to demonstrate how the model could act as a filter to reduce the amount of low‐quality data that enters an algorithm like GFAST. To preserve our limited real earthquake data for model inference, we generated a training dataset composed of >700,000 synthetic displacement waveforms. We combined the synthetic waveforms with real‐time GNSS noise to produce realistically noisy training waveforms and then tested our model on additional synthetic data and performed inference using the real data that were held back. We discuss the performance of our trained model on both the unseen synthetic data and real inference data. Our model can be used to selectively filter only high‐quality data where an earthquake signal is observed for input into an algorithm like GFAST (outperforming a simple signal‐to‐noise ratio–based filter) to reduce the error in GFAST’s real‐time earthquake magnitude estimations.

California↗

USGS1988

Land cover mapping of the upper Kuskokwim Resource Managment Area using LANDSAT and a digital data base approach

Digital land cover and terrain data for the Upper Kuskokwim Resource Hanagement Area (UKRMA) were produced by the U.S. Geological Survey, Earth Resources Observation Systems Field Office, Anchorage, Alaska for the Bureau of Land Management. These and other environmental data, were incorporated into a digital data base to assist in the management and planning of the UKRMA. The digital data base includes land cover classifications, elevation, slope, and aspect data centering on the UKRMA boundaries. The data are stored on computer compatible tapes at a 50-m pixel size. Additional digital data in the data base include: (a) summer and winter Landsat multispectral scanner (MSS) data registered to a 50-m Universal Transverse Mercator grid; (b) elevation, slope, aspect, and solar illumination data; (c) soils and surficial geology; and (e) study area boundary. The classification of Landsat MSS data resulted in seven major classes and 24 subclasses. Major classes include: forest, shrubland, dwarf scrub, herbaceous, barren, water, and other. The final data base will be used by resource personnel for management and planning within the UKRMA.

Alaska↗

USGS1998

Availability of Ground-Water Data for California, Water Year 1997

The Water Resources Division of the U.S. Geological Survey, in cooperation with Federal, State, and local water agencies, obtains a large amount of data pertaining to the ground-water resources of California each water year. These data constitute a valuable data base for developing an improved understanding of the water resources of the State. Beginning with the 1985 water year and continuing through 1993, these data were published in a report series entitled 'Water Resources Data for California, Volume 5. Ground-Water Data.' Prior to the introduction of this series, historical ground-water information was published in U.S. Geological Survey Water-Supply Papers. In 1994, the Volume 5 Ground-Water Data report was discontinued, but data continue to be available in our data bases. This Fact Sheet serves as an index to ground-water data for 1997. The 2-page report contains a map of California showing the number of wells (by county) with available water-level and water-quality data for the current water year (fig. 2) and instructions for obtaining this and other ground-water information contained in the data bases of the Water Resources Division, California District.

Fact Sheet↗

USGS1997

Mineral-resource data bases

Data bases are essential for modern scientific research. The new and exciting work being done in the Mineral Resource Program in the U.S. Geological Survey (USGS) usually begins with the question, "Where are the known deposits?" A mineral-resource data base containing this type of information and more can be useful not just to USGS scientists, but to anyone who needs such data. Users of the data bases from outside the USGS include mining and exploration companies, environmental groups, academia, other Federal Agencies, and the general public. At present, the USGS has two large mineral-resource data bases, MRDS (Mineral Resource Data System) and MAS (Minerals Availability System). MRDS was built and is mamtained by the USGS, and MAS was built and maintained by the Bureau of Mines. In 1996, after the Bureau was abolished, MAS was transferred to the USGS. The two data bases were compiled for different purposes and contain very different mformation. For instance, MAS contains information on costs, details of mining methods, and feasibility studies. MRDS has mineralogical and geologic data that are not contained in MAS. Because they are both mineral-resource data bases, however, they contain some information in common, such as location, name(s) of sites, and commodities present. Both data bases are international in scope, and both are quite large. MRDS contains over 110,000 records, while MAS has over 220,000. One reason that MAS has more records is that it contains information on smelters, mill sites, and fossil fuel sites, as well as mineral- resource sites. The USGS is working to combine the information in both data bases. This is a large undertaking that will require some years to complete. In the interim, information from both data bases will still be available

Fact Sheet↗

USGS2000

Availability of Ground-Water Data for California, Water Year 1999

The Water Resources Division of the U.S. Geological Survey, in cooperation with Federal, State, and local water agencies, obtains a large amount of data pertaining to the ground-water resources of California each water year. These data constitute a valuable data base for developing an improved understanding of the water resources of the State. Beginning with the 1985 water year and continuing through 1993, these data were published in a report series entitled ?Water Resources Data for California, Volume 5. Ground-Water Data.? Prior to the introduction of this series, historical ground-water information was published in U.S. Geological Survey Water-Supply Papers. In 1994, the Volume 5 Ground-Water Data report was discontinued, but data continue to be available in our data bases. This Fact Sheet serves as an index to ground-water data for 1999. The 2-page report contains a map of California showing the number of wells (by county) with available water-level and water-quality data for the current water year (fig. 2) and instructions for obtaining this and other ground-water information contained in the data bases of the Water Resources Division, California District.

Fact Sheet↗

USGS1999

Availability of Ground-Water Data For California, Water Year 1998

The Water Resources Division of the U.S. Geological Survey, in cooperation with Federal, State, and local water agencies, obtains a large amount of data pertaining to the ground-water resources of California each water year. These data constitute a valuable data base for developing an improved understanding of the water resources of the State. Beginning with the 1985 water year and continuing through 1993, these data were published in a report series entitled ?Water Resources Data for California, Volume 5. Ground-Water Data.? Prior to the introduction of this series, historical ground-water information was published in U.S. Geological Survey Water-Supply Papers. In 1994, the Volume 5 Ground-Water Data report was discontinued, but data continue to be available in our data bases. This Fact Sheet serves as an index to ground-water data for 1998. The 2-page report contains a map of California showing the number of wells (by county) with available water-level and water-quality data for the current water year (fig. 2) and instructions for obtaining this and other ground-water information contained in the data bases of the Water Resources Division, California District.

Fact Sheet↗

USGS2007

Global Data Toolset (GDT)

According to the United Nations Environment Programme World Conservation Monitoring Centre (UNEP-WCMC) approximately 60 percent of the data contained in the World Database on Protected Areas (WDPA) has missing or incomplete boundary information. As a result, global analyses based on the WDPA can be inaccurate, and professionals responsible for natural resource planning and priority setting must rely on incomplete geospatial data sets. To begin to address this problem the World Data Center for Biodiversity and Ecology, in cooperation with the U. S. Geological Survey (USGS) Rocky Mountain Geographic Science Center (RMGSC), the National Biological Information Infrastructure (NBII), the Global Earth Observation System, and the Inter-American Biodiversity Information Network (IABIN) sponsored a Protected Area (PA) workshop in Asuncion, Paraguay, in November 2007. The primary goal of this workshop was to train representatives from eight South American countries on the use of the Global Data Toolset (GDT) for reviewing and editing PA data. Use of the GDT will allow PA experts to compare their national data to other data sets, including non-governmental organization (NGO) and WCMC data, in order to highlight inaccuracies or gaps in the data, and then to apply any needed edits, especially in the delineation of the PA boundaries. In addition, familiarizing the participants with the web-enabled GDT will allow them to maintain and improve their data after the workshop. Once data edits have been completed the GDT will also allow the country authorities to perform any required review and validation processing. Once validated, the data can be used to update the global WDPA and IABIN databases, which will enhance analysis on global and regional levels.

Fact Sheet↗

USGS2002

Ground-water-quality data for Albany and surrounding areas, Southwest Georgia, 1951-99

This report presents ground-water-quality data from the surficial, Upper Floridan, Claiborne, Clayton, and Upper Cretaceous aquifers in the Albany and surrounding areas of southwest Georgia. Water-quality data from about 186 wells in Baker, Calhoun, Dougherty, Lee, Mitchell, Terrell, and Worth Counties are presented for the period from 1951 through 1999. The data include field water-quality parameters collected during 1951-99, volatile and semi-volatile organic compounds collected during 1981-97, inorganic compounds collected during 1951-99, trace metals collected during 1964-99, radiochemicals collected during 1993-95, herbicides and insecticides collected during 1980-97, and recovery data for laboratory surrogate compounds (used for quality control and quality assurance for organic samples) collected during 1993-97. Ground-water quality data are presented in tables by data type and arranged by well number. Illustrations in this report contain information about study area location, well location, stratigraphy, and formation water-bearing properties. Ground-water-quality data are presented in text files and in a data base that includes geographic and tabular data. Data presented in this report provide a base with which to better define and interpret the quality of ground water in Albany, Ga., and surrounding areas. Although some of these data may have been published in previous reports associated with water-resources investigations, water-quality data are compiled as a useful resource.

Georgia↗

USGS2003

User's Manual for the National Water-Quality Assessment Program Invertebrate Data Analysis System (IDAS) Software: Version 3

The Invertebrate Data Analysis System (IDAS) software provides an accurate, consistent, and efficient mechanism for analyzing invertebrate data collected as part of the National Water-Quality Assessment Program and stored in the Biological Transactional Database (Bio-TDB). The IDAS software is a stand-alone program for personal computers that run Microsoft (MS) Windows?. It allows users to read data downloaded from Bio-TDB and stored either as MS Excel? or MS Access? files. The program consists of five modules. The Edit Data module allows the user to subset, combine, delete, and summarize community data. The Data Preparation module allows the user to select the type(s) of sample(s) to process, calculate densities, delete taxa based on laboratory processing notes, combine lifestages or keep them separate, select a lowest taxonomic level for analysis, delete rare taxa, and resolve taxonomic ambiguities. The Calculate Community Metrics module allows the user to calculate over 130 community metrics, including metrics based on organism tolerances and functional feeding groups. The Calculate Diversities and Similarities module allows the user to calculate nine diversity and eight similarity indices. The Data export module allows the user to export data to other software packages and produce tables of community data that can be imported into spreadsheet and word-processing programs. Though the IDAS program was developed to process invertebrate data downloaded from USGS databases, it will work with other data sets that are converted to the USGS (Bio-TDB) format. Consequently, the data manipulation, analysis, and export procedures provided by the IDAS program can be used by anyone involved in using benthic macroinvertebrates in applied or basic research.

Open-File Report↗

USGS2004

The National Assessment of Shoreline Change: A GIS Compilation of Vector Shorelines and Associated Shoreline Change Data for the U.S. Gulf of Mexico

Introduction The Coastal and Marine Geology Program of the U.S. Geological Survey has generated a comprehensive database of digital vector shorelines and shoreline change rates for the U.S. Gulf of Mexico. These data, which are presented herein, were compiled as part of the U.S. Geological Survey's National Assessment of Shoreline Change Project. Beach erosion is a chronic problem along most open-ocean shores of the United States. As coastal populations continue to grow and community infrastructures are threatened by erosion, there is increased demand for accurate information including rates and trends of shoreline migration. There is also a critical need for shoreline change data that is consistent from one coastal region to another. One purpose of this work is to develop standard repeatable methods for mapping and analyzing shoreline movement so that periodic updates regarding coastal erosion and land loss can be made nationally that are systematic and internally consistent. This data compilation for open-ocean, sandy shorelines of the Gulf of Mexico is the first in a series that will eventually include the Atlantic Coast, Pacific Coast, and parts of Hawaii and Alaska. Short- and long-term shoreline change evaluations are based on merging three historical shorelines with a modern shoreline derived from lidar (light detection and ranging) topographic surveys. Historical shorelines generally represent the following time periods: 1800s, 1920s-1930s, and 1970s. The most recent shoreline is derived from data collected over the period of 1998-2002. Long-term rates of change are calculated by linear regression using all four shorelines. Short-term rates of change are simple end-point rate calculations using the two most recent shorelines. Please refer to our full report on shoreline change in the Gulf of Mexico, National Assessment of Shoreline Change: Part 1, Historical Shoreline Changes and Associated Coastal Land Loss Along the U.S. Gulf of Mexico (USGS Open File Report 2004-1043) for additional information regarding methods and results. Data in this report are organized into data layers by state and are provided as single-point vector datasets with metadata. Vector shorelines may represent a compilation of data from one or more sources and these sources are attributed in the dataset. All data are intended to be GIS-ready inasmuch as the data should not require any additional cleanup, formatting, or renaming of fields in order to use the data in a Geographic Information System (GIS). This project employs the Environmental Systems Research Institute's (ESRI) ArcView as its GIS mapping tool and contains several data layers (or themes) that are used to create a geographic view of the margin off the U.S. Gulf of Mexico. These vector data form a basemap comprised of polygon and line themes that include a U.S. coastline (1:80,000), U.S. cities, and state boundaries.

Open-File Report↗

USGS2006

High-resolution chirp seismic reflection data acquired from the Cap de Creus shelf and canyon area, Gulf of Lions, Spain in 2004

Seismic reflection data were collected from the Cap de Creus shelf and canyon in the southwest portion of the Gulf of Lions in October 2004. The data were acquired using the U.S. Geological Survey`s (USGS) high-resolution Edgetech CHIRP 512i seismic reflection system aboard the R/V Oceanus. Data from the shipboard 3.5 kHz echosounder were also collected but are not presented here. The seismic reflection data were collected as part of EuroSTRATAFORM funded by the Office of Naval Research. In October 2004, more than 200 km of high resolution seismic reflection data were collected in water depths ranging 30 m - 600 m. All data were recorded with a Delph Seismic PC-based digital recording system and processed with Delph Seismic software. Processed sections were georeferenced into tiff images for digital archive, processing and display. Penetration ranged 20-80 m. The data feature high quality vertical cross-section imagery of numerous sequences of Quaternary seismic stratigraphy. The report includes trackline maps showing the location of the data, as well as both digital data files (SEG-Y) and images of all of the profiles. The data are of high quality and provide new information on the location and thickness of sediment deposits overlying a major erosion surface on the Cap de Creus shelf; they also provide new insight into sediment processes on the walls and in the channel of Cap de Creus Canyon. These data are under study by researchers at the US Geological Survey, the University of Barcelona, and Texas A and M University. Copies of the data are available to all researchers.

Open-File Report↗

USGS2009

Quality-Assurance Data for Routine Water Analyses by the U.S. Geological Survey Laboratory in Troy, New York - July 2001 Through June 2003

The laboratory for analysis of low-ionic-strength water at the U.S. Geological Survey (USGS) Water Science Center in Troy, N.Y., analyzes samples collected by USGS projects throughout the Northeast. The laboratory's quality-assurance program is based on internal and interlaboratory quality-assurance samples and quality-control procedures that were developed to ensure proper sample collection, processing, and analysis. The quality-assurance and quality-control data were stored in the laboratory's Lab Master data-management system, which provides efficient review, compilation, and plotting of data. This report presents and discusses results of quality-assurance and quality control samples analyzed from July 2001 through June 2003. Results for the quality-control samples for 19 analytical procedures were evaluated for bias and precision. Control charts indicate that data for six of the analytical procedures were occasionally biased for either high-concentration or low-concentration samples but were within control limits; these procedures were: acid-neutralizing capacity, chloride, magnesium, nitrate (ion chromatography), potassium, and sodium. The calcium procedure was biased throughout the analysis period for the high-concentration sample, but was within control limits. The total monomeric aluminum and fluoride procedures were biased throughout the analysis period for the low-concentration sample, but were within control limits. The total aluminum, pH, specific conductance, and sulfate procedures were biased for the high-concentration and low-concentration samples, but were within control limits. Results from the filter-blank and analytical-blank analyses indicate that the procedures for 16 of 18 analytes were within control limits, although the concentrations for blanks were occasionally outside the control limits. The data-quality objective was not met for the dissolved organic carbon or specific conductance procedures. Sampling and analysis precision are evaluated herein in terms of the coefficient of variation obtained for triplicate samples in the procedures for 18 of the 21 analytes. At least 90 percent of the samples met data-quality objectives for all procedures except total monomeric aluminum (83 percent of samples met objectives), total aluminum (76 percent of samples met objectives), ammonium (73 percent of samples met objectives), dissolved organic carbon (86 percent of samples met objectives), and nitrate (81 percent of samples met objectives). The data-quality objective was not met for the nitrite procedure. Results of the USGS interlaboratory Standard Reference Sample (SRS) Project indicated satisfactory or above data quality over the time period, with most performance ratings for each sample in the good-to-excellent range. The N-sample (nutrient constituents) analysis had one unsatisfactory rating for the ammonium procedure in one study. The T-sample (trace constituents) analysis had one unsatisfactory rating for the magnesium procedure and one marginal rating for the potassium procedure in one study and one unsatisfactory rating for the sodium procedure in another. Results of Environment Canada's National Water Research Institute (NWRI) program indicated that at least 90 percent of the samples met data-quality objectives for 10 of the 14 analytes; the exceptions were acid-neutralizing capacity, ammonium, dissolved organic carbon, and sodium. Data-quality objectives were not met in 37 percent of samples analyzed for acid-neutralizing capacity, 28 percent of samples analyzed for dissolved organic carbon, and 30 percent of samples analyzed for sodium. Results indicate a positive bias for the ammonium procedure in one study and a negative bias in another. Results from blind reference-sample analyses indicated that data-quality objectives were met by at least 90 percent of the samples analyzed for calcium, chloride, magnesium, pH, potassium, and sodium. Data-quality objectives were met by 78 percent of

Open-File Report↗

USGS2009

Quality-Assurance Data for Routine Water Analyses by the U.S. Geological Survey Laboratory in Troy, New York - July 2005 through June 2007

The laboratory for analysis of low-ionic-strength water at the U.S. Geological Survey (USGS) Water Science Center in Troy, N.Y., analyzes samples collected by USGS projects throughout the Northeast. The laboratory's quality-assurance program is based on internal and interlaboratory quality-assurance samples and quality-control procedures that were developed to ensure proper sample collection, processing, and analysis. The quality-assurance and quality-control data were stored in the laboratory's Lab Master data-management system, which provides efficient review, compilation, and plotting of data. This report presents and discusses results of quality-assurance and quality control samples analyzed from July 2005 through June 2007. Results for the quality-control samples for 19 analytical procedures were evaluated for bias and precision. Control charts indicate that data for eight of the analytical procedures were occasionally biased for either high-concentration or low-concentration samples but were within control limits; these procedures were: total aluminum, calcium, magnesium, nitrate (colorimetric method), potassium, silicon, sodium, and sulfate. Eight of the analytical procedures were biased throughout the analysis period for the high-concentration sample, but were within control limits; these procedures were: total aluminum, calcium, dissolved organic carbon, chloride, nitrate (ion chromatograph), potassium, silicon, and sulfate. The magnesium and pH procedures were biased throughout the analysis period for the low-concentration sample, but were within control limits. The acid-neutralizing capacity, total monomeric aluminum, nitrite, and specific conductance procedures were biased for the high-concentration and low-concentration samples, but were within control limits. Results from the filter-blank and analytical-blank analyses indicated that the procedures for 16 of 17 analytes were within control limits, although the concentrations for blanks were occasionally outside the control limits. The data-quality objective was not met for dissolved organic carbon. Sampling and analysis precision are evaluated herein in terms of the coefficient of variation obtained for triplicate samples in the procedures for 18 of the 21 analytes. At least 93 percent of the samples met data-quality objectives for all analytes except acid-neutralizing capacity (85 percent of samples met objectives), total monomeric aluminum (83 percent of samples met objectives), total aluminum (85 percent of samples met objectives), and chloride (85 percent of samples met objectives). The ammonium and total dissolved nitrogen did not meet the data-quality objectives. Results of the USGS interlaboratory Standard Reference Sample (SRS) Project met the Troy Laboratory data-quality objectives for 87 percent of the samples analyzed. The P-sample (low-ionic-strength constituents) analysis had two outliers each in two studies. The T-sample (trace constituents) analysis and the N-sample (nutrient constituents) analysis had one outlier each in two studies. Results of Environment Canada's National Water Research Institute (NWRI) program indicated that at least 85 percent of the samples met data-quality objectives for 11 of the 14 analytes; the exceptions were acid-neutralizing capacity, total aluminum and ammonium. Data-quality objectives were not met in 41 percent of samples analyzed for acid-neutralizing capacity, 50 percent of samples analyzed for total aluminum, and 44 percent of samples analyzed for ammonium. Results from blind reference-sample analyses indicated that data-quality objectives were met by at least 86 percent of the samples analyzed for calcium, magnesium, pH, potassium, and sodium. Data-quality objectives were met by 76 percent of the samples analyzed for chloride, 80 percent of the samples analyzed for specific conductance, and 77 percent of the samples analyzed for sulfate.

Open-File Report↗

USGS2014

National Oceanic and Atmospheric Administration hydrographic survey data used in a U.S. Geological Survey regional geologic framework study along the Delmarva Peninsula

The U.S. Geological Survey initiated a research effort in 2014 to define the geologic framework of the Delmarva Peninsula inner continental shelf, which included new data collection and assembly of relevant extant datasets. Between 2006 and 2011, Science Applications International Corporation, under contract to the National Oceanic and Atmospheric Administration National Ocean Service, carried out 23 hydrographic surveys covering more than 4,100 square kilometers of the continental shelf using Reson multibeam echosounders and Klein towed sidescan sonars to update nautical charts along the Delmarva Peninsula. Acoustic backscatter data from these instruments are valuable for characterizing aspects of shallow geologic framework, including seafloor geology, sediment transport pathways, and marine resources. The data cover an area that extends from the entrance of Delaware Bay, Delaware, south to Parramore Island, Virginia, in water depths of about 3 to 35 meters below mean lower low water. Data were collected along lines spaced 40 meters apart, resulting in 40 to 100 percent seafloor coverage for multibeam bathymetry. Processed bathymetric data within the Delmarva Peninsula study area are available through a National Ocean Service interactive map interface, but towed sidescan data products are limited, and multibeam backscatter data products have not been available in the past. The U.S. Geological Survey obtained raw Reson multibeam data files from Science Applications International Corporation and the National Oceanic and Atmospheric Administration for 20 hydrographic surveys and extracted backscatter data using the Fledermaus Geocoder Toolbox from Quality Positioning Service. The backscatter mosaics produced by the U.S. Geological Survey for the inner continental shelf of the Delmarva Peninsula using National Oceanic and Atmospheric Administration data increased regional geophysical surveying efficiency, collaboration among government agencies, and the area over which geologic data can be interpreted by the U.S. Geological Survey. This report describes the methods by which the backscatter data were extracted and processed and includes backscatter mosaics and interpolated bathymetric surfaces.

Delaware, Maryland, Virginia↗

USGS2015

Collections management plan for the U.S. Geological Survey Woods Hole Coastal and Marine Science Center Data Library

The U.S. Geological Survey Woods Hole Coastal and Marine Science Center has created a Data Library to organize, preserve, and make available the field, laboratory, and modeling data collected and processed by Woods Hole Coastal and Marine Science Center staff. This Data Library supports current research efforts by providing unique, historic datasets with accompanying metadata. The Woods Hole Coastal and Marine Science Center’s Data Library has custody of historic data and records that are still useful for research, and assists with preservation and distribution of marine science records and data in the course of scientific investigation and experimentation by researchers and staff at the science center. The data accession and retention policies employed by the Woods Hole Coastal and Marine Science Center Data Library are based on scientific need and the National Archives and Records Administration standards for Federal records retention. Criteria for inclusion of data and records into the Data Library, the scope of the Data Library holdings, and operating procedures for the management and running of the library are designed to support the research operations of the U.S. Geological Survey. This report explains the roles and detailed responsibilities of library and scientific staff, and provides step-by-step instructions for managing the collections of the Woods Hole Coastal and Marine Science Center Data Library.

Open-File Report↗

USGS2016

Improve wildlife species tracking—Implementing an enhanced global positioning system data management system for California condors

U.S. Fish and Wildlife Service (USFWS) staff in the Pacific Southwest Region and at the Hopper Mountain National Wildlife Refuge Complex requested technical assistance to improve their global positioning system (GPS) data acquisition, management, and archive in support of the California Condor Recovery Program. The USFWS deployed and maintained GPS units on individual Gymnogyps californianus (California condor) in support of long-term research and daily operational monitoring and management of California condors. The U.S. Geological Survey (USGS) obtained funding through the Science Support Program to provide coordination among project participants, provide GPS Global System for Mobile Communication (GSM) transmitters for testing, and compare GSM/GPS with existing Argos satellite GPS technology. The USFWS staff worked with private companies to design, develop, and fit condors with GSM/GPS transmitters. The Movebank organization, an online database of animal tracking data, coordinated with each of these companies to automatically stream their GPS data into Movebank servers and coordinated with USFWS to improve Movebank software for managing transmitter data, including proofing/error checking of incoming GPS data. The USGS arranged to pull raw GPS data from Movebank into the USGS California Condor Management and Analysis Portal (CCMAP) ( https://my.usgs.gov/ccmap ) for production and dissemination of a daily map of condor movements including various automated alerts. Further, the USGS developed an automatic archiving system for pulling raw and proofed Movebank data into USGS ScienceBase to comply with the Federal Information Security Management Act of 2002. This improved data management system requires minimal manual intervention resulting in more efficient data flow from GPS data capture to archive status. As a result of the project’s success, Pinnacles National Park and the Ventana Wildlife Society California condor programs became partners and adopted the same workflow, tracking, and data archive system. This GPS tracking data management model and workflow should be applicable and beneficial to other wildlife tracking programs.

California↗