USGS Science⌕ Search

SEARCH · USGS Science

Results for “Research and Development Report”

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 1,801 records · Page 100Linked to original sources
USGS2021

Alaska Landbird Conservation Plan

Alaska is a land of extremes. The diversity of its avifauna reflects the heterogeneity of its landscape, with more than 500 species of birds recorded in the state. Species inhabiting primarily terrestrial habitats, known collectively as landbirds, constitute the largest and most ecologically diverse component of the Alaska avifauna. Habitats used by landbirds range from temperate rainforests in southeastern Alaska to Arctic tundra across much of northern Alaska. Most of these landbird species are migratory, and four major global migration flyways converge on rich breeding areas in Alaska. Alaska has one endemic landbird species, the McKay’s Bunting, and is home to an impressive number of landbird populations for which it hosts a large proportion of the regional, continental, or global population. Thus, Alaska has a significant stewardship responsibility for these particular landbird species and subspecies. Habitats in Alaska remain largely pristine due to the region’s remote nature, vast size, and small human population. Alaska’s growing population and attendant economic development, however, present many challenges that could affect all wildlife, including landbirds. Threats in Alaska are often considered to be less significant than those occurring elsewhere, where habitats are being altered by more rapidly increasing anthropogenic pressures, but they carry far-reaching consequences nonetheless. Habitats and ecosystem dynamics are changing rapidly due to the magnitude of climate warming at high latitudes. As such, effective landbird conservation in Alaska requires a broad, landscape-scale approach. Conservation of landbirds over such an extensive and diverse landscape also demands that we integrate efforts in habitat management, population monitoring, research, education, and outreach at local, regional, continental, and international scales. Information on distribution and habitat requirements of landbirds should be incorporated into land-use planning decisions. Synthesizing information on distribution and population trends of landbirds is a critical, time-sensitive task. Such information should be provided in a form that is readily available to land managers and policy decision-makers. The primary objectives of this plan are to (1) describe the region and Alaska’s landbird avifauna; (2) identify species of concern, important habitats, and key information needs; (3) highlight major conservation issues and threats to landbirds; and (4) identify potential conservation actions. We first examine landbird conservation at the statewide level within broad perspectives (regional, continental, and global), then take a detailed look at the specific issues, information needs, and potential conservation actions within each Bird Conservation Region in Alaska.

Alaska↗
USGS2010

EAARL Coastal Topography-Eastern Florida, Post-Hurricane Jeanne, 2004: 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 Aeronautics and Space Administration (NASA), Wallops Flight Facility, VA. This project provides highly detailed and accurate datasets of a portion of the eastern Florida coastline beachface, acquired post-Hurricane Jeanne (September 2004 hurricane) on October 1, 2004. 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↗
USGS2006

Quality-Assurance Data for Routine Water Analyses by the U.S. Geological Survey Laboratory in Troy, New York--July 1999 through June 2001

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 LabMaster 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 1999 through June 2001. Results for the quality-control samples for 18 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: acid-neutralizing capacity, total monomeric aluminum, total aluminum, calcium, chloride and nitrate (ion chromatography and colormetric method) and sulfate. The total aluminum and dissolved organic carbon procedures were biased throughout the analysis period for the high-concentration sample, but were within control limits. The calcium and specific conductance procedures were biased throughout the analysis period for the low-concentration sample, but were within control limits. The magnesium procedure was biased for the high-concentration and low concentration samples, but was within control limits. Results from the filter-blank and analytical-blank analyses indicate that the procedures for 14 of 15 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 17 of the 18 analytes. At least 90 percent of the samples met data-quality objectives for all analytes except ammonium (81 percent of samples met objectives), chloride (75 percent of samples met objectives), and sodium (86 percent of samples met objectives). Results of the USGS interlaboratory Standard Reference Sample (SRS) Project indicated good data quality over the time period, with most ratings for each sample in the good to excellent range. The P-sample (low-ionic-strength constituents) analysis had one satisfactory rating for the specific conductance procedure in one study. The T-sample (trace constituents) analysis had one satisfactory rating for the aluminum procedure in one study and one unsatisfactory rating for the sodium procedure in another. The remainder of the samples had good or excellent ratings for each study. Results of Environment Canada's National Water Research Institute (NWRI) program indicated that at least 89 percent of the samples met data-quality objectives for 10 of the 14 analytes; the exceptions were ammonium, total aluminum, dissolved organic carbon, and sodium. Results indicate a positive bias for the ammonium procedure in all studies. Data-quality objectives were not met in 50 percent of samples analyzed for total aluminum, 38 percent of samples analyzed for dissolved organic carbon, and 27 percent of samples analyzed for sodium. Results from blind reference-sample analyses indicated that data-quality objectives were met by at least 91 percent of the samples analyzed for calcium, chloride, fluoride, magnesium, pH, potassium, and sulfate. Data-quality objectives were met by 75 percent of the samples analyzed for sodium and 58 percent of the samples analyzed for specific conductance.

Open-File Report↗
USGS1982

Design concepts for a Global Telemetered Seismograph Network

This study represents a first step in developing an integrated, real-time global seismic data acquisition system a Global Telemetered Seismograph Network (GTSN). The principal objective of the GTSN will be to acquire reliable, high-quality, real-time seismic data for rapid location and analysis of seismic events. A secondary, but important, objective of the GTSN is to augment the existing off-line seismic data base available for research. The deployment of the GTSN will involve a variety of interrelated activities development of the data acquisition and receiving equipment, establishment of satellite and terrestrial communication links, site selection and preparation, training of station personnel, equipment installation, and establishment of support facilities. It is a complex program and the development of a sound management plan will be essential. The purpose of this study is not to fix design goals or dictate avenues of approach but to develop working concepts that may be used as a framework for program planning. The international exchange of seismic data has been an important factor in the progress that has been made during the past two decades in our understanding of earthquakes and global tectonics. The seismic data base available for analysis and research is derived principally from the Global Seismograph Network (GSN), which is funded and managed by the U.S. Geological Survey (USGS). The GSN comprises some 120 seismograph stations located in more than 60 countries of the world. Established during the 1960 s with the installation of the World-Wide Standardized Seismograph Network (WWSSN) , the GSN has been augmented in recent years by the installation of more advanced data systems, such as the Seismic Research Observatories (SRO), the modified High-Gain LongPeriod (ASRO) seismographs, and the digital WWSSN (DWWSSN). The SRO, ASRO, and DWWSSN stations have the common, distinctive feature of digital data recording, so they are known collectively as the Global Digital Seismograph Network (GDSN). The fundamental objective in operating the GSN is to create and update a seismic data base that is accessible without restrictions to organizations and research scientists throughout the world. The USGS provides cooperating stations with instrumentation, training, and continuing support, including supplies and on-site maintenance. In return, the host organization operates the equipment and sends the recorded data to the USGS. Analog data (seismograms) are microfilmed and about four million copies are requested annually by researchers. Digital data, which are recorded on magnetic tape, are organized by the USGS Albuquerque Seismological Laboratory (ASL) into networkday tapes and copies of the day tapes are furnished to data users through national and regional data centers. After copying, original data are returned to the stations and used for local research. Most of the stations in the GSN also provide the USGS with seismic readings « phase arrival times and amplitudes scaled from the seismograms. These readings are transmitted on a daily or biweekly basis via commercial or diplomatic communication channels. They are used by the USGS National Earthquake Information Service (NEIS) to determine the location and magnitude of earthquakes occurring throughout the world. The results are published monthly in bulletins that are distributed to the participating stations and virtually all scientific organizations that are involved in seismological studies. It is a much-valued service that provides a current, updated catalog of seismic activity on a global scale. The NEIS also has the responsibility for rapid reporting of large and potentially destructive earthquakes. The NEIS issues news bulletins as soon as possible after the occurrence of magnitude 6.5 or greater earthquakes (magnitude 5 or greater in the conterminous United States). The news bulletins are sent to disaster relief, public safety, and other interested organizations. Tsunami warnings issued to countries bordering the Pacific Ocean are based initially on earthquake location and magnitude data. Rapid reporting of earthquakes requires real-time waveform data or readings. Currently, signals are being telemetered from more than thirty stations in the United States to the NEIS, which is located in Golden, Colorado. An extension of the telemetry network to other countries will provide the seismological community with a significantly improved means of monitoring earthquake activity in real time; it will lower the response time for determining the location and magnitude of potentially destructive or tsunamigenic earthquakes and it will provide more timely information that may be needed by governments to respond promptly.

Open-File Report↗
USGS1966

Water in the Humboldt River Valley near Winnemucca, Nevada

Most of the work of the interagency Humboldt River Research Project in the Winnemucca reach of the Humboldt River valley has been completed. More than a dozen State and Federal agencies and several private organizations and individuals participated in the study. The major objective of the project, which began in 1959, is to evaluate the water resources of the entire Humboldt River basin. However, because of the large size of the basin, most of the work during the first 5 years of the project was done in the Winnemucca area. The purpose of this report is to summarize briefly and simply the information regarding the water resources of the Winnemucca area-especially the quantitative aspects of the flow system-given in previous reports of the project. The Winnemucca reach of the Humboldt River valley, which is in north-central Nevada, is about 200 miles downstream from the headwaters of the Humboldt River and includes that part of the valley between the Comus and Rose Creek gaging stations. Average annual inflow to the storage area (the valley lowlands) in the Winnemucca reach in water years 1949-62 was about 250,000 acre-feet. Of this amount, about 68 percent was Humboldt River streamflow, as measured at the Comus gaging station, 23 percent was precipitation directly on the storage area, 6 percent was ground-water inflow, and about 3 percent was tributary streamflow. Average annual streamflow at the Rose Creek gaging station during the same period was about 155,000 acre-feet, or about 17,000 acre-feet less than that at the Comus gaging station. Nearly all the streamflow lost was consumed by evapotranspiration in the project area. Total average annual evapotranspiration loss during the period was about 115,000 acre-feet, or about 42 percent of the total average annual outflow. The most abundant ions in the ground and surface water in the area are commonly sodium and bicarbonate. Much of the water has a dissolved-solids content that ranges from 500 to 750 parts per million; however, locally, the dissolved-solids content of the ground water is more than 5,000 parts per million. The chemical quality of the Humboldt River, especially during periods of low flow, reflects the chemical quality of ground-water inflow from tributary areas that discharges into the river. Almost all water in the project area is moderately hard to very hard; otherwise, it is generally suitable for most uses. Increased ground-water development, the conjunctive use of ground and surface water, and increased irrigation efficiency would probably conserve much of the water presently consumed by nonbeneficial evapotranspiration. Intensive ground-water development, especially from the highly permeable medial gravel subunit, will, however, decrease the flow of the Humboldt River to the extent that some pumpage may not be offset by a corresponding decrease in natural evapotranspiration losses. Such streamflow depletions will therefore infringe upon downstream surface-water rights. The results of this study indicate that the Humboldt River and ground water in the unconsolidated deposits beneath and adjacent to the river in the Winnemucca area are closely related. Somewhat similar conditions probably exist elsewhere in the Humboldt River valley. Additional detailed studies are needed-both upstream and downstream from the Winnemucca area-to adequately define the flow system and the interrelations among the components of the system in the remainder of the valley. Before proceeding with additional detailed studies, however, a 1-year overall appraisal of the water resources of the basin should be considered. A major objective of this study would be to provide information that would help select the next subarea of the valley to be studied in detail and to decide which of the methods of study used in the Winnemucca area could be most effectively used in the future studies.

Water Supply Paper↗
USGS2020

Optimization of tidal marsh management at the Cape May and Supawna Meadows National Wildlife Refuges, New Jersey, through use of structured decision making

Structured decision making is a systematic, transparent process for improving the quality of complex decisions by identifying measurable management objectives and feasible management actions; predicting the potential consequences of management actions relative to the stated objectives; and selecting a course of action that maximizes the total benefit achieved and balances tradeoffs among objectives. The U.S. Geological Survey, in cooperation with the U.S. Fish and Wildlife Service, applied an existing, regional framework for structured decision making to develop a prototype tool for optimizing tidal marsh management decisions at the Cape May and Supawna Meadows National Wildlife Refuges in New Jersey. Refuge biologists, refuge managers, and research scientists identified multiple potential management actions to improve the ecological integrity of 13 marsh management units within the refuges and estimated the outcomes of each action in terms of performance metrics associated with each management objective. Value functions previously developed at the regional level were used to transform metric scores to a common utility scale, and utilities were summed to produce a single score representing the total management benefit that would be accrued from each potential management action. Constrained optimization was used to identify the set of management actions, one per marsh management unit, that would maximize total management benefits at different cost constraints at the refuge scale. Results indicated that, for the objectives and actions considered here, total management benefits may increase consistently up to approximately $ 785,000, but that further expenditures may yield diminishing return on investment. Management actions in optimal portfolios at total costs less than $ 785,000 included applying sediment to the marsh surface (thin layer deposition) in seven marsh management units, controlling the invasive reed Phragmites australis in four marsh management units, remediating hydrologic alterations in two marsh management units, and planting native vegetation in one marsh management unit. The management benefits were derived from expected improvements in the capacity for marsh elevation to keep pace with sea-level rise, increases in numbers of spiders (as an indicator of trophic health) and tidal marsh obligate birds, and increased cover of native vegetation. The prototype presented here provides a framework for decision making at the Cape May and Supawna Meadows National Wildlife Refuges that can be updated as new data and information become available. Insights from this process may also be useful to inform future habitat management planning at the refuges.

New Jersey↗
USGS2010

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↗
USGS2014

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↗
USGS2023

Documenting Arctic sea ice dynamics with Global Fiducials Program imagery

For more than 25 years, the U.S. Geological Survey (USGS) has used the remote-sensing capabilities of United States National Imagery Systems (USNIS) to obtain high-resolution electro-optical imagery to monitor Earth’s response to global environmental change. A major focus has been monitoring sea ice behavior in the Arctic Ocean and its marginal seas. In 1997 and 1998, under the direction of the Global Fiducials Program (GFP), USNIS imagery was collected during the Surface Heat Budget of the Arctic Ocean (SHEBA) Project. In 1999, collection of USNIS imagery of six static sea ice sites in the Arctic Ocean and its marginal seas began, and the imagery was archived in the USGS-hosted Global Fiducials Library (GFL). The static sites were imaged through 2014, creating time series of geographically referenced images which scientists have used to study seasonal changes in Arctic ice over the same locations for extended time periods. In early 2009, the Central Intelligence Agency’s MEDEA Program requested that the USGS use USNIS imagery to track movements of sea ice floes during an entire Arctic summer (April through September). The goal was to improve researchers’ understanding of seasonal changes in Arctic sea ice. In order to track and repeatedly capture imagery of the same ice as it drifted across the Arctic Ocean, the USGS developed a methodology and a series of protocols to use data from telemetering drift buoys deployed at locations across the Arctic Ocean by the International Arctic Buoy Programme (IABP) to track the drift of targeted ice masses for periods that exceeded a year. Resulting time series of sea ice imagery, captured while monitoring 38 individual buoys, were archived in the GFL. In 2013 and 2014, in support of the Seasonal Ice Zone Reconnaissance Surveys (SIZRS) Program led by the University of Washington, Seattle, Washington, the USGS requested the collection of USNIS imagery of selected sites in the Beaufort and Chukchi Seas located at every degree of latitude between 70º and 80º N. along a north-south transect. This was done to track and understand the interplay among the ice, atmosphere, and ocean and what it contributes to the rapid decline in summer ice extent that has occurred in recent years. Under the auspices of the GFP, thousands of sea ice images have been collected. Many of those that pass a quality and cloud-cover screening are archived in the GFL. Of these, more than 1,750 sea ice images have been publicly released, following an editing and processing procedure that produces high-resolution degraded images, known as “literal imagery-derived products” or LIDPs. These LIDPs have been approved for free, unrestricted public distribution and scientific analysis. The LIDPs can be downloaded from the USGS Global Fiducials Library Data Access Portal (USGS GFLDAP) at https://www.usgs.gov/global-fiducials-library-data-access-portal . In addition, nonliteral imagery-derived products (nonliteral IDPs), such as metadata, maps, charts, and graphs, have also been released.

Open-File Report↗
USGS2010

EAARL Coastal Topography-Chandeleur Islands, Louisiana, 2010: Bare Earth

These remotely sensed, geographically referenced elevation measurements of lidar-derived bare-earth (BE) and submerged 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 Aeronautics and Space Administration (NASA), Wallops Flight Facility, VA. This project provides highly detailed and accurate datasets of a portion of the Chandeleur Islands, acquired March 3, 2010. 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↗
USGS2022

Exploring and mitigating plague for One Health purposes

Purpose of Review In 2020, the Appropriations Committee for the U.S. House of Representatives directed the CDC to develop a national One Health framework to combat zoonotic diseases, including sylvatic plague, which is caused by the flea-borne bacterium Yersinia pestis . This review builds upon that multisectoral objective. We aim to increase awareness of Y. pestis and to highlight examples of plague mitigation for One Health purposes (i.e., to achieve optimal health outcomes for people, animals, plants, and their shared environment). We draw primarily upon examples from the USA, but also discuss research from Madagascar and Uganda where relevant, as Y. pestis has emerged as a zoonotic threat in those foci. Recent Findings Historically, the bulk of plague research has been directed at the disease in humans. This is not surprising, given that Y. pestis is a scourge of human history. Nevertheless, the ecology of Y. pestis is inextricably linked to other mammals and fleas under natural conditions. Accumulating evidence demonstrates Y. pestis is an unrelenting threat to multiple ecosystems, where the bacterium is capable of significantly reducing native species abundance and diversity while altering competitive and trophic relationships, food web connections, and nutrient cycles. In doing so, Y. pestis transforms ecosystems, causing “shifting baselines syndrome” in humans, where there is a gradual shift in the accepted norms for the condition of the natural environment. Eradication of Y. pestis in nature is difficult to impossible, but effective mitigation is achievable; we discuss flea vector control and One Health implications in this context. Summary There is an acute need to rapidly expand research on Y. pestis , across multiple host and flea species and varied ecosystems of the Western US and abroad, for human and environmental health purposes. The fate of many wildlife species hangs in the balance, and the implications for humans are profound in some regions. Collaborative multisectoral research is needed to define the scope of the problem in each epidemiological context and to identify, refine, and implement appropriate and effective mitigation practices.

Current Tropical Medicine Reports↗
USGS2014

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

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 pre-Hurricane Sandy on October 18, 22, 23, and 26, 2012. The datasets are made available for use as a management tool to research scientists and natural-resource managers. An innovative airborne lidar, 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 near-shore 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↗
USGS2019

Optimization of salt marsh management at the Rhode Island National Wildlife Refuge Complex through use of structured decision making

Structured decision making is a systematic, transparent process for improving the quality of complex decisions by identifying measurable management objectives and feasible management actions; predicting the potential consequences of management actions relative to the stated objectives; and selecting a course of action that maximizes the total benefit achieved and balances tradeoffs among objectives. The U.S. Geological Survey, in cooperation with the U.S. Fish and Wildlife Service, applied an existing, regional framework for structured decision making to develop a prototype tool for optimizing salt marsh management decisions at the Rhode Island National Wildlife Refuge Complex. Refuge biologists, refuge managers, and research scientists identified multiple potential management actions to improve the ecological integrity of nine salt marsh management units within the refuge complex and estimated the outcomes of each action in terms of performance metrics associated with each management objective. Value functions previously developed at the regional level were used to transform metric scores to a common utility scale, and utilities were summed to produce a single score representing the total management benefit that would be accrued from each potential management action. Constrained optimization was used to identify the set of management actions, one per salt marsh management unit, that would maximize total management benefits at different cost constraints at the refuge scale. Results indicated that, for the objectives and actions considered here, total management benefits may increase consistently up to approximately $ 150,000, but that further expenditures may yield diminishing return on investment. Management actions in optimal portfolios at total costs less than $ 150,000 included digging runnels (by hand or machine) on the marsh surface to improve drainage in eight management units, applying sediment to the marsh surface (thin layer deposition) in one management unit, constructing islands for use by tidal marsh obligate birds in two management units, and controlling Phragmites australis in one management unit. The management benefits were derived from expected improvements in the capacity for marsh elevation to keep pace with sea-level rise and increases in numbers of spiders (as an indicator of trophic health) and tidal marsh obligate birds. The prototype presented here provides a framework for decision making at the Rhode Island National Wildlife Refuge Complex that can be updated as new data and information become available. Insights from this process may also be useful to inform future habitat management planning at the refuge.

Rhode Island↗
USGS2022

Optimization of salt marsh management at the Petit Manan National Wildlife Refuge of the Maine Coastal Islands National Wildlife Refuge Complex, Maine, through use of structured decision making

Structured decision making is a systematic, transparent process for improving the quality of complex decisions by identifying measurable management objectives and feasible management actions; predicting the potential consequences of management actions relative to the stated objectives; and selecting a course of action that maximizes the total benefit achieved and balances tradeoffs among objectives. The U.S. Geological Survey, in cooperation with the U.S. Fish and Wildlife Service, applied an existing, regional framework for structured decision making to develop a prototype tool for optimizing tidal marsh management decisions at the Petit Manan National Wildlife Refuge of the Maine Coastal Islands National Wildlife Refuge Complex in Maine. Refuge biologists, refuge managers, and research scientists identified multiple potential management actions to improve the ecological integrity of two marsh management units within the refuge complex, totaling about 47 hectares, and estimated the outcomes of each action in terms of performance metrics associated with each management objective. Value functions previously developed at the regional level were used to transform metric scores to a common utility scale, and utilities were summed to produce a single score representing the total management benefit that could be accrued from each potential management action. Constrained optimization was used to identify the set of management actions, one per marsh management unit, that could maximize total management benefits at different cost constraints at the refuge scale. Results indicated that, for the objectives and actions considered here, total management benefits may increase consistently up to $ 9,545, and may continue to increase at a lower rate with further expenditures. Potential management actions in optimal portfolios at total costs less than or equal to $ 9,545 included removing dikes to restore tidal flow in the Gouldsboro Bay management unit and installing runnels to improve surface-water drainage in the Sawyers Marsh management unit. The potential management benefits were derived from expected increases in the numbers of tidal marsh obligate breeding birds and density of spiders (as an indicator of trophic health), reduced duration of flooding, and increased capacity of marsh elevation to keep pace with sea-level rise. The prototype presented here does not resolve management decisions; rather, it provides a framework for decision making at the Maine Coastal Islands National Wildlife Refuge Complex that can be updated for implementation as new data and information become available. Insights from this process may also be useful to inform future habitat management planning at the refuge complex.

Maine↗
USGS2020

Using advanced population genomics to better understand the relationship between offshore and spawning habitat use for Atlantic Sturgeon

Atlantic Sturgeon ( Acipenser oxyrinchus oxyrinchus ) are a large-bodied anadromous fish that historically supported important fisheries along the east coast of the United States. Following years of overharvest and habitat degradation, populations experienced severe declines. In 2012, the National Marine Fisheries Service listed Atlantic Sturgeon under the Endangered Species Act (ESA; 61 FR 4722). Their listing named five Distinct Population Segments (DPSs), predicated on genetic groups composed of geographically proximate populations. Federal management of Atlantic Sturgeon presents challenges, as sturgeon from each of the five DPSs mix extensively in coastal and marine habitats yet take and recovery progress must be evaluated separately for each unit. Genetic assignment testing based on mitochondrial and microsatellite markers allows individuals to be assigned back to their natal river and DPS. However, this approach is not perfect and some individuals may be incorrectly assigned. Recent advances in genomics offer the potential of a higher resolution approach to genetic assignment testing, and thus may reduce uncertainty associated with assignment testing. In addition, genomics allows a greater number of markers to be examined from across a broader portion of the sturgeon genome, thus may provide an enhanced perspective of population structure for the species, and potentially allow other previously intractable questions to be addressed (Bernatchez et al. 2017, Supple and Shapiro 2018). We used next-generation sequencing to develop a draft genome for Atlantic Sturgeon and identify single nucleotide polymorphisms (SNPs) that could be used to resolve the natal river and DPS of individual Atlantic Sturgeon. We identified 1,210 candidate SNPs within the nuclear genome as well as 49 SNPs within the mitochondrial genome. After filtering and review, we selected 161 nuclear SNPs and 39 mitochondrial SNPs for further testing and evaluation. We used genotyping-in-thousands by sequencing (GT-seq) to simultaneously sequence nuclear SNP loci, mitochondrial SNP loci, and the existing panel of twelve microsatellite loci. This effort required a pilot sequencing run on a single sturgeon sample to test marker amplification and refine primer strengths, followed by a series of sequencing runs to generate baseline data for 288 individuals representing nine populations of Atlantic Sturgeon in four DPSs. Using baseline data from the nine populations, we ran a series of genomic analyses to characterize diversity within and among populations, providing a benchmark for this species using the new SNP markers. Allelic richness was similar for all populations, although there was a general trend of more northern population containing greater levels of allelic richness. Interestingly, we observed linkage disequilibrium among many pairs of loci within many populations. This might be the result of physical linkage but could also suggest these populations are recovering from genetic bottlenecks and/or are effectively small, leading to specific haplotypes to be favored by chance. Pairwise differentiation among populations varied among the populations ( F ST range: 0.010-0.098) and was significantly correlated ( r = 0.771; P < 0.001) to pairwise F ST observed using microsatellite markers). Population clustering and ordination techniques using the new genomic data both support an overall population structure that is similar to the current DPS management units (which were developed primarily based on microsatellite genetic data). Overall, this suggests that existing microsatellite markers and the panel of SNP markers developed in this study provide similar information about the populations structure and ecology of Atlantic Sturgeon. Given the observed differences in allele frequencies among populations, our genomic baseline supports previous assertations that Atlantic Sturgeon show natal homing, despite mixing extensively in marine waters during non-breeding periods. Lower levels of differentiation between populations in the South Atlantic DPS suggest that populations in this region may have greater levels of gene flow relative to their more northerly conspecifics, which has also previously been suggested based on microsatellite data. The observed differentiation among populations provides the necessary foundation for determining the natal river and DPS of Atlantic Sturgeon using assignment testing. We tested the utility of our new genomic baseline for resolving the population and DPS of Atlantic Sturgeon. Our nuclear SNP markers showed utility for identifying the origin of unknown Atlantic Sturgeon samples, as 86.5% were assigned to the correct DPS and 66.3% were assigned to the correct natal river. However, since this study was funded the Conservation Genetics and Genomics Laboratory at Leetown Science Center has made significant improvements to their microsatellite genetic baseline, which now performs more effectively than our new genomic approach (the genetic baseline includes 12 populations and 5 DPSs, and correctly assigns 95.8% of individuals to DPS and 84.9% of individuals to their natal population using 12 microsatellite loci). We conducted an ad hoc exploration of how additional microsatellite or nuclear SNP loci may further improve the accuracy of assignment testing. We found that additional microsatellite markers are likely to result in greater improvements in assignment efficiency than additional nuclear SNPs. However, a much larger number of SNP loci (which if identified could be sequenced using other methods that are now available; e.g., the RAD-capture approach published by Ali et al. 2016) could produce assignment efficiencies that are greater than what is currently feasible using microsatellites. In the absence of further research and development of additional SNP markers for Atlantic Sturgeon (possibly using an approach other than GT-seq), the existing microsatellite loci are the most effective means available to determine the natal river and DPS of Atlantic Sturgeon encountered in offshore waters. Because our new genomic markers were less effective than the existing panel of 12 microsatellite markers, we chose to use the existing microsatellite markers to assign Atlantic Sturgeon captured in another BOEM-funded study (cooperative agreement M16AC00003; Monitoring endangered Atlantic Sturgeon and commercial finfish habitat use offshore New York) following consultation with our project officer. Using this approach, we genotyped and assigned 186 Atlantic Sturgeon captured in coastal waters off the Rockaway Peninsula, New York. The vast majority of these sturgeon were assigned to the New York Bight DPS (94.62%), and most appear to belong to the Hudson River population (87.10%) with smaller contributions from the Delaware River population (7.53%). Smaller contributions (2.15%) were observed from six other populations, including those from the James, York, Kennebec, Ogeechee, and Edisto rivers. Although most of the fish we assigned were assigned to the nearest spawning rivers (Hudson and Delaware), the contributions from distant rivers is consistent with the propensity of this species to move long distances and form mixed stock aggregations along the continental shelf. This finding indicates that spawning populations (and their corresponding DPS) from distant locations may potentially be impacted by offshore activities. In fact, activities in this region of the New York Bight could negatively impact Atlantic Sturgeon population from at least four different DPSs. Genetic or genomic assignment testing remains an essential tool to characterize potential impacts to Atlantic Sturgeon populations and should be applied more broadly to better characterize potential impacts of activities in other locations.

Atlantic Coast↗
USGS2021

Synthesis of habitat availability and carrying capacity research to support water management decisions and enhance conditions for Pacific salmon in the Willamette River, Oregon

Flow management is complex in the Willamette River Basin where the U.S. Army Corps of Engineers owns and operates a system of 13 dams and reservoirs (hereinafter Willamette Project), which are spread throughout three large tributaries including the Middle Fork Willamette, McKenzie, and Santiam Rivers. The primary purpose of the Willamette Project is flood-risk management, which provides critical protection to the Willamette Valley, but flow managers must also consider factors such as power generation, water-quality improvement, irrigation, recreation, and protection for aquatic species such as U.S. Endangered Species Act-listed Chinook salmon ( Oncorhynchus tshawytscha ) and steelhead ( O. mykiss ). Flow-management decision-making in the basin can benefit from models that allow for flow-scenario comparisons and a wide range of modeling methods are available. For this study, we examined existing datasets and modeling efforts in the basin and provided an overview of available options. Most previous studies used Physical Habitat Simulation System, habitat data were collected from a series of transects within modeled reaches, and habitat suitability indices were obtained from the literature, or using expert opinion. These studies provide information for specific reaches of the Willamette River Basin, which limits their ability to provide broad-scale predictive capability. Recent efforts to develop a two-dimensional hydraulic model in the mainstem Willamette River, and in specific reaches of primary tributaries downstream from Project dams, have bolstered modeling capabilities in the basin. This work has developed spatially continuous water depth and velocity data in more than 250 kilometers (km) of river downstream from Project dams and has predictive capability throughout the year at flows up to normal peak levels. Additionally, other methods are described for estimating habitat availability, which include habitat suitability criteria, logistic regression, occupancy and abundance modeling, and energetic based approaches. There are strengths and weaknesses to each approach and selection of the preferred approach in the Willamette River Basin will depend on the desired metrics of interest and the risk tolerance of managers and stakeholders in the basin.

Oregon↗
USGS2016

Estimating black bear density in New Mexico using noninvasive genetic sampling coupled with spatially explicit capture-recapture methods

During the 2004–2005 to 2015–2016 hunting seasons, the New Mexico Department of Game and Fish (NMDGF) estimated black bear abundance (Ursus americanus) across the state by coupling density estimates with the distribution of primary habitat generated by Costello et al. (2001). These estimates have been used to set harvest limits. For example, a density of 17 bears/100 km2 for the Sangre de Cristo and Sacramento Mountains and 13.2 bears/100 km2 for the Sandia Mountains were used to set harvest levels. The advancement and widespread acceptance of non-invasive sampling and mark-recapture methods, prompted the NMDGF to collaborate with the New Mexico Cooperative Fish and Wildlife Research Unit and New Mexico State University to update their density estimates for black bear populations in select mountain ranges across the state. We established 5 study areas in 3 mountain ranges: the northern (NSC; sampled in 2012) and southern Sangre de Cristo Mountains (SSC; sampled in 2013), the Sandia Mountains (Sandias; sampled in 2014), and the northern (NSacs) and southern Sacramento Mountains (SSacs; both sampled in 2014). We collected hair samples from black bears using two concurrent non-invasive sampling methods, hair traps and bear rubs. We used a gender marker and a suite of microsatellite loci to determine the individual identification of hair samples that were suitable for genetic analysis. We used these data to generate mark-recapture encounter histories for each bear and estimated density in a spatially explicit capture-recapture framework (SECR). We constructed a suite of SECR candidate models using sex, elevation, land cover type, and time to model heterogeneity in detection probability and the spatial scale over which detection probability declines. We used Akaike’s Information Criterion corrected for small sample size (AICc) to rank and select the most supported model from which we estimated density. We set 554 hair traps, 117 bear rubs and collected 4,083 hair samples. We identified 725 (367 M, 358 F) individuals; the sex ratio for each study area was approximately equal. Our density estimates varied within and among mountain ranges with an estimated density of 21.86 bears/100 km2 (95% CI: 17.83 – 26.80) for the NSC, 19.74 bears/100 km2 (95% CI: 13.77 – 28.30) in the SSC, 25.75 bears/100 km2 (95% CI: 13.22 – 50.14) in the Sandias, 21.86 bears/100 km2 (95% CI: 17.83 – 26.80) in the NSacs, and 16.55 bears/100 km2 (95% CI: 11.64 – 23.53) in the SSacs. Overall detection probability for hair traps and bear rubs, combined, was low across all study areas and ranged from 0.00001 to 0.02. We speculate that detection probabilities were affected by failure of some hair samples to produce a complete genotype due to UV degradation of DNA, and our inability to set and check some sampling devices due to wildfires in the SSC. Ultraviolet radiation levels are particularly high in New Mexico compared to other states where NGS methods have been used because New Mexico receives substantial amounts of sunshine, is relatively high in elevation (1,200 m – 4,000 m), and is at a lower latitude. Despite these sampling difficulties, we were able to produce density estimates for New Mexico black bear populations with levels of precision comparable to estimated black bear densities made elsewhere in the U.S. Our ability to generate reliable black bear density estimates for 3 New Mexico mountain ranges is attributable to our use of a statistically robust study design and analytical method. There are multiple factors that need to be considered when developing future SECR-based density estimation projects. First, the spatial extent of the population of interest and the smallest average home range size must be determined; these will dictate size of the trapping array and spacing necessary between hair traps. The number of technicians needed and access to the study areas will also influence configuration of the trapping array. We believe shorter sampling occasions could be implemented to reduce degradation of DNA due to UV radiation; this might help increase amplification rates and thereby increase both the number of unique individuals identified and the number of recaptures, improving the precision of the density estimates. A pilot study may be useful to determine the length of time hair samples can remain in the field prior to collection. In addition, researchers may consider setting hair traps and bear rubs in more shaded areas (e.g., north facing slopes) to help reduce exposure to UV radiation. To reduce the sampling interval it will be necessary to either hire more field personnel or decrease the number of hair traps per sampling session. Both of these will enhance detection of long-range movement events by individual bears, increase initial capture and recapture rates, and improve precision of the parameter estimates. We recognize that all studies are constrained by limited resources, however, increasing field personnel would also allow a larger study area to be sampled or enable higher trap density. In conclusion, we estimated the density of black bears in 5 study areas within 3 mountains ranges of New Mexico. Our estimates will aid the NMDGF in setting sustainable harvest limits. Along with estimates of density, information on additional demographic rates (e.g., survival rates and reproduction) and the potential effects that climate change and future land use may have on the demography of black bears may also help inform management of black bears in New Mexico, and may be considered as future areas for research.

New Mexico↗
USGS2014

EAARL-B coastal topography: Fire Island, New York, pre-Hurricane Sandy, 2012: seamless (bare earth and submerged)

These remotely sensed, geographically referenced elevation measurements of lidar-derived seamless (bare-earth and 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 Fire Island, New York, acquired pre-Hurricane Sandy on October 27, 2012. The datasets are made available for use as a management tool to research scientists and natural-resource managers. An innovative airborne lidar, 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 near-shore 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 York↗

Refine your search to explore more results.