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At least 73 records · Page 4Linked to original sources

Uncertainty in biological monitoring: a framework for data collection and analysis to account for multiple sources of sampling bias

Biological monitoring programmes are increasingly relying upon large volumes of citizen-science data to improve the scope and spatial coverage of information, challenging the scientific community to develop design and model-based approaches to improve inference. Recent statistical models in ecology have been developed to accommodate false-negative errors, although current work points to false-positive errors as equally important sources of bias. This is of particular concern for the success of any monitoring programme given that rates as small as 3% could lead to the overestimation of the occurrence of rare events by as much as 50%, and even small false-positive rates can severely bias estimates of occurrence dynamics. We present an integrated, computationally efficient Bayesian hierarchical model to correct for false-positive and false-negative errors in detection/non-detection data. Our model combines independent, auxiliary data sources with field observations to improve the estimation of false-positive rates, when a subset of field observations cannot be validated a posteriori or assumed as perfect. We evaluated the performance of the model across a range of occurrence rates, false-positive and false-negative errors, and quantity of auxiliary data. The model performed well under all simulated scenarios, and we were able to identify critical auxiliary data characteristics which resulted in improved inference. We applied our false-positive model to a large-scale, citizen-science monitoring programme for anurans in the north-eastern United States, using auxiliary data from an experiment designed to estimate false-positive error rates. Not correcting for false-positive rates resulted in biased estimates of occupancy in 4 of the 10 anuran species we analysed, leading to an overestimation of the average number of occupied survey routes by as much as 70%. The framework we present for data collection and analysis is able to efficiently provide reliable inference for occurrence patterns using data from a citizen-science monitoring programme. However, our approach is applicable to data generated by any type of research and monitoring programme, independent of skill level or scale, when effort is placed on obtaining auxiliary information on false-positive rates.

Methods in Ecology and Evolution↗

Adapting visitor use management under a changing climate across the U.S. National Park System

Research shows that climate change is already affecting both resources and visitors in U.S. National Parks. We sought to better understand if and how park staff across the National Park Service are adapting to climatic changes that affect visitor use, as well as barriers and challenges to adaptation and information needs. We conducted semi-structured qualitative interviews with 63 staff from 31 representative national park units across the United States. We qualitatively coded interviews for themes using deductive and inductive coding approaches. Results indicate that park staff are already taking action to adapt to changes that are affecting visitor use, including efforts to increase resiliency of infrastructure and to support the health and safety of visitors (e.g., increased communication, preventative search and rescue, changes to programming). Common barriers and challenges include institutional factors (such as funding, staffing capacity, and shifting priorities), uncertainty about future conditions, and difficulties with prioritizing climate adaptation. Data, tool, and information needs varied, but commonly included social science data such as visitor surveys, and tools to help synthesize and standardize information and help translate science into action. These results provide insights into current actions park staff are taking to adapt to climate change and what resources may be helpful in the future to lower the challenges and barriers to adaptation.

Journal of Environmental Management↗

An overview of the Landsat Data Continuity Mission

The Landsat Data Continuity Mission (LDCM) is the follow-on mission to Landsat 7 and will be the eighth mission in the Landsat series. The mission is in development via an interagency partnership between the National Aeronautics and Space Administration (NASA) and the Department of Interior (DOI) / United States Geological Survey (USGS). The LDCM satellite will carry two earth-observing sensors, the Operational Land Imager (OLI) to collect image data for nine spectral bands in the reflective portion of the spectrum and the Thermal Infrared Sensor (TIRS) to collect coincident image data for two thermal spectral bands. The LDCM ground segment will control the satellite and will receive, process, archive, and distribute the science data collected by the OLI and TIRS instruments. The USGS Earth Resources Observation & Science Center (EROS) will distribute LDCM data products at no cost to requestors. The mission objective is to continues the Landsat program's collection, archive, and distribution of multispectral imagery affording global, synoptic, and repetitive coverage of the Earth's land surfaces at a scale where natural and human-induced changes can be detected, differentiated, characterized, and monitored over time. The LDCM launch readiness date is currently December, 2012.

Conference Paper↗

Science target prioritization framework for remote sensing

Behind the scenes of a remote sensing mission there are complex decision making and planning operations. Streamlining these operations, with a quantitative scientific value framework, aids efficient and optimized science data collection. While there have been previous efforts to quantify the science value for specific science scenarios, our work aims to develop a general framework which can be applied across different scenarios. We describe a pipeline of processes which combines model forecast and observation data, in computational forms, as dictated by the mission objectives set forth by subject matter experts. The framework is described with use cases involving the monitoring of nitrogen dioxide (NO2) concentrations over the Gulf of Mexico and methane concentrations over interior Alaska.

Conference Paper↗

Predicting secretive species distribution using Bayesian networks with and without expert elicitation: A case study incorporating double-blind peer review

1. Species that are secretive, imperilled and consequently data deficient often re-quire conservation action despite limited available information. In such scenarios, Bayesian networks (BNs) offer a versatile and intuitive approach for utilizing various information sources, including literature reviews, community science data sets and expert knowledge. Although it has been suggested that peer review be incorporated during expert elicitations in a BN modelling context, little information exists about how to implement this approach or about how models constructed using this approach perform. 2. We documented a double-blind peer review approach for expert elicitation in a BN modelling context. Further, we compared BN models that were generated by experts who engaged in this peer-review process (PRBNs) to those that were generated by a single expert whose knowledge was supplemented only by a literature review (LRBNs). These comparisons were based on the ability to predict the occurrence (via community science and satellite telemetry data) of a secretive and data deficient species, the King Rail ( Rallus elegans ), throughout a large region. 3. We found that the LRBNs tended to predict King Rail occurrence as well as, or better than, the PRBNs. The LRBNs that we evaluated provided more consistent predictions across our study area. However, preliminary data suggest that the PRBNs may better distinguish between locations of focal and non-focal species within smaller regions. 4. Practical implication. Our framework for utilizing double-blind peer review could serve as a useful guide and have practical implications for incorporating expert knowledge in BN models. Further, our model comparison case study suggests that, in some contexts, a single expert who uses a literature review to inform the creation of BN models may be able to accurately predict the occurrence of a secretive and data-deficient focal species. Taken together, this information could help ecologists decide when a double-blind peer review approach to expert elicitation is necessary and how to implement this approach in a BN modelling context.

Arkansas, Louisiana, Mississippi, Missouri, Tennes↗

Centralized mission planning and scheduling system for the Landsat Data Continuity Mission

Satellites in Low Earth Orbit provide missions with closer range for studying aspects such as geography and topography, but often require efficient utilization of space and ground assets. Optimizing schedules for these satellites amounts to a complex planning puzzle since it requires operators to face issues such as discontinuous ground contacts, limited onboard memory storage, constrained downlink margin, and shared ground antenna resources. To solve this issue for the Landsat Data Continuity Mission (LDCM, Landsat 8), all the scheduling exchanges for science data request, ground/space station contact, and spacecraft maintenance and control will be coordinated through a centralized Mission Planning and Scheduling (MPS) engine, based upon GMV’s scheduling system flexplan9 . The synchronization between all operational functions must be strictly maintained to ensure efficient mission utilization of ground and spacecraft activities while working within the bounds of the space and ground resources, such as Solid State Recorder (SSR) and available antennas. This paper outlines the functionalities that the centralized planning and scheduling system has in its operational control and management of the Landsat 8 spacecraft.

Conference Paper↗

Community for Data Integration 2016 annual report

The Community for Data Integration (CDI) represents a dynamic community of practice focused on advancing science data and information management and integration capabilities across the U.S. Geological Survey and the CDI community. This annual report describes the various presentations, activities, and outcomes of the CDI monthly forums, working groups, virtual training series, and other CDI-sponsored events in fiscal year 2016. The report also describes the objectives and accomplishments of the 13 CDI-funded projects in fiscal year 2016.

Open-File Report↗

USGS Information Technology Strategic Plan: Fiscal Years 2007-2011

Introduction: The acquisition, management, communication, and long-term stewardship of natural science data, information, and knowledge are fundamental mission responsibilities of the U.S. Geological Survey (USGS). USGS scientists collect, maintain, and exchange raw scientific data and interpret and analyze it to produce a wide variety of science-based products. Managers throughout the Bureau access, summarize, and analyze administrative or business-related information to budget, plan, evaluate, and report on programs and projects. Information professionals manage the extensive and growing stores of irreplaceable scientific information and knowledge in numerous databases, archives, libraries, and other digital and nondigital holdings. Information is the primary currency of the USGS, and it flows to scientists, managers, partners, and a wide base of customers, including local, State, and Federal agencies, private sector organizations, and individual citizens. Supporting these information flows is an infrastructure of computer systems, telecommunications equipment, software applications, digital and nondigital data stores and archives, technical expertise, and information policies and procedures. This infrastructure has evolved over many years and consists of tools and technologies acquired or built to address the specific requirements of particular projects or programs. Developed independently, the elements of this infrastructure were typically not designed to facilitate the exchange of data and information across programs or disciplines, to allow for sharing of information resources or expertise, or to be combined into a Bureauwide and broader information infrastructure. The challenge to the Bureau is to wisely and effectively use its information resources to create a more Integrated Information Environment that can reduce costs, enhance the discovery and delivery of scientific products, and improve support for science. This Information Technology Strategic Plan for the USGS outlines key information technology (IT) strategic goals and objectives that will support the Bureau's science mission, while also aligning with the Department of the Interior (DOI) IT Strategic Plan and the DOI Government Performance and Results Act (GPRA) Strategic Plan.

Circular↗

Integrated science strategy for assessing and monitoring water availability and migratory birds for terminal lakes across the Great Basin, United States

Executive Summary In 2022, the U.S. Geological Survey (USGS) established the Saline Lake Ecosystems Integrated Water Availability Assessment (IWAAs) to monitor and assess the hydrology of terminal lakes in the Great Basin and the migratory birds and other wildlife dependent on those habitats. Scientists from across the USGS (with specialties in water quantity, water quality, limnology, avian biology, data science, landscape ecology, and science communication) formed the Saline Lake Ecosystems IWAAs Team. The team has developed this regional strategic science plan to guide data collection and assessment activities at terminal lakes in the Great Basin. The U.S. Congress requested the USGS to establish the Saline Lake Ecosystems IWAAs in response to historically low water levels at terminal lakes and associated wetlands across the Great Basin. Not all Great Basin terminal lakes have high salinity; however, all terminal lakes occur in endorheic, closed, basins with no surface-water outflow. Low lake levels across the Great Basin are the result of increased water use for agriculture and municipalities, drought conditions, and a warming climate. Great Basin terminal lake water extents have decreased by as much as 90 percent over the last 150 years, and terminal lake wetlands have decreased in area by as much as 47 percent since 1984. Lake elevations and wetland areas are primarily supported by freshwater inputs from snowmelt feeding upgradient rivers, streams, and springs. These freshwater inputs have been severely reduced because of continued and increased surface-water diversions and surface-water capture through groundwater pumping for agriculture, mining, and public supply as well as unprecedented drought conditions and warming temperatures related to climate change. Water quality, specifically salinity, is highly variable for terminal lakes of the Great Basin, and this variability is a result of the balance between freshwater inflow and evaporation. Variability of salinity at each of the terminal lakes can be affected by lake morphology, hydrogeologic features of the basin, annual variability in weather patterns, and changes in upgradient water use. Hypersaline terminal lakes provide abundant food resources such as brine shrimp and brine flies that support nesting and migrating birds. The density and composition of invertebrates are closely tied to lake salinity. Increased salinity can exceed the tolerance of invertebrates, severely limiting their biomass. In contrast, decreased salinity can lead to altered invertebrate community composition, reducing the abundance of optimal avian prey resources. Great Basin terminal lake ecosystems, including open-water and adjacent aquatic and terrestrial environments, provide resources necessary to sustain many animal populations throughout the year. Although a variety of taxa use terminal lakes, these ecosystems are of acute importance for the millions of migratory waterbirds (for example, shorebirds, wading birds, and waterfowl) dependent on the network of terminal lakes and their associated wetlands. Migratory birds transiting the Pacific and Central Flyways use Great Basin terminal lake ecosystems throughout the year to feed, nest, and transit between wintering and breeding ranges. As such, successful conservation of birds and their habitats requires coordinated management of water and habitats across the Great Basin network of terminal lakes and wetlands. The linkages between water availability and ecosystem vulnerability of terminal lakes in the Great Basin are not well understood. The vulnerability of terminal lakes is related to the factors driving change and adaptive capacity of the lake ecosystem. Saline lake ecosystems are vulnerable when changes in water quantity affect ecosystem function. Water quantity affects salinity, which affects food webs and habitat; these linkages can be investigated with water-quality and food web monitoring. Water quantity also affects inundated habitat, which can be quantified through remote sensing. It is necessary to quantify hydroclimatic and water use controls on water availability to terminal lakes to assess the response of the ecosystems. Remotely sensed data can provide a broad-scale and long-term synoptic view of terminal lake hydrologic characteristics, but ground observations are required to interpret changes in water quality and ecological functions. Some terminal lake basins have ongoing monitoring and modeling efforts within the Great Basin (for example, Great Salt Lake, Carson River Basin), yet most monitoring locations are hydrologically upgradient and too far away from lake inflows to provide an accurate assessment of hydrological trends for the lake ecosystems. Other terminal lakes have no long-term hydrological monitoring in their respective watersheds (for example, Lake Abert). Ecological data collection in the Great Basin is also insufficient to understand how many birds exist on the landscape, how birds use the mosaic of terminal-lake habitats as an interconnected system, and how Great Basin terminal lakes are linked to the larger continental system of the Pacific and Central Flyways. Across agencies and organizations, tracking bird movement, abundance, and diversity is inconsistent, with some lakes having once- or twice-a-year bird survey efforts and a few locations having more intensive ecological data-gathering efforts (for example, Great Salt Lake, Lake Abert). Bridging hydrological and ecological information gaps will improve understanding of the trends in water supply and water quality, habitat availability and usage, and impacts on vulnerable waterbird species, all of which would be used by managers in coordinated conservation of this unique network of terminal-lake habitats. The terminal lakes of the Great Basin are part of the Basin and Range physiographic province that extends from the Colorado Plateau on the east to the Sierra Nevada on the west, and from the Snake River Plain on the north to the Garlock fault and the Mojave block on the south. The Great Basin is larger than 650,000 square kilometers and encompasses most of the State of Nevada but also extends to western Utah, eastern California, southeastern Idaho, southwestern Wyoming, and southeastern Oregon. The climate is arid to semiarid with a hydrologic regime that is snowmelt dominated, providing as much as 75 percent of total annual runoff for the region. Terminal lakes of the Great Basin occupy the lowest areas of closed (endorheic) drainage basins, such that lake levels and water quality respond rapidly to surface-water inflow. Terminal lakes provide local and regional economic value to the States in the Great Basin, including mineral extraction, aquaculture, public works, and recreational uses. As an example, assessments of Great Salt Lake’s ecological health and economic impact find hemispheric importance for the former and regional importance for the latter. Great Salt Lake creates about 7,000 jobs and $2 billion of economic output per year, most of which would be lost with further declines in lake level. The objectives of this Science Strategy are threefold: (1) to identify how changing water availability affects the quality, diversity, and abundance of habitats supporting continental waterbird populations; (2) to highlight the scientific monitoring and assessment needs of Great Basin terminal lakes; and (3) to support coordinated management and conservation actions to benefit those ecosystems, migratory birds, and other wildlife. There are long-term hydrological, ecological, and societal challenges associated with terminal lakes ecosystems in the Great Basin. This Science Strategy benefits partners by providing a conceptual model, nested at different spatial extents, that identifies key scientific information needs to inform coordinated implementation of management and conservation plans within and among hydrologic basins to address these complex challenges.

California, Idaho, Nevada, Oregon, Utah, Wyoming↗

The water-energy nexus: An earth science perspective

Water availability and use are closely connected with energy development and use. Water cannot be delivered to homes, businesses, and industries without energy, and most forms of energy development require large amounts of water. The United States faces two significant and sometimes competing challenges: to provide sustainable supplies of freshwater for humans and ecosystems and to ensure adequate sources of energy for future generations. This report reviews the complex ways in which water and energy are interconnected and describes the earth science data collection and research that can help the Nation address these important challenges. The earth sciences have been a cornerstone in developing our current understanding of the water-energy nexus. A full understanding of the nexus, however, is limited by uncertainty in our knowledge of fundamental issues, such as the quantity of freshwater that is available, the amount of water that is used in energy development, the effects that emerging energy development technologies have on water quality and quantity, and the amount of energy required to treat and deliver freshwater. Enhanced data collection and research can improve our understanding of these important issues and thereby lay the groundwork for informed resource management. Relevant earth science issues analyzed and discussed herein include freshwater availability; water use; ecosystems health; assessment of saline water resources; assessment of fossil-fuel, uranium, and geothermal resources; subsurface injection of wastewater and carbon dioxide and related induced seismicity; climate change and its effect on water availability and energy production; byproducts and waste streams of energy development; emerging energy-development technologies; and energy for water treatment and delivery.

Circular↗

Sharing our data—An overview of current (2016) USGS policies and practices for publishing data on ScienceBase and an example interactive mapping application

This report provides an overview of current (2016) U.S. Geological Survey policies and practices related to publishing data on ScienceBase, and an example interactive mapping application to display those data. ScienceBase is an integrated data sharing platform managed by the U.S. Geological Survey. This report describes resources that U.S. Geological Survey Scientists can use for writing data management plans, formatting data, and creating metadata, as well as for data and metadata review, uploading data and metadata to ScienceBase, and sharing metadata through the U.S. Geological Survey Science Data Catalog. Because data publishing policies and practices are evolving, scientists should consult the resources cited in this paper for definitive policy information. An example is provided where, using the content of a published ScienceBase data release that is associated with an interpretive product, a simple user interface is constructed to demonstrate how the open source capabilities of the R programming language and environment can interact with the properties and objects of the ScienceBase item and be used to generate interactive maps.

Open-File Report↗

Considerations for incorporating quality control into water quality sampling strategies for the U.S. Geological Survey

This report describes considerations for incorporating routine quality-assessment and quality-control evaluations into U.S. Geological Survey discrete water-sampling programs and projects. U.S. Geological Survey water-data science in 2020 is characterized by robustness, external reproducibility, collaborative large-volume data analysis, and efficient delivery of water-quality data. Confidence in data, or robustness, can be increased by supplementing traditional field-based quality-control data with laboratory quality control (QC) data, such as third-party blind spikes and blind blanks, laboratory blanks, and laboratory-reagent spikes. Laboratory quality-control data can provide additional information about bias and variability, method performance, and false-positive and false-negative rates that are not available from field QC data alone. Reproducibility is supported by means of standardizing metadata and documentation. Collaborative analysis brings together disparate elements of various types of quality-control review and communicates persistent data quality issues for compounds to data users internal and external to the U.S. Geological Survey. Efficient delivery of water-quality data is achieved when quality-control review is accomplished in the same expedited (near real-time) time frame as distribution of environmental results to the public and might be improved with consideration given to data versioning or to a system of alerting data users to data interpretation that might differ from originally published data.

Open-File Report↗

A data management life-cycle

Documented, reliable, and accessible data and information are essential building blocks supporting scientific research and applications that enhance society's knowledge base (fig. 1). The U.S. Geological Survey (USGS), a leading provider of science data, information, and knowledge, is uniquely positioned to integrate science and natural resource information to address societal needs. The USGS Central Energy Resources Team (USGS-CERT) provides critical information and knowledge on the quantity, quality, and distribution of the Nation's and the world's oil, gas, and coal resources. By using a life-cycle model, the USGS-CERT Data Management Project is developing an integrated data management system to (1) promote access to energy data and information, (2) increase data documentation, and (3) streamline product delivery to the public, scientists, and decision makers. The project incorporates web-based technology, data cataloging systems, data processing routines, and metadata documentation tools to improve data access, enhance data consistency, and increase office efficiency

Fact Sheet↗

U.S. Geological Survey 21st-Century science strategy 2020–2030

Today’s Earth system challenges are far more complex and urgent than those that existed in 1879 when the USGS was established. Society’s greatest challenges are directly or indirectly linked to major areas of USGS science. Increased pressures on natural resources continue with consequences for national security, food and water availability, natural disasters, human health, and biodiversity loss. As we look forward 10, 20, and 30 years, our mission will be more important than ever before. A broad but coherent view is required for stewardship of the Nation’s land, water, mineral, energy, and ecosystem resources, which involves complex tradeoffs among multiple, often competing objectives. Increasingly, resource managers and decision makers need “the whole USGS”: integrated multidisciplinary Earth and biological science data, geospatial tools, predictive models, decision-support tools, and the expertise to interpret them. This Science Strategy defines a vision and mission for how we will continue to evolve USGS Science to address these Earth system challenges.

Circular↗

The role of digital cartographic data in the geosciences

The increasing demand of the Nation's natural resource developers for the manipulation, analysis, and display of large quantities of earth-science data has necessitated the use of computers and the building of geoscience information systems. These systems require, in digital form, the spatial data on map products. The basic cartographic data shown on quadrangle maps provide a foundation for the addition of geological and geophysical data. If geoscience information systems are to realize their full potential, large amounts of digital cartographic base data must be available. A major goal of the U.S. Geological Survey is to create, maintain, manage, and distribute a national cartographic and geographic digital database. This unified database will contain numerous categories (hydrography, hypsography, land use, etc.) that, through the use of standardized data-element definitions and formats, can be used easily and flexibly to prepare cartographic products and perform geoscience analysis. ?? 1983.

Computers & Geosciences↗

Integrated distance sampling models for simple point counts

Point counts (PCs) are widely used in biodiversity surveys but, despite numerous advantages, simple PCs suffer from several problems: detectability, and therefore abundance, is unknown; systematic spatiotemporal variation in detectability yields biased inferences, and unknown survey area prevents formal density estimation and scaling-up to the landscape level. We introduce integrated distance sampling (IDS) models that combine distance sampling (DS) with simple PC or detection/nondetection (DND) data to capitalize on the strengths and mitigate the weaknesses of each data type. Key to IDS models is the view of simple PC and DND data as aggregations of latent DS surveys that observe the same underlying density process. This enables the estimation of separate detection functions, along with distinct covariate effects, for all data types. Additional information from repeat or time-removal surveys, or variable survey duration, enables the separate estimation of the availability and perceptibility components of detectability with DS and PC data. IDS models reconcile spatial and temporal mismatches among data sets and solve the above-mentioned problems of simple PC and DND data. To fit IDS models, we provide JAGS code and the new “ IDS() ” function in the R package unmarked . Extant citizen-science data generally lack the information necessary to adjust for detection biases, but IDS models address this shortcoming, thus greatly extending the utility and reach of these data. In addition, they enable formal density estimation in hybrid designs, which efficiently combine DS with distance-free, point-based PC or DND surveys. We believe that IDS models have considerable scope in ecology, management, and monitoring.

Ecology↗

The Moon mineralogy mapper (M 3 ) on Chandrayaan-1

The Moon Mineralogy Mapper (M 3 ) is a NASA-supported guest instrument on ISRO's remote sensing mission to Moon, Chandrayaan-1. The M 3 is an imaging spectrometer that operates from the visible into the near-infrared (0.42-3.0 ??m) where highly diagnostic mineral absorption bands occur. Over the course of the mission M 3 will provide low resolution spectroscopic data for the entire lunar surface at 140 m/pixel (86 spectral channels) to be used as a base-map and high spectral resolution science data (80 m/pixel; 260 spectral channels) for 25-50% of the surface. The detailed mineral assessment of different lunar terrains provided by M 3 is principal information needed for understanding the geologic evolution of the lunar crust and lays the foundation for focused future in-depth exploration of the Moon.

Current Science↗

Global Land Information System (GLIS)

The Global Land Information System (GLIS) is an interactive computer system developed by the U.S. Geological Survey (USGS) for scientists seeking sources of information about the Earth's land surfaces. GLIS contains "metadata," that is, descriptive information about data sets. Through GLIS, scientists can evaluate data sets, determine their availability, and place online requests for products. GLIS is more, however, than a mere list of products. It offers online samples of earth science data that may be ordered through the system.

General Information Product↗