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At least 667 records · Page 37Linked to original sources
USGS2000

The National Biological Information Infrastructure: Coming of age

Coordinated by the US Geological Survey, the National Biological Information Infrastructure (NBII) is a Web-based system that provides increased access to data and information on the nation's biological resources. The NBII can be viewed from a variety of perspectives. This article - an individual case study and not a broad survey with extensive references to the literature - addresses the structure of the NBII related to thematic sections, infrastructure sections and place-based sections, and other topics such as the Integrated Taxonomic Information System (one of our more innovative tools) and the development of our controlled vocabulary.

Online and CDROM Review↗
USGS2000

Generation of data acquisition requests for the ASTER satellite instrument for monitoring a globally distributed target: glaciers

The advanced spaceborne thermal emission and reflection radiometer (ASTER) instrument is scheduled to be launched on the EOS Terra platform in 1999. The Global Land Ice Measurements from Space project has planned to acquire ASTER images of most of the world's land ice annually during the six-year ASTER mission. This article describes the process of creating the data acquisition requests needed to cover approximately 170,000 glacier targets.

IEEE Transactions on Geoscience and Remote Sensing↗
USGS2020

Geoacoustic inversion for a New England mud patch sediment using the silt-suspension theory of marine mud

This article provides an application of the silt-suspension theory to a Bayesian-inference inversion for the geo-acoustic parameters in marine mud. The theory, with consequences that have been developed recently, postulates a suspension of water and clay mineral card-houses that supports moderately dilute concentrations of silt particles. The approach is an example of a physically based model inversion, in which parameters representing physical mud-layer properties are obtained by inversion and used to produce estimates of geoacoustic properties, including their frequency dependence. The acoustic data are from a combustive source signal propagated along a track, located over several meters of fine-grained mud in the New England Mud Patch, to a single hydrophone on a receiver array during the 2017 Seabed Characterization Experiment. Data extracted from a nearby piston core inform the physical modeling, with selections of inversion parameters guided by both sensitivity analyses and bounds from archival and core measurements. Results show the feasibility of this inversion approach. The estimates of mud density and sound speed are close to values obtained independently. The frequency dependence of attenuation is estimated over the full low-frequency source band and has an approximate power exponent of 1.72.

IEEE Journal of Oceanic Engineering↗
USGS2023

Automated soft pressure sensor array-based sea lamprey detection using machine learning

Sea lamprey, a destructive invasive species in the Great Lakes in North America, is among very few fishes that rely on oral suction during migration and spawning. Recently, soft pressure sensors have been proposed to detect the attachment of sea lamprey as part of the monitoring and control effort. However, human decision is still required for the recognition of patterns in the measured signals. In this article, a novel automated soft pressure sensor array-based sea lamprey detection framework is proposed using object detection convolutional neural networks. First, the resistance measurements of the pressure sensor array are converted to mappings of relative change in resistance. These mappings typically show two different types of patterns under lamprey attachment: a high-pressure circular pattern corresponding to the mouth rim compressed against the sensor (“compression” pattern), and a low-pressure blob corresponding to the partial vacuum region of the sucking mouth (“suction” pattern). Three types of object detection algorithms, single-shot detector (SSD), RetinaNet, and YOLOv5s, are applied to the dataset of measurements collected in the presence of sea lamprey attachment, and the comparison of their performance shows that YOLOv5s model achieves the highest mean average precision (mAP) and the fastest inference speed. Furthermore, to improve the accuracy of the prediction model and reduce the false positive (FP) rate due to the sensor’s memory effect, a filter branch with different detection thresholds for the compression and suction patterns, respectively, is added to the original machine-learning algorithm. The trained model is validated and used to automatically detect sea lamprey attachments and locate the suction area on the sensor in real time.

IEEE Sensors Journal↗
USGS2009

Foreword to the issue on remote sensing of regional land use and land cover

This issue showcases some good work from Chinese authors who attended the International Workshop of Earth Observation and Remote Sensing Applications (EORSA), held in Beijing, China, June 30-July 2, 2008. The five articles in this issue focus on remote sensing of regional land use and land cover.

IEEE Journal of Selected Topics in Applied Earth O↗
USGS2021

Applications of bistatic radar to volcano topography – A review of 10 years of TanDEM-X

The TanDEM-X satellite mission has revolutionized DEM generation from spaceborne synthetic aperture radar. In addition to the primary objective of generating a consistent digital elevation model with global coverage and unprecedented accuracy, the mission has acquired time series of topographic data over several volcanoes, providing an excellent opportunity to test the use of this innovative dataset for volcano monitoring and research. In this article, we review the utilization of the single-pass TanDEM-X data for studying various kinds of volcanic activity, such as basaltic lava flows, the formation and destruction of lava domes and related pyroclastic density currents, and subsurface magma withdrawal and intrusion. We then consider the uses of these data for hazard assessment and forecasting. Our goal is to highlight the importance of timely and repeated topographic information in volcanology, and to suggest the development of future spaceborne bistatic synthetic aperture radar satellite missions, such as ESA's Earth Explorer 10 candidate mission, “Harmony.”

IEEE Journal of Selected Topics in Applied Earth O↗
USGS2021

Cloud-native repositories for big scientific data

Scientific data have traditionally been distributed via downloads from data server to local computer. This way of working suffers from limitations as scientific datasets grow toward the petabyte scale. A “cloud-native data repository,” as defined in this article, offers several advantages over traditional data repositories—performance, reliability, cost-effectiveness, collaboration, reproducibility, creativity, downstream impacts, and access and inclusion. These objectives motivate a set of best practices for cloud-native data repositories: analysis-ready data, cloud-optimized (ARCO) formats, and loose coupling with data-proximate computing. The Pangeo Project has developed a prototype implementation of these principles by using open-source scientific Python tools. By providing an ARCO data catalog together with on-demand, scalable distributed computing, Pangeo enables users to process big data at rates exceeding 10 GB/s. Several challenges must be resolved in order to realize cloud computing’s full potential for scientific research, such as organizing funding, training users, and enforcing data privacy requirements.

Computing in Science and Engineering↗
USGS2022

Acquisition of Moon measurements by Earth orbiting sensors for lunar calibration

The reflected light from the Moon can be utilized as a reference for radiometric calibration by employing a model to generate reference values corresponding to the Moon observations made by instruments. Using a calibration target that is outside the atmosphere provides a distinct advantage for space-based instruments; however, the lunar irradiance sensed by satellite instruments naturally changes as the host spacecraft traverses its orbit. This article presents a study of the potential impact on lunar radiometric measurements due to their acquisition from an orbiting platform. A simulation of a Sun-synchronous orbit was coupled to the U.S. Geological Survey (USGS) lunar model to generate predicted irradiances for points along orbit passes through several lunations. These irradiance values exhibit variations tied to the spacecraft motion, arising primarily from changes in the Moon-sensor distance and the phase angle. The two effects are similar in overall magnitude, but their respective contributions depend on the time of month and the orbit. Relative changes in irradiance mostly fall within an envelope of ±0.006% per second, except at the smallest phase angles. These studies enable planning space-based Moon observations to minimize the change in the target irradiance, an important consideration for measurements acquired for radiometric characterization of the Moon.

IEEE Transactions on Geoscience and Remote Sensing↗
USGS2015

Trophic cascades from wolves to grizzly bears or changing abundance of bears and alternate foods?

This is a Forum article commenting on: Ripple, W. J., Beschta, R. L., Fortin, J. K., & Robbins, C. T. (2014) Trophic cascades from wolves to grizzly bears in Yellowstone. Journal of Animal Ecology, 83, 223–233. Comparisons Ripple et al. (2014) used to demonstrate increased fruit availability and consumption by grizzly bears post-wolf reintroduction are flawed and tenuous at best. Importantly, a more parsimonious (than trophic cascades) hypothesis, not sufficiently considered by Ripple et al., exists and is better supported by available data I review.

Journal of Animal Ecology↗
USGS2023

Reanalysis indicates little evidence of reduction in eagle mortality rate by automated curtailment of wind turbines

Unintended consequences of renewable energy development include collision-caused deaths of birds and bats. Energy companies may risk prosecution if protected species are among the casualties. Shutting down turbines during high collision-risk conditions could reduce mortality rates, and several companies are developing systems to identify such conditions. A recent peer-reviewed article published in the Journal of Applied Ecology reported a remarkable ‘82% (75%–89%) reduction in the fatality rate’ of eagles at a wind energy facility due to a device marketed as Identiflight®—remarkable because of the impressive effect size and the extremely high level of precision. We show that reported results stem from four major errors, which, when corrected, give an unremarkable estimate of 50% (−159%, 89%) reduction (or possible increase) in the fatality rate. The errors include the following: (i) Ignoring annual variation . They compare the average number of eagle fatalities over 4 years before activation of Identiflight® to the number in a single year after, ignoring annual variation in fatalities. (ii) Unfounded causal inference . Lack of replication (one treatment year at one site) is ignored, leading to unwarranted causal inference. (iii) Inflated effect size . Effect size is inflated by assuming (without providing evidence) that the difference in fatality relative to the mean at a neighbouring site would be exactly repeated at the treatment site. Furthermore, the observed difference in fatalities at the control site depends strongly on the arbitrarily chosen date distinguishing the ‘Before’ and ‘After’ periods, yielding unreliable results. (iv) Inconsistency of data . It is unclear why 7 of 42 reported eagle fatalities were not included in the data analyzed, potentially further inflating the estimated effect size. Synthesis and applications . The recent claim, published in the Journal of Applied Ecology, that ‘Eagle fatalities are reduced by automated curtailment of wind turbines’ is not supported by the data but stems from errors that led to strongly overstated effect size and precision, and unfounded inference. In theory, automated curtailment has obvious potential for reducing eagle fatalities, but several more years of data at several locations and appropriate statistical analyses will be required to evaluate its effectiveness and to inform management prescriptions involving this technology.

Journal of Applied Ecology↗
USGS2022

The effects of cheatgrass invasion on US Great Basin carbon storage depend on interactions between plant community composition, precipitation seasonality, and soil climate regime

Annual-grass invasions are transforming desert ecosystems in ways that affect ecosystem carbon (C) balance, but previous studies do not agree on the pattern, magnitude and direction of changes. A recent meta-analysis of 41 articles and 386 sites concludes that invasion by annual grasses such as cheatgrass ( Bromus tectorum L) reduces C in biomass across the Great Basin (Nagy et al., 2021). Reanalysis reveals that whether cheatgrass affects biomass C stocks is not generalizable, but rather depends on the considerable variation in climate across the subject sites. Our analysis suggests that accurate Great Basin-scale estimates of cheatgrass effects on C balance are not yet possible. Addition of climate variables to the meta-analysis reveals that cheatgrass invasion (a) reduced C in above-ground biomass in relatively summer-wet sites but not in summer-dry sites, (b) increased surface soil C in sites with intermediate resistance and resilience classifications (R&R) but not in low R&R sites—that is, mesic/aridic soil climates and (c) did not affect deep soil C. Considering that cheatgrass has expanded most in relatively summer-dry sites and mesic/aridic sites, omission of climate factors leads to model overestimates of cheatgrass effects on C when extrapolating to larger areas. Estimates of cheatgrass effects on C would also be improved if the analysis considered that (a) perennial grasslands are a common community state in the Great Basin that have intermediary C relative to annual grasslands and sagebrush stands, that is the omission of perennial grasslands from analysis inflates the baseline C storage of uninvaded Great Basin ecosystems, and( b) cheatgrass does not often exist in stable monocultures and soil carbon can reflect current or recent presence of other species. Synthesis and applications . Invasions often reveal heterogeneity in ecosystem structure and function that is not otherwise evident, and the heterogeneity can influence estimation of the net impacts of the invaders. For cheatgrass and other invaders, we propose that formally accounting for the spatial variability of invasion on ecosystem functions will improve the estimation of their net effect on ecosystem C, and thus improve prospects for adjusting management practices to optimize C sequestration.

western United States↗
USGS2016

Supporting diverse data providers in the open water data initiative: Communicating water data quality and fitness of use

Shared, trusted, timely data are essential elements for the cooperation needed to optimize economic, ecologic, and public safety concerns related to water. The Open Water Data Initiative (OWDI) will provide a fully scalable platform that can support a wide variety of data from many diverse providers. Many of these will be larger, well-established, and trusted agencies with a history of providing well-documented, standardized, and archive-ready products. However, some potential partners may be smaller, distributed, and relatively unknown or untested as data providers. The data these partners will provide are valuable and can be used to fill in many data gaps, but can also be variable in quality or supplied in nonstandardized formats. They may also reflect the smaller partners' variable budgets and missions, be intermittent, or of unknown provenance. A challenge for the OWDI will be to convey the quality and the contextual “fitness” of data from providers other than the most trusted brands. This article reviews past and current methods for documenting data quality. Three case studies are provided that describe processes and pathways for effective data-sharing and publication initiatives. They also illustrate how partners may work together to find a metadata reporting threshold that encourages participation while maintaining high data integrity. And lastly, potential governance is proposed that may assist smaller partners with short- and long-term participation in the OWDI.

Journal of the American Water Resources Associatio↗
USGS2017

Measuring urban water conservation policies: Toward a comprehensive index

This article (1) discusses existing efforts to measure water conservation policies (WCPs) in the United States (U.S.); (2) suggests general methodological guidelines for creating robust water conservation indices (WCIs); (3) presents a comprehensive template for coding WCPs; (4) introduces a summary index, the Vanderbilt Water Conservation Index (VWCI), which is derived from 79 WCP observations for 197 cities for the year 2015; and (5) compares the VWCI to WCP data extracted from the 2010 American Water Works Association (AWWA) Water and Wastewater Rates survey. Existing approaches to measuring urban WCPs in U.S. cities are limited because they consider only a portion of WCPs or they are restricted geographically. The VWCI consists of a more comprehensive set of 79 observations classified as residential, commercial/industrial, billing structure, drought plan, or general. Our comparison of the VWCI and AWWA survey responses indicate reasonable agreement ( ρ = 0.76) between the two WCIs for 98 cities where the data overlap. The correlation suggests the AWWA survey responses can provide fairly robust longitudinal WCP information, but we argue the measurement of WCPs is still in its infancy, and our approach suggests strategies for improving existing methods.

Journal of the American Water Resources Associatio↗
USGS2017

A comparison of three federal datasets for thermoelectric water withdrawals in the United States for 2010

Historically, thermoelectric water withdrawal has been estimated by the Energy Information Administration (EIA) and the U.S. Geological Survey's (USGS) water-use compilations. Recently, the USGS developed models for estimating withdrawal at thermoelectric plants to provide estimates independent from plant operator-reported withdrawal data. This article compares three federal datasets of thermoelectric withdrawals for the United States in 2010: one based on the USGS water-use compilation, another based on EIA data, and the third based on USGS model-estimated data. The withdrawal data varied widely. Many plants had three different withdrawal values, and for approximately 54% of the plants the largest withdrawal value was twice the smallest, or larger. The causes of discrepancies among withdrawal estimates included definitional differences, definitional noise, and various nondefinitional causes. The uncertainty in national totals can be characterized by the range among the three datasets, from 5,640 m 3 /s (129 billion gallons per day [bgd]) to 6,954 m 3 /s (158 bgd), or by the aggregate difference between the smallest and largest values at each plant, from 4,014 m 3 /s (92 bgd) to 8,590 m 3 /s (196 bgd). When used to assess the accuracy of reported values, the USGS model estimates identify plants that need to be reviewed.

Journal of the American Water Resources Associatio↗
USGS2023

Water quality impacts of climate change, land use, and population growth in the Chesapeake Bay watershed

The 2010 Chesapeake Bay Total Maximum Daily Load was established for the water quality and ecological restoration of the Chesapeake Bay. In 2017, the latest science, data, and modeling tools were used to develop revised Watershed Implementation Plans (WIPs). In this article, we examine the vulnerability of the Chesapeake Bay watershed to the combined pressures of climate change and growth in population, agricultural intensity, and economic activity for the 60-year period 1995–2055. The results will be used to revise WIPs, as needed, to account for expected increases in loads. Assessing changes relative to 1995 for the years 2025, 2035, 2045, and 2055, mean annual precipitation increases of 3.11%, 4.21%, 5.34%, and 6.91%, respectively, air temperature increases of 1.12, 1.45, 1.84, and 2.12°C, respectively, and potential evapotranspiration increases of 3.36%, 4.43%, 5.54%, and 6.35%, respectively, are projected. Population in the watershed is expected to grow by 3.5 million between 2025 and 2055. Watershed model results show incremental increases in streamflow (2.3%–6.2%), nitrogen (2.6%–10.8%), phosphorus (4.5%–26.7%), and sediment (3.8%–18.8%) loads to the tidal Bay due to climate change. Growth in population, agricultural intensity, development, and economic activity resulted in relatively smaller increases in loads compared to climate change.

Chesapeake Bay watershed↗
USGS2017

eDNAoccupancy: An R package for multi-scale occupancy modeling of environmental DNA data

In this article we describe eDNAoccupancy, an R package for fitting Bayesian, multi-scale occupancy models. These models are appropriate for occupancy surveys that include three, nested levels of sampling: primary sample units within a study area, secondary sample units collected from each primary unit, and replicates of each secondary sample unit. This design is commonly used in occupancy surveys of environmental DNA (eDNA). eDNAoccupancy allows users to specify and fit multi-scale occupancy models with or without covariates, to estimate posterior summaries of occurrence and detection probabilities, and to compare different models using Bayesian model-selection criteria. We illustrate these features by analyzing two published data sets: eDNA surveys of a fungal pathogen of amphibians and eDNA surveys of an endangered fish species.

Molecular Ecology Resources↗
USGS2020

The use of Bayesian priors in Ecology: The good, the bad and the not great

Bayesian data analysis (BDA) is a powerful tool for making inference from ecological data, but its full potential has yet to be realized. Despite a generally positive trajectory in research surrounding model development and assessment, far too little attention has been given to prior specification. Default priors, a sub‐class of non‐informative prior distributions that are often chosen without critical thought or evaluation, are commonly used in practice. We believe the fear of being too ‘subjective’ has prevented many researchers from using any prior information in their analyses despite the fact that defending prior choice (informative or not) promotes good statistical practice. In this commentary, we provide an overview of how BDA is currently being used in a random sample of articles, discuss implications for inference if current bad practices continue, and highlight sub‐fields where knowledge about the system has improved inference and promoted good statistical practices through the careful and justified use of informative priors. We hope to inspire a renewed discussion about the use of Bayesian priors in Ecology with particular attention paid to specification and justification. We also emphasize that all priors are the result of a subjective choice, and should be discussed in that way.

Methods in Ecology and Evolution↗
USGS2026

A systematic review of avian influenza virus transmission models: Gaps and opportunities

Highly pathogenic avian influenza virus (HPAIV) increasingly threatens wild birds, poultry, non-human mammals and humans, yet gaps and opportunities in avian influenza virus (AIV) transmission modelling have not been comprehensively synthesized. We reviewed 182 articles published through 2025, categorized dimensions, including modelling approaches, data, host types, biological levels, spatial scales, temporal scales and model objectives, examined associations among these dimensions, and synthesized author-stated limitations and recommendations. Statistical and mechanistic models dominated. Model data centred on population dynamics and demography, disease surveillance, host epidemiology and competence, meteorology and land use and land cover. Most studies focused on poultry or wild birds at regional spatial scales, seasonal/annual and multi-year temporal scales, population or multi-population levels, and were retrospective. Machine learning and decision- making models were less common. Immunity, behaviour and life history, community composition, morphology, viral genetics and viral persistence received less attention. Non-human mammals, individual and community biological levels, local and broader spatial scales, daily temporal scales and prospective modelling were also less frequently modelled. The authors frequently reported limitations related to data availability, surveillance sampling and reporting bias, and model simplification, while commonly recommending improved data quality and greater model complexity and realism.

Methods in Ecology and Evolution↗