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At least 1,549 records · Page 86Linked to original sources
USGS2000

The United States Board on Geographic Names: Standardization or regulation?

The United States Board on Geographic Names was created in 1890 to standardize the use of geographic names on federal maps and documents, and was established in its present form in 1947 by public law. The Board is responsible for geographic name usage and application throughout the federal government and its members must approve a name change or new name before it can be applied to federal maps and publications. To accomplish its mission, the Board has developed principles, policies, and procedures for use in the standardization process. The Board is also responsible legally for the promulgation of standardized names, whether or not these names have ever been controversial, and today this is accomplished by the universal availability of electronic databases for domestic and foreign names. This paper examines the development of Board policies and the implementation of these policies to achieve standardization with a view to relating these policies and activities to questions of standardization or regulation.

Names↗
USGS2015

Variations in community exposure to lahar hazards from multiple volcanoes in Washington State (USA)

Understanding how communities are vulnerable to lahar hazards provides critical input for effective design and implementation of volcano hazard preparedness and mitigation strategies. Past vulnerability assessments have focused largely on hazards posed by a single volcano, even though communities and officials in many parts of the world must plan for and contend with hazards associated with multiple volcanoes. To better understand community vulnerability in regions with multiple volcanic threats, we characterize and compare variations in community exposure to lahar hazards associated with five active volcanoes in Washington State, USA—Mount Baker, Glacier Peak, Mount Rainier, Mount Adams and Mount St. Helens—each having the potential to generate catastrophic lahars that could strike communities tens of kilometers downstream. We use geospatial datasets that represent various population indicators (e.g., land cover, residents, employees, tourists) along with mapped lahar-hazard boundaries at each volcano to determine the distributions of populations within communities that occupy lahar-prone areas. We estimate that Washington lahar-hazard zones collectively contain 191,555 residents, 108,719 employees, 433 public venues that attract visitors, and 354 dependent-care facilities that house individuals that will need assistance to evacuate. We find that population exposure varies considerably across the State both in type (e.g., residential, tourist, employee) and distribution of people (e.g., urban to rural). We develop composite lahar-exposure indices to identify communities most at-risk and communities throughout the State who share common issues of vulnerability to lahar-hazards. We find that although lahars are a regional hazard that will impact communities in different ways there are commonalities in community exposure across multiple volcanoes. Results will aid emergency managers, local officials, and the public in educating at-risk populations and developing preparedness, mitigation, and recovery plans within and across communities.

Washington↗
USGS2022

The global environmental agenda urgently needs a semantic web of knowledge

Progress in key social-ecological challenges of the global environmental agenda (e.g., climate change, biodiversity conservation, Sustainable Development Goals) is hampered by a lack of integration and synthesis of existing scientific evidence. Facing a fast-increasing volume of data, information remains compartmentalized to pre-defined scales and fields, rarely building its way up to collective knowledge. Today's distributed corpus of human intelligence, including the scientific publication system, cannot be exploited with the efficiency needed to meet current evidence synthesis challenges; computer-based intelligence could assist this task. Artificial Intelligence (AI)-based approaches underlain by semantics and machine reasoning offer a constructive way forward, but depend on greater understanding of these technologies by the science and policy communities and coordination of their use. By labelling web-based scientific information to become readable by both humans and computers, machines can search, organize, reuse, combine and synthesize information quickly and in novel ways. Modern open science infrastructure—i.e., public data and model repositories—is a useful starting point, but without shared semantics and common standards for machine actionable data and models, our collective ability to build, grow, and share a collective knowledge base will remain limited. The application of semantic and machine reasoning technologies by a broad community of scientists and decision makers will favour open synthesis to contribute and reuse knowledge and apply it toward decision making.

Environmental Evidence↗
USGS2024

A benchmark for computational analysis of animal behavior, using animal-borne tags

Background Animal-borne sensors (‘bio-loggers’) can record a suite of kinematic and environmental data, which are used to elucidate animal ecophysiology and improve conservation efforts. Machine learning techniques are used for interpreting the large amounts of data recorded by bio-loggers, but there exists no common framework for comparing the different machine learning techniques in this domain. This makes it difficult to, for example, identify patterns in what works well for machine learning-based analysis of bio-logger data. It also makes it difficult to evaluate the effectiveness of novel methods developed by the machine learning community. Methods To address this, we present the Bio-logger Ethogram Benchmark (BEBE), a collection of datasets with behavioral annotations, as well as a modeling task and evaluation metrics. BEBE is to date the largest, most taxonomically diverse, publicly available benchmark of this type, and includes 1654 h of data collected from 149 individuals across nine taxa. Using BEBE, we compare the performance of deep and classical machine learning methods for identifying animal behaviors based on bio-logger data. As an example usage of BEBE, we test an approach based on self-supervised learning. To apply this approach to animal behavior classification, we adapt a deep neural network pre-trained with 700,000 h of data collected from human wrist-worn accelerometers. Results We find that deep neural networks out-perform the classical machine learning methods we tested across all nine datasets in BEBE. We additionally find that the approach based on self-supervised learning out-performs the alternatives we tested, especially in settings when there is a low amount of training data available. Conclusions In light of these results, we are able to make concrete suggestions for designing studies that rely on machine learning to infer behavior from bio-logger data. Therefore, we expect that BEBE will be useful for making similar suggestions in the future, as additional hypotheses about machine learning techniques are tested. Datasets, models, and evaluation code are made publicly available at https://github.com/earthspecies/BEBE , to enable community use of BEBE.

Movement Ecology↗
USGS2006

High-resolution seismic-reflection imaging 25 years of change in I-70 sinkhole, Russell County, Kansas

Time-lapse seismic reflection imaging improved our understanding of the consistent, gradual surface subsidence ongoing at two sinkholes in the Gorham Oilfield discovered beneath a stretch of Interstate Highway 70 through Russell and Ellis Counties in Kansas in 1966. With subsidence occurring at a rate of around 10 cm per year since discovery, monitoring has been beneficial to ensure public safety and optimize maintenance. A miniSOSIE reflection survey conducted in 1980 delineated the affected subsurface and successfully predicted development of a third sinkhole at this site. In 2004 and 2005 a high-resolution vibroseis survey was completed to ascertain current conditions of the subsurface, rate and pattern of growth since 1980, and potential for continued growth. With time and improved understanding of the salt dissolution affected subsurface in this area it appears that these features represent little risk to the public from catastrophic failure. However, from an operational perspective the Kansas Department of Transportation should expect continued subsidence, with future increases in surface area likely at a slightly reduced vertical rate. Seismic characteristics appear empirically consistent with gradual earth material compaction/settling. ?? 2005 Society of Exploration Geophysicists.

SEG Technical Program Expanded Abstracts↗
USGS2019

Increases in life-safety risks to building occupants from induced earthquakes in the central United States

Earthquake occurrence rates in some parts of the central United States have been elevated for a number of years; this increase has been widely attributed to deep wastewater injection associated with oil and gas activities. This induced seismicity has caused damage to buildings and infrastructure and substantial public concern. In March 2016, the U.S. Geological Survey (USGS) published its first earthquake ground motion hazard model that accounts for the elevated seismicity, producing a one-year forecast encompassing both induced and natural earthquakes. To assess the potential impacts of the elevated seismicity on buildings and the public, this paper quantifies forecasted risks of a) building collapse and b) falling of nonstructural building components, by combining the 2016 USGS hazard model with fragility curves for generic modern code-compliant buildings. The assessment shows significant increases in both types of risk compared to that due to non-induced earthquakes alone; the magnitudes of the increases vary from a few times to more than a 100 times, depending on location, building period (which is correlated to building height), alternatives for the hazard model, and the type of risk of interest. For exploratory purposes only, we also estimate revised values of the risk-targeted ground motion that are currently used for designing buildings.

Texas, Oklahoma↗
USGS2008

ShakeCast: Automating and improving the use of shakemap for post-earthquake deeision-making and response

When a potentially damaging earthquake occurs, utility and other lifeline managers, emergency responders, and other critical users have an urgent need for information about the impact on their particular facilities so they can make appropriate decisions and take quick actions to ensure safety and restore system functionality. ShakeMap, a tool used to portray the extent of potentially damaging shaking following an earthquake, on its own can be useful for emergency response, loss estimation, and public information. However, to take full advantage of the potential of ShakeMap, we introduce ShakeCast. ShakeCast facilitates the complicated assessment of potential damage to a user's widely distributed facilities by comparing the complex shaking distribution with the potentially highly variable damageability of their inventory to provide a simple, hierarchical list and maps of structures or facilities most likely impacted. ShakeCast is a freely available, post-earthquake situational awareness application that automatically retrieves earthquake shaking data from ShakeMap, compares intensity measures against users' facilities, sends notifications of potential damage to responsible parties, and generates facility damage maps and other Web-based products for both public and private emergency managers and responders. ?? 2008, Earthquake Engineering Research Institute.

Earthquake Spectra↗
USGS2020

Sustainable fisheries management: Pacific salmon

What has happened to the salmon resource in the Pacific Northwest? Who is responsible and what can be done to reverse the decline in salmon populations? The responsibly falls on everyone involved - fishermen, resource managers and concerned citizens alike - to take the steps necessary to ensure that salmon populations make a full recovery. This collection of papers examines the state of the salmon fisheries in the Pacific Northwest. They cover existing methods and supply model approaches for alternative solutions. The editors stress the importance of input from and cooperation with all parties involved to create a viable solution. Grass roots education and participation is the key to public support - and ultimately the success - of whatever management solutions are developed. A unique and valuable scientific publication, Sustainable Fisheries Management: Pacific Salmon clearly articulates the current state of the Pacific salmon resource, describes the key features of its management, and provides important guidance on how we can make the transition towards sustainable fisheries. The solutions presented in this book provide the basis of a strategy for sustainable fisheries, requiring society and governmental agencies to establish a shared vision, common policies, and a process for collaborative management.

Book↗
USGS2011

Methodology for prediction of rip currents using a three-dimensional numerical, coupled, wave current model

Rip current currents constitute one of the most common hazards in the nearshore that threaten the lives of the unaware public that makes recreational use of the coastal zone. Society responds to this danger through a number of measures that include: (a) the deployment of trained lifeguards; (b) public education related to the hidden hazards of the nearshore; and (c) establishment of warning systems.

Conference Paper↗
USGS2007

Impacts of waste from concentrated animal feeding operations on water quality

Waste from agricultural livestock operations has been a long-standing concern with respect to contamination of water resources, particularly in terms of nutrient pollution. However, the recent growth of concentrated animal feeding operations (CAFOs) presents a greater risk to water quality because of both the increased volume of waste and to contaminants that may be present (e.g., antibiotics and other veterinary drugs) that may have both environmental and public health importance. Based on available data, generally accepted livestock waste management practices do not adequately or effectively protect water resources from contamination with excessive nutrients, microbial pathogens, and pharmaceuticals present in the waste. Impacts on surface water sources and wildlife have been documented in many agricultural areas in the United States. Potential impacts on human and environmental health from long-term inadvertent exposure to water contaminated with pharmaceuticals and other compounds are a growing public concern. This workgroup, which is part of the Conference on Environmental Health Impacts of Concentrated Animal Feeding Operations: Anticipating Hazards-Searching for Solutions, identified needs for rigorous ecosystem monitoring in the vicinity of CAFOs and for improved characterization of major toxicants affecting the environment and human health. Last, there is a need to promote and enforce best practices to minimize inputs of nutrients and toxicants from CAFOs into freshwater and marine ecosystems.

Environmental Health Perspectives↗
USGS2000

Schaben field, Kansas: Improving performance in a Mississippian shallow-shelf carbonate

Schaben field (Kansas), located along the northeastern shelf of the Hugoton embayment, produces from Mississippian carbonates in erosional highs immediately beneath a regional unconformity. Production comes from depths of around 4400 ft (1342 m) in partially dolomitized shelf deposits. A detailed reservoir characterization/simulation study, recently performed as part of a Department of Energy Reservoir Class Oil Field Demonstration Project, has led to important revision in explanations for observed patterns of production. Cores recovered from three new data wells identify three main facies: Spicule-rich wackestone-packstone, echinoderm wackestone/packstone/grainstone, and dolomitic mudstone-wackestone. Reservoir quality is highest in spicule-rich wackestone/packstones but is subject to a very high degree of vertical heterogeneity due to facies interbedding, silification, and variable natural fracturing. The oil reservoir is underlain by an active aquifer, which helps maintain reservoir pressure but supports significant water production. Reservoir simulation, using public-domain, PC-based software, suggests that infill drilling is an efficient approach to enhanced recovery. Recent drilling directed by simulation results has shown considerable success in improving field production rates. Results from the Schaben field demonstration project are likely to have wide application for independent oil and exploration companies in western Kansas.Schaben field (Kansas), located along the northeastern shelf of the Hugoton embayment, produces from Mississippian carbonates in erosional highs immediately beneath a regional unconformity. Production comes from depths of around 4400 ft (1342 m) in partially dolomitized shelf deposits. A detailed reservoir characterization/simulation study, recently performed as part of a Department of Energy Reservoir Class Oil Field Demonstration Project, has led to important revision in explanations for observed patterns of production. Cores recovered from three new data wells identify three main facies: spicule-rich wackestone-packstone, echinoderm wackestone/packstone/grainstone, and dolomitic mudstone-wackestone. Reservoir quality is highest in spicule-rich wackestone/packstones but is subject to a very high degree of vertical heterogeneity due to facies interbedding, silification, and variable natural fracturing. The oil reservoir is underlain by an active aquifer, which helps maintain reservoir pressure but supports significant water production. Reservoir simulation, using public-domain, PC-based software, suggests that infill drilling is an efficient approach to enhanced recovery. Recent drilling directed by simulation results has shown considerable success in improving field production rates. Results from the Schaben field demonstration project are likely to have wide application for independent oil and exploration companies in western Kansas.

Kansas↗
USGS2021

Synergistic interventions to control COVID-19: Mass testing and isolation mitigates reliance on distancing

Stay-at-home orders and shutdowns of non-essential businesses are powerful, but socially costly, tools to control the pandemic spread of SARS-CoV-2. Mass testing strategies, which rely on widely administered frequent and rapid diagnostics to identify and isolate infected individuals, could be a potentially less disruptive management strategy, particularly where vaccine access is limited. In this paper, we assess the extent to which mass testing and isolation strategies can reduce reliance on socially costly non-pharmaceutical interventions, such as distancing and shutdowns. We develop a multi-compartmental model of SARS-CoV-2 transmission incorporating both preventative non-pharmaceutical interventions (NPIs) and testing and isolation to evaluate their combined effect on public health outcomes. Our model is designed to be a policy-guiding tool that captures important realities of the testing system, including constraints on test administration and non-random testing allocation. We show how strategic changes in the characteristics of the testing system, including test administration, test delays, and test sensitivity, can reduce reliance on preventative NPIs without compromising public health outcomes in the future. The lowest NPI levels are possible only when many tests are administered and test delays are short, given limited immunity in the population. Reducing reliance on NPIs is highly dependent on the ability of a testing program to identify and isolate unreported, asymptomatic infections. Changes in NPIs, including the intensity of lockdowns and stay at home orders, should be coordinated with increases in testing to ensure epidemic control; otherwise small additional lifting of these NPIs can lead to dramatic increases in infections, hospitalizations and deaths. Importantly, our results can be used to guide ramp-up of testing capacity in outbreak settings, allow for the flexible design of combined interventions based on social context, and inform future cost-benefit analyses to identify efficient pandemic management strategies.

PLOS Computational Biology↗
USGS2013

Representation of ecological systems within the protected areas network of the continental United States

If conservation of biodiversity is the goal, then the protected areas network of the continental US may be one of our best conservation tools for safeguarding ecological systems (i.e., vegetation communities). We evaluated representation of ecological systems in the current protected areas network and found insufficient representation at three vegetation community levels within lower elevations and moderate to high productivity soils. We used national-level data for ecological systems and a protected areas database to explore alternative ways we might be able to increase representation of ecological systems within the continental US. By following one or more of these alternatives it may be possible to increase the representation of ecological systems in the protected areas network both quantitatively (from 10% up to 39%) and geographically and come closer to meeting the suggested Convention on Biological Diversity target of 17% for terrestrial areas. We used the Landscape Conservation Cooperative framework for regional analysis and found that increased conservation on some private and public lands may be important to the conservation of ecological systems in Western US, while increased public-private partnerships may be important in the conservation of ecological systems in Eastern US. We have not assessed the pros and cons of following the national or regional alternatives, but rather present them as possibilities that may be considered and evaluated as decisions are made to increase the representation of ecological systems in the protected areas network across their range of ecological, geographical, and geophysical occurrence in the continental US into the future.

PLoS ONE↗
USGS2016

Twitter predicts citation rates of ecological research

The relationship between traditional metrics of research impact (e.g., number of citations) and alternative metrics ( altmetrics ) such as Twitter activity are of great interest, but remain imprecisely quantified. We used generalized linear mixed modeling to estimate the relative effects of Twitter activity, journal impact factor, and time since publication on Web of Science citation rates of 1,599 primary research articles from 20 ecology journals published from 2012–2014. We found a strong positive relationship between Twitter activity (i.e., the number of unique tweets about an article) and number of citations. Twitter activity was a more important predictor of citation rates than 5-year journal impact factor. Moreover, Twitter activity was not driven by journal impact factor; the ‘highest-impact’ journals were not necessarily the most discussed online. The effect of Twitter activity was only about a fifth as strong as time since publication; accounting for this confounding factor was critical for estimating the true effects of Twitter use. Articles in impactful journals can become heavily cited, but articles in journals with lower impact factors can generate considerable Twitter activity and also become heavily cited. Authors may benefit from establishing a strong social media presence, but should not expect research to become highly cited solely through social media promotion. Our research demonstrates that altmetrics and traditional metrics can be closely related, but not identical. We suggest that both altmetrics and traditional citation rates can be useful metrics of research impact.

PLoS ONE↗
USGS2018

Phytoforensics: Trees as bioindicators of potential indoor exposure via vapor intrusion

Human exposure to volatile organic compounds (VOCs) via vapor intrusion (VI) is an emerging public health concern with notable detrimental impacts on public health. Phytoforensics, plant sampling to semi-quantitatively delineate subsurface contamination, provides a potential non-invasive screening approach to detect VI potential, and plant sampling is effective and also time- and cost-efficient. Existing VI assessment methods are time- and resource-intensive, invasive, and require access into residential and commercial buildings to drill holes through basement slabs to install sampling ports or require substantial equipment to install groundwater or soil vapor sampling outside the home. Tree-core samples collected in 2 days at the PCE Southeast Contamination Site in York, Nebraska were analyzed for tetrachloroethene (PCE) and results demonstrated positive correlations with groundwater, soil, soil-gas, sub-slab, and indoor-air samples collected over a 2-year period. Because tree-core samples were not collocated with other samples, interpolated surfaces of PCE concentrations were estimated so that comparisons could be made between pairs of data. Results indicate moderate to high correlation with average indoor-air and sub-slab PCE concentrations over long periods of time (months to years) to an interpolated tree-core PCE concentration surface, with Spearman’s correlation coefficients (ρ) ranging from 0.31 to 0.53 that are comparable to the pairwise correlation between sub-slab and indoor-air PCE concentrations (ρ = 0.55, n = 89). Strong correlations between soil-gas, sub-slab, and indoor-air PCE concentrations and an interpolated tree-core PCE concentration surface indicate that trees are valid indicators of potential VI and human exposure to subsurface environment pollutants. The rapid and non-invasive nature of tree sampling are notable advantages: even with less than 60 trees in the vicinity of the source area, roughly 12 hours of tree-core sampling with minimal equipment at the PCE Southeast Contamination Site was sufficient to delineate vapor intrusion potential in the study area and offered comparable delineation to traditional sub-slab sampling performed at 140 properties over a period of approximately 2 years.

Nebraska↗
USGS2018

Communicating information on nature-related topics: Preferred information channels and trust in sources

How information is communicated influences the public’s environmental perceptions and behaviors. Information channels and sources both play an important role in the dissemination of information. Trust in a source is often used as a proxy for whether a particular piece of information is credible. To determine preferences for information channels and trust in various sources for information on nature-related topics, a mail-out survey was sent to randomly selected U.S. addresses ( n = 1,030). Diverse groups of people may have differing communication preferences. Therefore, we explored differences in channel preferences and trust by demographics using regression models. Overall, the most preferred channels were personal experience, reading online content, and watching visual media online. The most trusted sources were science organizations, universities, and friends/family. Channel preferences varied the most by education level and age, while source trust was most influenced by education, race, age, and size of current residence (rural-urban). The influence of demographics varied depending on the individual channel and source, with some groups preferring certain channels or sources but not others. Results are useful to consider when disseminating information on nature-related topics to a general public audience. More broadly, results also suggest spreading information using different channels and sources depending on the specific audience being targeted.

PLoS ONE↗
USGS2020

Possibility for reverse zoonotic transmission of SARS-CoV-2 to free-ranging wildlife: A case study of bats

The COVID-19 pandemic highlights the substantial public health, economic, and societal consequences of virus spillover from a wildlife reservoir. Widespread human transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) also presents a new set of challenges when considering viral spillover from people to naïve wildlife and other animal populations. The establishment of new wildlife reservoirs for SARS-CoV-2 would further complicate public health control measures and could lead to wildlife health and conservation impacts. Given the likely bat origin of SARS-CoV-2 and related beta-coronaviruses (β-CoVs), free-ranging bats are a key group of concern for spillover from humans back to wildlife. Here, we review the diversity and natural host range of β-CoVs in bats and examine the risk of humans inadvertently infecting free-ranging bats with SARS-CoV-2. Our review of the global distribution and host range of β-CoV evolutionary lineages suggests that 40+ species of temperate-zone North American bats could be immunologically naïve and susceptible to infection by SARS-CoV-2. We highlight an urgent need to proactively connect the wellbeing of human and wildlife health during the current pandemic and to implement new tools to continue wildlife research while avoiding potentially severe health and conservation impacts of SARS-CoV-2 "spilling back" into free-ranging bat populations.

PLoS Pathogens↗
USGS2026

Evaluating U.S. Geological Survey 3D Elevation Program LiDAR data as a source for building height

Accurate building height information is used for numerous urban applications, including infrastructure modeling, disaster risk assessment, and energy demand estimation. The U.S. Geological Survey collects airborne lidar data to support the three-dimensional elevation program (3DEP). The high point density and vertical accuracy of the lidar point clouds are optimal for 3D mapping. Few studies have systematically evaluated building height extraction from 3DEP lidar point clouds in urban areas. This study assesses the accuracy and consistency of building height estimates from two publicly available data sets by comparing them to the 3DEP lidar data. The public building height data sets are USA Structures and Microsoft Global Building Footprints (GBF), and they are evaluated across two contrasting urban sites. Building heights from USA Structures are also lidar-derived, whereas GBF estimates are based on stereo matching of optical imagery. Building heights from 3DEP were extracted by classifying lidar points using a deep learning model, isolating roof and ground returns, and computing the height as the median elevation difference between the roof and surrounding ground points. For both sites, 3DEP lidar-derived heights show strong agreement with USA Structures (R 2 = 0.87 and 0.86; MAE = 1.8 and 2.2 m), confirming the internal consistency and reliability of lidar-derived measurements. In contrast, comparisons with GBF height estimates reveal significantly lower correlations (R 2 = 0.54 and 0.60; MAE = 2.5 and 3.1 m), highlighting the limitations of imagery-based height reconstruction, particularly in dense or heterogeneous urban environments. These findings indicate that lidar can be used as an accurate source for vertical structure characterization and underscore the benefits of improved integration and bias correction when using imagery-derived building heights. The results provide support for hybrid approaches that combine the broad spatial coverage of optical data sets with the accuracy of lidar for scalable 3D urban mapping.

Colorado, Texas↗