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At least 217 records · Page 12Linked to original sources
USGS2023

Obtaining and applying public data for training students in technical statistical writing: Case studies with data from U.S. Geological Survey and general ecological literature

Effective undergraduate statistical education requires training using real-world data. Textbook datasets seldom match the complexities and messiness of real-world data and finding these datasets can be challenging for educators. Consulting and industrial datasets often have nondisclosure agreements. Academic datasets often require subject area expertise beyond those of a general education or lack connections to real-world applications. Many governments, including the United States, now require the release of data from projects they directly complete or fund though grants and contracts. We show how statistical educators may find datasets and incorporate them into courses. Specifically, we use two examples from the U.S. Geological Survey (USGS) and one example from the ecology literature. We demonstrate the use of these datasets in an upper-level analysis of variance (ANOVA) class. In addition to describing how we found the datasets, we describe how to include them into course work and the course’s student assessments. We have used these datasets over multiple semesters and included student feedback from these courses. Although our examples focus on an ANOVA class, the general methods for finding data shared here could be used for statistical classes ranging from high school to graduate education. Supplementary materials for this article are available online.

Journal of Statistics and Data Science Education↗
USGS2026

Evaluating machine learning approaches to identify and predict oil and gas produced water lithium concentrations

Recently, the demand for battery-grade lithium has substantially increased, largely due to electrification of the transportation sector. The search for new lithium sources has turned to produced waters (frequently brines), a large-volume wastewater by-product of oil and gas extraction. Geochemical analysis indicates the presence of varying concentrations of lithium from produced water samples collected across the United States and represented in the U.S. Geological Survey’s National Produced Water Geochemical Database, as well as mixtures of Marcellus Shale produced water included in the Pennsylvania Department of Environmental Protection’s Oil and Gas Well Waste Reports. We first examined whether the geochemical signature of the lithium-bearing produced waters is sufficiently distinct so that machine learning (ML) can be used to correctly classify samples to the formation of origin. The produced water sample data used to assess classification accuracy were from the Marcellus Shale, Utica Shale and Point Pleasant Formation (Utica), and Smackover Formation oil and gas wells. Further, we evaluated the potential for ML to accurately classify Marcellus Shale produced water spatially (i.e., northeast versus southwest Pennsylvania). We then investigated whether ML algorithms applied to a suite of geochemical concentration data (i.e. Ba, Br, Cl, K, Mg, Sr) may be used to predict the lithium concentration of an unknown sample. Finally, we applied an estimated economic lithium grade cutoff of 150 milligrams per liter (mg/l) and assessed the utility of ML to predict whether a produced water sample would fall above or below the grade cutoff based on the suite of geochemical parameters. Four machine learning algorithms—Random Forest (RF), Gradient Boosting Trees (GBT), Extreme Boosting (XGBoost), and Deep Neural Networks (DNN) were assessed. This study successfully demonstrates that all four machine learning methods can precisely and accurately estimate lithium concentrations and geologic formation classification. The products of this study contribute to the growing body of knowledge aimed at expanding the lithium resource base within the United States.

Alabama, Arkansas, Florida, Georgia, Louisiana, Mi↗
USGS2025

The National Fish Habitat Partnership – A unique path to conserving fish habitat

The National Fish Habitat Partnership (NFHP) is a science based, non-regulatory, partnership-driven effort to conserve fish habitat across the USA. The NFHP was developed in the early to mid-2000s in response to the noted declines to fish populations and their associated habitats across the USA with the effort led by the Association of Fish and Wildlife Agencies and supported by a wide range of federal and state fisheries agencies along with conservation organizations. Since 2006, 20 Fish Habitat Partnerships have been organized around specific habitats, fish species, or geographic areas. These partnerships have implemented 1,613 projects resulting in 9,720 habitat enhancements or parcels of habitat protected, including 7,962 riverine or coastline miles and 98,255 acres of marine, lake, impoundment, and reservoir fish habitat along with 1,499 science and data products using US$60,613,842 of direct NFHP investment matched or leveraged by $332,841,072. The NFHP was codified by the U.S. Congress in 2020 and reauthorized in 2024, building on the strong initial foundation and ensuring success into the future. Follow-up publications to this overview paper are planned by each Fish Habitat Partnership to fully describe the depth and breadth of this key U.S. habitat program.

Fisheries↗
USGS2021

Physics-guided machine learning for scientific discovery: An application in simulating lake temperature profiles

Physics-based models are often used to study engineering and environmental systems. The ability to model these systems is the key to achieving our future environmental sustainability and improving the quality of human life. This article focuses on simulating lake water temperature, which is critical for understanding the impact of changing climate on aquatic ecosystems and assisting in aquatic resource management decisions. General Lake Model (GLM) is a state-of-the-art physics-based model used for addressing such problems. However, like other physics-based models used for studying scientific and engineering systems, it has several well-known limitations due to simplified representations of the physical processes being modeled or challenges in selecting appropriate parameters. While state-of-the-art machine learning models can sometimes outperform physics-based models given ample amount of training data, they can produce results that are physically inconsistent. This article proposes a physics-guided recurrent neural network model (PGRNN) that combines RNNs and physics-based models to leverage their complementary strengths and improves the modeling of physical processes. Specifically, we show that a PGRNN can improve prediction accuracy over that of physics-based models (by over 20% even with very little training data), while generating outputs consistent with physical laws. An important aspect of our PGRNN approach lies in its ability to incorporate the knowledge encoded in physics-based models. This allows training the PGRNN model using very few true observed data while also ensuring high prediction accuracy. Although we present and evaluate this methodology in the context of modeling the dynamics of temperature in lakes, it is applicable more widely to a range of scientific and engineering disciplines where physics-based (also known as mechanistic) models are used.

ACM/IMS Transactions on Data Science↗
USGS2021

The 2018 update of the US National Seismic Hazard Model: Ground motion models in the western US

The U.S. Geological Survey (USGS) National Seismic Hazard Model (NSHM) is the scientific foundation of seismic design regulations in the United States and is regularly updated to consider the best available science and data. The 2018 update of the conterminous U.S. NSHM includes significant changes to the underlying ground motion models (GMMs), most of which are necessary to enable the new multi-period response spectra (MPRS) requirements of seismic design regulations that use hazard results for 22 spectral periods and eight site classes. This article focuses on the GMMs used in the western United States (WUS) and is a companion to a recent article on the GMMs used in the central and eastern United States (CEUS). In the WUS, for crustal and subduction earthquakes, two models used in previous versions of the NSHM are excluded to provide consistency over all considered periods and site classes. To more accurately estimate ground motions at long periods in the vicinity of Los Angeles, San Francisco, Salt Lake City, and Seattle, the 2018 NSHM incorporates deep sedimentary basin depth from local seismic velocity models. The subduction GMMs considered lack basin depth terms and are modified to include an additional scale factor to account for this. This article documents the WUS GMMs used in the 2018 NSHM update and provides detail on the changes to GMM medians, aleatory variability, epistemic uncertainty, and site-effect models. It compares each of these components with those considered in prior NSHMs and discusses their total effect on hazard.

Arizona, California, Idaho, Montana, New Mexico, N↗
USGS2021

The 2018 update of the US National Seismic Hazard Model: Ground motion models in the central and eastern US

The United States Geological Survey (USGS) National Seismic Hazard Model (NSHM) is the scientific foundation of seismic design regulations in the United States and is regularly updated to consider the best available science and data. The 2018 update of the conterminous US NSHM includes major changes to the underlying ground motion models (GMMs). Most of the changes are motivated by the new multi-period response spectra requirements of seismic design regulations that use hazard results for 22 spectral periods and 8 site classes. In the central and eastern United States (CEUS), the 2018 NSHM incorporates 31 new GMMs for hard-rock site conditions ( V S 30 = 3000 m / s ) "> ( V S 30 = 3000 m / s ) (VS30=3000m/s) , including the Next Generation Attenuation (NGA)-East GMMs. New aleatory variability and site-effect models, both specific to the CEUS, are applied to all median hard-rock GMMs. This article documents the changes to the USGS GMM selection criteria and provides details on the new CEUS GMMs used in the 2018 NSHM update. The median GMMs, their weights, epistemic uncertainty, and aleatory variability are compared with those considered in prior NSHMs. This article further provides implementation details on the CEUS site-effect model, which allows conversion of hard-rock ground motions to other site conditions in the CEUS for the first time in NSHMs. Compared with the 2014 NSHM hard-rock ground motions, the weighted average of median GMMs increases for large magnitude events at middle to large distance range, epistemic uncertainty increases in almost all situations, but aleatory variability is not significantly different. Finally, the total effect on hazard is demonstrated for an assumed earthquake source model in the CEUS, which shows an increased ring of ground motions in the vicinity of the New Madrid seismic zone and decreased ground motions near the East Tennessee seismic zone.

Earthquake Spectra↗
USGS2003

The challenge of archiving and preserving remotely sensed data

Few would question the need to archive the scientific and technical (S&T) data generated by researchers. At a minimum, the data are needed for change analysis. Likewise, most people would value efforts to ensure the preservation of the archived S&T data. Future generations will use analysis techniques not even considered today. Until recently, archiving and preserving these data were usually accomplished within existing infrastructures and budgets. As the volume of archived data increases, however, organizations charged with archiving S&T data will be increasingly challenged (U.S. General Accounting Office, 2002). The U.S. Geological Survey has had experience in this area and has developed strategies to deal with the mountain of land remote sensing data currently being managed and the tidal wave of expected new data. The Agency has dealt with archiving issues, such as selection criteria, purging, advisory panels, and data access, and has met with preservation challenges involving photographic and digital media. That experience has allowed the USGS to develop management approaches, which this paper outlines.

Data Science Journal↗
USGS2013

Assessing hazards along our Nation's coasts

Coastal areas are essential to the economic, cultural, and environmental health of the Nation, yet by nature coastal areas are constantly changing due to a variety of events and processes. Extreme storms can cause dramatic changes to our shorelines in a matter of hours, while sea-level rise can profoundly alter coastal environments over decades. These changes can have a devastating impact on coastal communities, such as the loss of homes built on retreating sea cliffs or protective dunes eroded by storm waves. Sometimes, however, the changes can be positive, such as new habitat created by storm deposits. The U.S. Geological Survey (USGS) is meeting the need for scientific understanding of how our coasts respond to different hazards with continued assessments of current and future changes along U.S. coastlines. Through the National Assessment of Coastal Change Hazards (NACCH), the USGS carries out the unique task of quantifying coastal change hazards along open-ocean coasts in the United States and its territories. Residents of coastal communities, emergency managers, and other stakeholders can use science-based data, tools, models, and other products to improve planning and enhance resilience.

Fact Sheet↗
USGS1982

Maps showing locations and descriptions of radiocarbon-dated samples from central and northern California

This compilation includes radiocarbon dates and other pertinent information about samples from northern and central California, principally north of latitude 36°, drawn largely from Radiocarbon, Science, unpublished data of U.S. Geological Survey geologists, and other published and unpublished data brought to the author's attention as of January 1981. It includes a location map, several tables, and two lists of sources that contain further information about the samples. This compilation is intended as a progress report rather than a complete survey of the literature.

California↗
USGS2007

Fly Ash: From Cradle to Grave

The Energy Resources Program of the U.S. Geological Survey promotes and supports coal research to improve the understanding of the coal endowment of the United States. This results in geologically based, non-biased energy information products for policy and decision makers, land and resource managers, other federal and state agencies, the domestic energy industry, foreign governments, nongovernmental groups, academia, and other scientists. A more integrated approach to our coal quality work involves what we call a 'cradle to grave' approach. These types of studies focus not on just one aspect of the coal but rather on how or where different quality parameters form and (or) occur and what happens to them through the mining, production, transport, utilization and waste disposal process. An extensive suite of coal quality analyses, mineralogical, petrology, and leaching investigations are determined on samples taken from the different phases of the coal utilization process. This report consists of a tutorial that was given on June 10, 2007 at the 32nd International Technical Conference on Coal Utilization & Fuel Systems, The Power of Coal, Clearwater Coal Conference in Clearwater, Florida, USA. This tutorial covers how these studies are conducted and the importance of providing improved, comprehensive, science-based data sets for policy and decision makers.

Open-File Report↗
USGS2025

Long Term Resource Monitoring procedures—Aquatic vegetation monitoring

This standard operating procedure (SOP) manual describes the collection of standardized, long-term data for aquatic vegetation communities in selected study pools of the Upper Mississippi River System in the United States. The primary intent of the data collection is to assess the status and trends that aid in understanding the unique river ecosystem and to guide large-scale ecological restoration of the river and its biological communities, like aquatic plants and their dependent wildlife. This SOP is an update to the version published in 2000 and reflects modifications to sample sizes and additions of new data collection procedures. All long-term monitoring programs and their SOPs must be adapted to changing conditions and be improved through learning, and this SOP clarifies procedures and adds new elements since the initial SOP was written more than 25 years ago. The SOP is intended for multiple audiences, including vegetation specialists through the Upper Mississippi River Restoration Program, data analysts using the publicly available data generated through this SOP, and natural resource managers and restoration practitioners who need data and science to guide some decisions. This SOP may be transferable and adaptable to other ecosystems when the aquatic plant community is the focus.

Illinois, Iowa, Minnesota, Missouri, Wisconsin↗
USGS2019

Radiometric calibration of a non-imaging airborne spectrometer to measure the Greenland ice sheet surface

Methods to radiometrically calibrate a non-imaging airborne visible-to-shortwave infrared (VSWIR) spectrometer to measure the Greenland ice sheet surface are presented. Airborne VSWIR measurement performance for bright Greenland ice and dark bare rock/soil targets is compared against the MODerate resolution atmospheric TRANsmission (MODTRAN ® ) radiative transfer code (version 6.0), and a coincident Landsat 8 Operational Land Imager (OLI) acquisition on 29 July 2015 during an in-flight radiometric calibration experiment. Airborne remote sensing flights were carried out in northwestern Greenland in preparation for the Ice, Cloud, and land Elevation Satellite 2 (ICESat-2) laser altimeter mission. A total of nine science flights were conducted over the Greenland ice sheet, sea ice, and open-ocean water. The campaign's primary purpose was to correlate green laser pulse penetration into snow and ice with spectroscopic-derived surface properties. An experimental airborne instrument configuration that included a nadir-viewing (looking downward at the surface) non-imaging Analytical Spectral Devices (ASD) Inc. spectrometer that measured upwelling VSWIR (0.35 to 2.5 µ m) spectral radiance ( W m - 2 sr - 1 µ m - 1 "> W m − 2 sr − 1 µ m − 1 ) in the two-color Slope Imaging Multi-polarization Photon-Counting Lidar's (SIMPL) ground instantaneous field of view, and a zenith-viewing (looking upward at the sky) ASD spectrometer that measured VSWIR spectral irradiance (W m −2 nm −1 ) was flown. National Institute of Standards and Technology (NIST) traceable radiometric calibration procedures for laboratory, in-flight, and field environments are described in detail to achieve a targeted VSWIR measurement requirement of within 5 % to support calibration/validation efforts and remote sensing algorithm development. Our MODTRAN predictions for the 29 July flight line over dark and bright targets indicate that the airborne nadir-viewing spectrometer spectral radiance measurement uncertainty was between 0.6 % and 4.7 % for VSWIR wavelengths (0.4 to 2.0 µ m) with atmospheric transmittance greater than 80 %. MODTRAN predictions for Landsat 8 OLI relative spectral response functions suggest that OLI is measuring 6 % to 16 % more top-of-atmosphere (TOA) spectral radiance from the Greenland ice sheet surface than was predicted using apparent reflectance spectra from the nadir-viewing spectrometer. While more investigation is required to convert airborne VSWIR spectral radiance into atmospherically corrected airborne surface reflectance, it is expected that airborne science flight data products will contribute to spectroscopic determination of Greenland ice sheet surface optical properties to improve understanding of their potential influence on ICESat-2 measurements.

Atmospheric Measurement Techniques↗
USGS2022

MIS 5e sea-level history along the Pacific coast of North America

The primary last interglacial, marine isotope substage (MIS) 5e records on the Pacific coast of North America, from Washington (USA) to Baja California Sur (Mexico), are found in the deposits of erosional marine terraces. Warmer coasts along the southern Golfo de California host both erosional marine terraces and constructional coral reef terraces. Because the northern part of the region is tectonically active, MIS 5e terrace elevations vary considerably, from a few meters above sea level to as much as 70 m above sea level. The primary paleo-sea-level indicator is the shoreline angle, the junction of the wave-cut platform with the former sea cliff, which forms very close to mean sea level. Most areas on the Pacific coast of North America have experienced uplift since MIS 5e time, but the rate of uplift varies substantially as a function of tectonic setting. Chronology in most places is based on uranium-series ages of the solitary coral Balanophyllia elegans (erosional terraces) or the colonial corals Porites and Pocillopora (constructional reefs). In areas lacking corals, correlation to MIS 5e often can be accomplished using amino acid ratios of fossil mollusks, compared to similar ratios in mollusks that also host dated corals. Uranium-series (U-series) analyses of corals that have experienced largely closed-system histories range from ∼124 to ∼118 ka, in good agreement with ages from MIS 5e reef terraces elsewhere in the world. There is no geomorphic, stratigraphic, or geochronological evidence for more than one high-sea stand during MIS 5e on the Pacific coast of North America. However, in areas of low uplift rate, the outer parts of MIS 5e terraces apparently were re-occupied by the high-sea stand at ∼100 ka (MIS 5c), evident from mixes of coral ages and mixes of molluscan faunas with differing thermal aspects. This sequence of events took place because glacial isostatic adjustment processes acting on North America resulted in regional high-sea stands at ∼100 and ∼80 ka that were higher than is the case in far-field regions, distant from large continental ice sheets. During MIS 5e time, sea surface temperatures (SSTs) off the Pacific coast of North America were higher than is the case at present, evident from extralimital southern species of mollusks found in dated deposits. Apparently, no wholesale shifts in faunal provinces took place, but in MIS 5e time, some species of bivalves and gastropods lived hundreds of kilometers north of their present northern limits, in good agreement with SST estimates derived from foraminiferal records and alkenone-based reconstructions in deep-sea cores. Because many areas of the Pacific coast of North America have been active tectonically for much or all of the Quaternary, many earlier interglacial periods are recorded as uplifted, higher-elevation terraces. In addition, from southern Oregon to northern Baja California, there are U-series-dated corals from marine terraces that formed at ∼80 ka, during MIS 5a. In contrast to MIS 5e, these terrace deposits host molluscan faunas that contain extralimital northern species, indicating cooler SST at the end of MIS 5. Here I present a review and standardized database of MIS 5e sea-level indicators along the Pacific coast of North America and the corresponding dated samples. The database is available in Muhs et al. (2021b; https://doi.org/10.5281/zenodo.5903285 ).

Earth System Science Data↗
USGS2022

The biogeography of relative abundance of soil fungi versus bacteria in surface topsoil

Fungi and bacteria are the two dominant groups of soil microbial communities worldwide. By controlling the turnover of soil organic matter, these organisms directly regulate the exchange of carbon between the soil and the atmosphere. Fundamental differences in the physiology and life history of bacteria and fungi suggest that variation in the biogeography of soil fungal and bacterial relative abundance could drive striking differences in carbon decomposition and soil organic matter formation across different biomes. However, a lack of global and predictive information on the distribution of these organisms in terrestrial 45 ecosystems has prevented the inclusion of soil fungal and bacterial relative abundance and the associated processes into global biogeochemical models. Here, we used a global scale dataset in the top soil surface (>3000 distinct observations of soil fungal and bacterial abundance) to generate the first quantitative and spatially high resolution (1km) explicit map of soil fungal proportion, defined as fungi/fungi + bacteria, across terrestrial ecosystems. We reveal striking latitudinal trends where fungal dominance increases in cold and high latitude environments with large soil carbon stocks. There was strong non-linear response of fungal 50 dominance to environmental gradient, i.e., mean annual temperature (MAT) and net primary productivity (NPP). Fungi and bacteria dominated in regions with low and high MAT and NPP, respectively, thus representing slow vs. fast soil energy channels, a concept with a long history in soil ecology. These high-resolution models provide the first steps towards representing the major soil microbial groups and their functional differences in global biogeochemical models to improve predictions of soil organic matter turnover under current and future climate scenarios

Earth System Science Data↗
USGS2017

PeRL: A circum-Arctic Permafrost Region Pond and Lake database

Ponds and lakes are abundant in Arctic permafrost lowlands. They play an important role in Arctic wetland ecosystems by regulating carbon, water, and energy fluxes and providing freshwater habitats. However, ponds, i.e., waterbodies with surface areas smaller than 1. 0 × 10 4 m 2 , have not been inventoried on global and regional scales. The Permafrost Region Pond and Lake (PeRL) database presents the results of a circum-Arctic effort to map ponds and lakes from modern (2002–2013) high-resolution aerial and satellite imagery with a resolution of 5 m or better. The database also includes historical imagery from 1948 to 1965 with a resolution of 6 m or better. PeRL includes 69 maps covering a wide range of environmental conditions from tundra to boreal regions and from continuous to discontinuous permafrost zones. Waterbody maps are linked to regional permafrost landscape maps which provide information on permafrost extent, ground ice volume, geology, and lithology. This paper describes waterbody classification and accuracy, and presents statistics of waterbody distribution for each site. Maps of permafrost landscapes in Alaska, Canada, and Russia are used to extrapolate waterbody statistics from the site level to regional landscape units. PeRL presents pond and lake estimates for a total area of 1. 4 × 10 6 km 2 across the Arctic, about 17 % of the Arctic lowland ( < 300 m a.s.l.) land surface area. PeRL waterbodies with sizes of 1. 0 × 10 6 m 2 down to 1. 0 × 10 2 m 2 contributed up to 21 % to the total water fraction. Waterbody density ranged from 1. 0 × 10 to 9. 4 × 10 1 km −2 . Ponds are the dominant waterbody type by number in all landscapes representing 45–99 % of the total waterbody number. The implementation of PeRL size distributions in land surface models will greatly improve the investigation and projection of surface inundation and carbon fluxes in permafrost lowlands. Waterbody maps, study area boundaries, and maps of regional permafrost landscapes including detailed metadata are available at https://doi.pangaea.de/10.1594/PANGAEA.868349 .

Earth System Science Data↗
USGS2017

The ACER pollen and charcoal database: A global resource to document vegetation and fire response to abrupt climate changes during the last glacial period

Quaternary records provide an opportunity to examine the nature of the vegetation and fire responses to rapid past climate changes comparable in velocity and magnitude to those expected in the 21st century. The best documented examples of rapid climate change in the past are the warming events associated with the Dansgaard-Oeschger (D-O) cycles during the last glacial period, which were sufficiently large to have had a potential feedback through changes in albedo and greenhouse gas emissions on climate. Previous reconstructions of vegetation and fire changes during the D-O cycles used independently constructed age models, making it difficult to compare the changes between different sites and regions. Here we present the ACER (Abrupt Climate Changes and Environmental Responses) global database which includes 93 pollen records from the last glacial period (73–15 ka) with a temporal resolution better than 1,000 years, 32 of which also provide charcoal records. A harmonized and consistent chronology based on radiometric dating (¹⁴C, ²³⁴U/²³⁰Th, OSL, ⁴⁰Ar/³⁹Ar dated tephra layers) has been constructed for 86 of these records, although in some cases additional information was derived using common control points based on event stratigraphy. The ACER database compiles metadata including geospatial and dating information, pollen and charcoal counts and pollen percentages of the characteristic biomes, and is archived in Microsoft AccessTM at doi:10.1594/PANGAEA.870867.

Earth System Science Data↗