Publications
Browse more than 160,000 publications authored by our scientists over the past 100+ year history of the USGS. Publications available are: USGS-authored journal articles, series reports, book chapters, other government publications, and more.
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Mission Area Publications
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Offspring sex ratios are male-biased reflecting sex-biased dispersal in Idaho, USA, wolves.
Offspring sex ratios can vary widely across species, and the reasons for such variation have long intrigued ecologists. For group-living animals, predicting offspring sex ratios as a function of group and environmental characteristics can be challenging. Additionally, mortality of group members can upend traditional theory used to explain offspring sex ratios observed in populations. Gray wolves (
Authors
David Edward Ausband
Puget small streams monitoring program annual status report, water year 2020
This status report summarizes data collection from Summer 2020 for the Stormwater Action Monitoring (SAM) project.
Authors
Rich W. Sheibley
The vegetation dynamics of the monsoonal wetland of the Keoladeo National Park, India: A reassessment
As a result of a field trip in 1980 to the monsoonal wetland of the Keoladeo National Park, India, which was organized by Dr. Brij Gopal, a study of the vegetation dynamics of this wetland was initiated. The original hypothesis for this study was that the seasonal vegetation changes caused by the annual summer monsoon was a compressed habitat cycle. Habitat cycles are a characteristic of prairie p
Authors
Arnold G. van der Valk, Beth Middleton
Prioritizing imperiled native aquatic species for conservation propagation
Native aquatic species are in decline, and hatcheries can play an important role in stemming these losses until larger ecological issues are addressed. However, as more federal and state agencies face budget uncertainty and the number of imperiled species increases, it is necessary to develop a tool to prioritize species for conservation propagation. Our objective was to create prioritized lists o
Authors
Molly A. H. Webb, Christopher S. Guy, Hilary B. Treanor, Krissy W. Wilson, Cassie D. Mellon, Paul Abate, Harry J. Crockett, Jordan Hofmeier, Chelsey Pasbrig, Patrick Isakson
GeoAI for spatial image processing
The development of digital image processing, as a subset of digital signal processing, depended upon the maturity of photography and image science, introduction of computers, discovery and advancement of digital recording devices, and the capture of digital images. In addition, government and industry applications in the Earth and medical sciences were paramount to the growth of the technology. Fr
Authors
Samantha Arundel, Kevin G McKeehan, Wenwen Li, Zhining Gu
Advancing subsurface investigations beyond the borehole with passive seismic horizontal-to-vertical spectral ratio and electromagnetic geophysical methods at transportation infrastructure sites in New Hampshire
The U.S. Geological Survey (USGS), in cooperation with the New Hampshire Department of Transportation (NHDOT), surveyed transportation infrastructure sites using rapidly deployable geophysical methods to assess benefits added to a comprehensive site characterization with traditional geotechnical techniques. Horizontal-to-vertical spectral-ratio (HVSR) passive-seismic and electromagnetic-induction
Authors
James Degnan, Krystle Pelham, Neil Terry, Sydney M. Welch, Carole D. Johnson
A characterization of the deep-sea coral and sponge community along the Oregon Coast using a remotely operated vehicle on the EXPRESS 2022 expedition
Deep-sea coral and sponge (DSCS) communities serve as essential fish habitat (EFH) by providing shelter and nursery habitat, increasing diversity, and increasing prey availability (Freese and Wing, 2003; Bright, 2007; Baillon et al., 2012; Henderson et al., 2020). Off the U.S. West Coast, threats to these long-lived, fragile organisms from bottom contact fishing gear, potential offshore renewable
Authors
Tom Laidig, Diana Watters, Meredith Everett, Nancy G. Prouty, Elizabeth Clarke
Hawaiian volcanic ash, an airborne fomite for nontuberculous mycobacteria
Nontuberculous mycobacteria (NTM) are environmentally acquired opportunistic pathogens that can cause chronic lung disease. Within the U.S., Hawai'i shows the highest prevalence rates of NTM lung infections. Here, we investigated a potential role for active volcanism at the Kīlauea Volcano located on Hawai'i Island in promoting NTM growth and diversity. We recovered NTM that are known to cause lun
Authors
Stephanie Dawrs, Ravleen Virdi, Grant Norton, Tamar Elias, Nabeeh Hasan, Schuyler Robinson, Jobel Matriz, L. Elaine Epperson, Cody Glickman, Sean Beagle, James L Crooks, Stephen T. Nelson, Edward Chan, David Damby, Michael Strong, Jennifer Honda
Variable climate-growth relationships of quaking aspen (Populus tremuloides) among Sky Island mountain ranges in the Great Basin, Nevada, USA
The Great Basin is an arid province located in the interior western United States. The region encompasses millions of hectares and quaking aspen (Populus tremuloides Michx.) forests comprise a minor portion of the total area. However, montane aspen forests play a disproportionately large role in providing ecosystem services in the region, including water retention, biodiversity, wildlife habitat,
Authors
Martin Senfeldr, Douglas J. Shinneman, Susan McIlroy, Paul Rogers, R. Justin DeRose
The Coastal Carbon Library and Atlas: Open source soil data and tools supporting blue carbon research and policy
Quantifying carbon fluxes into and out of coastal soils is critical to meeting greenhouse gas reduction and coastal resiliency goals. Numerous ‘blue carbon’ studies have generated, or benefitted from, synthetic datasets. However, the community those efforts inspired does not have a centralized, standardized database of disaggregated data used to estimate carbon stocks and fluxes. In this paper, we
Authors
James R. Holmquist, David H. Klinges, Michael Lonneman, Jaxine Wolfe, Brandon M. Boyd, Meagan J. Eagle, Jonathan Sanderman, Katherine Todd-Brown, Lauren N. Brown, E. Fay Belshe, Samantha K. Chapman, Ron Corstanje, Christopher N. Janousek, James T. Morris, Gregory Noe, Andre S. Rovai, Amanda C. Spivak, Megan Vahsen, Lisamarie Windham-Myers, Kevin D. Kroeger, Patrick Megonigal
Predicting large hydrothermal systems
We train five models using two machine learning (ML) regression algorithms (i.e., linear regression and XGBoost) to predict hydrothermal upflow in the Great Basin. Feature data are extracted from datasets supporting the INnovative Geothermal Exploration through Novel Investigations Of Undiscovered Systems project (INGENIOUS). The label data (the reported convective signals) are extracted from meas
Authors
Stanley Paul Mordensky, Erick Burns, Jacob DeAngelo, John Lipor
Cursed? Why one does not simply add new data sets to supervised geothermal machine learning models
Recent advances in machine learning (ML) identifying areas favorable to hydrothermal systems indicate that the resolution of feature data remains a subject of necessary improvement before ML can reliably produce better models. Herein, we consider the value of adding new features or replacing other, low-value features with new input features in existing ML pipelines. Our previous work identified st
Authors
Stanley Paul Mordensky, Erick Burns, John Lipor, Jacob DeAngelo