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.
Mission Area Publications
Mission Area Publications
We are focused on some of the most significant issues society faces, and our science is making a substantial contribution to the well-being of the Nation and the world. Learn more about the major topics our research covers and the programs focused on those topics.
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Understanding sea otter population change in southeast Alaska
IntroductionThe Southeast Alaska (SE) stock of northern sea otters (Enhydra lutris kenyoni) ranges from Cape Yakataga on the north to the Dixon Entrance on the south. During the maritime fur trade, sea otters were commercially harvested to near extinction in SE for their pelts and were presumed unlikely to naturally repopulate the region.
Authors
Joseph Michael Eisaguirre, Toshio D. Matsuoka, George G. Esslinger, Benjamin P Weitzman, Paul A. Schuette, Jamie N. Womble
Unified 200 kyr paleohydrologic history of the Southern Great Basin: Death Valley, Searles Valley, Owens Valley and the Devils Hole cave
We present a hydroclimate synthesis of the southern Great Basin over the last two glacial-interglacial cycles focused on paleolakes in Death Valley (core DV93-1), Searles Valley (core SLAPP-SRLS17), Owens Valley (core OL92), and the Devils Hole cave. There is close agreement between the occurrence of lakes in Death Valley and the height of the water table in the Devils Hole (50 km east of Death Va
Authors
Tim Lowenstein, Kristian Olson, Brian W. Stewart, David McGee, Justin Stroup, Adam M. Hudson, Kathleen Wendt, Mark Peaple, Sarah Feakins, Ronald Spencer, Tripti Bhattacharya, Steven P. Lundblad, Ronald Litwin
In situ lung dust analysis by automated Field Emission Scanning Electron Microscopy with Energy Dispersive X-ray Spectroscopy: A method for assessing inorganic particles in tissue from coal miners
Context.—Overexposure to respirable coal mine dust can cause severe lung disease including progressive massive fibrosis (PMF). Field emission scanning electron microscopy with energy dispersive x-ray spectroscopy (FESEM-EDS) has been used for in situ lung dust particle analysis for evaluation of disease etiology. Automating such work can reduce time, costs, and user bias.Objective.—To develop and
Authors
Emily A. Sarver, C. Keles, Heather A. Lowers, L. Zell-Baran, Leonard H. T. Go, J. Hua, C. Cool, Cecile Rose, F.H. Green, K. S. Almberg, R. A. Cohen
Application of normalized radar backscatter and hyperspectral data to augment rangeland vegetation fractional classification
Rangeland ecosystems in the western United States are vulnerable to climate change, fire, and anthropogenic disturbances, yet classification of rangeland areas remains difficult due to frequently sparse vegetation canopies that increase the influence of soils and senesced vegetation, the overall abundance of senesced vegetation, heterogeneity of life forms, and limited ground-based data. The Range
Authors
Matthew B. Rigge, Brett Bunde, Kory Postma, Simon Oliver, Norman Mueller
Mammalian lures monitored with time-lapse cameras increase detection of pythons and other snakes
BackgroundEnhancing detection of cryptic snakes is critical for the development of conservation and management strategies; yet, finding methods that provide adequate detection remains challenging. Issues with detecting snakes can be particularly problematic for some species, like the invasive Burmese python (Python bivittatus) in the Florida Everglades.MethodsUsing multiple survey methods, we pred
Authors
Marina E. McCampbell, McKayla M. Spencer, Kristen Hart, Gabrielle Link, Andrew J. Watson, Robert A. McCleery
Computationally efficient emulation of spheroidal elastic deformation sources using machine learning models: a Gaussian-process-based approach
Elastic continuum mechanical models are widely used to compute deformations due to pressure changes in buried cavities, such as magma reservoirs. In general, analytical models are fast but can be inaccurate as they do not correctly satisfy boundary conditions for many geometries, while numerical models are slow and may require specialized expertise and software. To overcome these limitations, we t
Authors
Kyle R. Anderson, Mengyang Gu
Siting considerations for satellite observation of river discharge
With growing global capability for satellite measurement of river discharge (flow) comes a need to understand and reduce error in satellite-based discharge measurements. Satellite-based discharge estimates are based on measurements of water surface width, elevation, slope, and potentially velocity. Site selection is important for reducing error and uncertainty in both conventional and satellite-ba
Authors
Jack R. Eggleston, Chris A. Mason, David M. Bjerklie, Michael T. Durand, Robert W. Dudley, Merritt Elizabeth Harlan
A reproducible manuscript workflow with a Quarto template
Scientists and resource managers increasingly use Markdown-based tools to create reproducible reports and manuscripts. These workflows allow people to use standardized methods that are more reproducible, efficient, and transparent than other standard office tools. We present a Quarto template and demonstrate how this template may be used for a journal, the Journal of Fish and Wildlife Management,
Authors
Richard A. Erickson, Althea A. Archer, Michael N. Fienen
Assessing the vertical accuracy of digital elevation models by quality level and land cover
The vertical accuracy of elevation data in coastal environments is critical because small variations in elevation can affect an area’s exposure to waves, tides, and storm-related flooding. Elevation data contractors typically quantify the vertical accuracy of lidar-derived digital elevation models (DEMs) on a per-project basis to gauge whether the datasets meet quality and accuracy standards. Here
Authors
Minoo Han, Nicholas Enwright, Dean B. Gesch, Jason M. Stoker, Jeffrey J. Danielson, Christopher J. Amante
A spatial machine learning model developed from noisy data requires multiscale performance evaluation: Predicting depth to bedrock in the Delaware River Basin, USA
Spatial machine learning models can be developed from observations with substantial unexplainable variability, sometimes called ‘noise’. Traditional point-scale metrics (e.g., R2) alone can be misleading when evaluating these models. We present a multi-scale performance evaluation (MPE) using two additional scales (distributional and geostatistical). We apply the MPE framework to predictions of de
Authors
Phillip J. Goodling, Kenneth Belitz, Paul Stackelberg, Brandon J. Fleming
Back from the brink: Estimating daily and annual abundance of natural-origin salmon smolts from 30-years of mixed-origin capture-recapture data
Evaluating the status and trends of natural-origin anadromous fish populations over time requires robust estimates of out-migrating juvenile abundance. Information on abundance is typically acquired by capturing actively migrating fish as they pass stationary monitoring platforms. Challenges to estimation include protracted migration timing, temporally varying capture probabilities and the contemp
Authors
Dalton Hance, John Plumb, Russell Perry, Kenneth Tiffan
Modeling the mid-piacenzian warm climate using the water isotope-enabled Community Earth System Model (iCESM1.2-ITPCAS)
The mid-Piacenzian Warm Period (MPWP, ~ 3.264–3.025 Ma) is the most recent example of a persistently warmer climate in equilibrium with atmospheric CO2 concentrations similar to today. Towards studying patterns and dynamics of a warming climate the MPWP is often compared to today. Following the Pliocene Model Intercomparison Project, Phase 2 (PlioMIP2) protocol we prepare a water isotope-enabled C
Authors
Yong Sun, Baohuang Su, Harry J. Dowsett, Haibin Wu, Jun Hu, Christian Stepanek, Zhongyu Xiong, Xiayu Yuan, Gilles Ramstein