Data Releases
The data collected and the techniques used by USGS scientists should conform to or reference national and international standards and protocols if they exist and when they are relevant and appropriate. For datasets of a given type, and if national or international metadata standards exist, the data are indexed with metadata that facilitates access and integration.
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Serologic Survey of Selected Arthropod Borne Pathogens in Free-ranging Snowshoe Hares (Lepus americanus) Captured in Northern Michigan, USA
We conducted a serosurvey of snowshoe hares (Lepus americanus) for vector-borne pathogens in 2016-2017 that were captured in the Hiawatha National Forest in the eastern Upper Peninsula of Michigan, USA. At capture, in addition to age, sex, body weight of the hare and a blood sample data was collected on the ecological land type (USDA Forest Service. 2006. Hiawatha National Forest 2006 Forest Plan.
Data from temperature measurements in research drill hole Y-7, Upper Geyser Basin, Yellowstone National Park
Active thermal areas in Yellowstone National Park provide insight into a variety of hydrothermal processes occurring at depth, such as water-rock interactions, the formation of alteration minerals, and microbial (thermophile) metabolism in extreme environments. Research drill hole Y-7 (44°29'8.74", -110°51'7.67") is one of 13 holes completed by the U.S. Geological Survey in 1967 and 1968 at select
PHREEQC files for geochemical simulations in the Ohio River alluvial aquifer of West Virginia
This data release includes PHREEQC files used for geochemical models in the Ohio River alluvial aquifer of West Virginia. The associated publication by McAdoo and Connock (2024) should be consulted to understand the purpose and limitations of these simulations and data. The wateq4f database (Ball and Nordstrom, 1991) was used for the PHREEQC simulation. A report by Parkhurst and Appelo (2013) ser
Aquaculture and Irrigation Water Use Model (AIWUM) 2.0 input and output datasets
Datasets are inputs and outputs of Aquaculture and Irrigation Water Use Model (AIWUM) 2.0. AIWUM 2.0 employs remote sensing data sets and machine learning utilizing Distributed Random Forests, an ensemble machine learning algorithm to estimate annual and monthly groundwater use for irrigation and aquaculture (2014–20) throughout this region at 1 km resolution, using annual pumping data from flowm
Black bear (Ursus Americanus) spatial capture recapture dataset in and near Glacier National Park, Montana, USA, 2004
Tabular and raster data containing spatial capture recapture records for male and female black bears (Ursus americanus) in Glacier National Park and surrounding landscape collected from June - October 2004 and associated tabular data files required for analysis of data with spatial capture connectivity models and raster data describing the ouput from SCR models. Associated tables and rasters inclu
Input and results from a random forest classification (RFC) model that predicts redox conditions in groundwater in the contiguous United States
This data release provides model inputs and outputs for a model that predicts redox conditions in groundwater in the contiguous United States. Input variables describe the hydrology, soils, geology, and hydrologic position of groundwater sample locations. The data release accompanies a journal article that describes model development and applications (Tesoriero_and_others_2023).
Groundwater-quality data in the Gilroy Hollister basin and surrounding areas Domestic-Supply Aquifer Study Unit, 2022: Results from the California GAMA Priority Basin Project
The U.S. Geological Survey collected groundwater samples from 33 wells used for domestic and small system drinking water supplies in Santa Clara and San Benito Counties, California in 2022. The wells were sampled for the Gilroy Hollister basin and surrounding areas Domestic-Supply Aquifer Study Unit of the State Water Resources Control Board Groundwater Ambient Monitoring and Assessment (GAMA) Pro
USGS National and Global Oil and Gas Assessment Project—Raton Basin-Sierra Grande Uplift Province, Raton Continuous Resources: Assessment Unit Boundaries, Assessment Input Data, and Fact Sheet Data Tables
This data release contains the boundaries of assessment units and input data for the assessment of undiscovered oil and gas resources in upper Cretaceous marine shales in the Raton Basin-Sierra Grande Uplift Province, Colorado and New Mexico. The Assessment Unit is the fundamental unit used in the National Assessment Project for the assessment of undiscovered oil and gas resources. The Assessment
Dead Tree Detection Validation Data from Sequoia and Kings Canyon National Parks
Most of these data were collected in order to create a database of tree locations for use in calibrating remote sensing tools and products, particularly dead tree detection tools and canopy species maps. Data include tree locations, species identification, and status (live, dead, and, if dead, sometimes includes information on foliage and twig retention). They are a collection of different samplin
Carbon, Nitrogen, and Sulfur Stable Isotopes from Primary Producers, Invertebrates, and Fish at the Nisqually River Delta, Washington from 2011, 2012, and 2015
This dataset consists of carbon, nitrogen, and sulfur stable isotope data from primary producers, invertebrates, and fish from the Nisqually River Delta, Washington from 2011, 2012, and 2015. Data were collected to determine food web structure in different habitat zones within the entire river delta. Data collection for primary producers and invertebrates were led by U.S. Geological Survey, while
Bayou Bonfouca Marsh Creation (PO-104): 2016 and 2018 land-water classifications
The Louisiana State Legislature created the Coastal Wetlands Planning, Protection and Restoration Act (CWPPRA) in order to conserve, restore, create and enhance Louisiana's coastal wetlands. The wetland restoration plans developed pursuant to these acts specifically require an evaluation of the effectiveness of each coastal wetlands restoration project in achieving long-term solutions to arresting
Grain-size analysis data of sediment samples from the beach and nearshore environments at the Pea Island National Wildlife Refuge DUNEX site, North Carolina in 2021
This data release supersedes version 1.0, published in September 2022 at https://doi.org/10.5066/P9XEFRYR. Versioning details are documented in the accompanying revision_history.txt file.
These data provide grain-size measurements from sediment samples collected as part of the USGS DUring Nearshore Event eXperiment (DUNEX) site on Pea Island National Wildlife Refuge, NC. DUNEX is a multi-agency,