Filters: Tags: South Dakota (X) > partyWithName: U.S. Geological Survey - ScienceBase (X)
419 results (22ms)|
Filters
Date Range
Extensions
Types Contacts Categories Tag Types
|
Real-time kinematic global navigation satellite system equipment was used to survey the edge of bank at selected locations on the Lake Sharpe shoreline near Lower Brule South Dakota at intervals from 2010–15. This work was completed by the U.S. Geological Survey in cooperation with the Lower Brule Sioux Tribe Environmental Protection Office.
This dataset provides timeseries data on water quality and quantity, as collected or computed from outside sources. The format is many tables with one row per time series observation (1 tab-delimited file per site-variable combination, 1 zip file per site). This compilation of data is intended for use in estimating or interpreting metabolism. Sites were included if they met the initial criteria of having at least 100 dissolved oxygen observations and one of the accepted NWIS site types ('ST','ST-CA','ST-DCH','ST-TS', or 'SP'). This dataset is part of a larger data release of metabolism model inputs and outputs for 356 streams and rivers across the United States (https://doi.org/10.5066/F70864KX). The complete release...
These data were collected as part of a field trial to test the effectiveness of a sylvatic plague vaccine (see Rocke et al., 2017 for details). Vaccine and control plots were selected randomly from the available pairs at each location. Baits containing Rhodamine B, a biomarker, were distributed at each plot. At least 1 week and no more than 2 months post-baiting each year, local collaborators captured, marked, and sampled prairie dogs. Hair and whisker samples were collected from up to 50 unique prairie dogs from each plot each year. Sex, age, weight, and the identity of all current-year and prior-year recaptures were recorded for each captured animal. In the laboratory, hair/whiskers were assessed for the presence...
Categories: Data;
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: Arizona,
Awapa Plateau,
Buffalo Gap National Grasslands,
Cedar City,
Charles M. Russell National Wildlife Refuge,
These data represent simulated soil temperature and moisture conditions for current climate, and for future climate represented by all available climate models at two time periods during the 21st century. These data were used to: 1) quantify the direction and magnitude of expected changes in several measures of soil temperature and soil moisture, including the key variables used to distinguish the regimes used in the R and R categories; 2) assess how these changes will impact the geographic distribution of soil temperature and moisture regimes; and 3) explore the implications for using R and R categories for estimating future ecosystem resilience and resistance.
Geographic distribution data were collected based on county level occurrences (or converted from point occurrences to county level occurrences) within the five focal states (Minnesota, North Dakota, South Dakota, Nebraska & Iowa) and each U.S. state or Canadian province bordering those focal states (Wisconsin, Illinois, Missouri, Kansas, Wyoming, & Montana in the USA and Saskatchewan, Ontario & Manitoba in Canada).
The RCMAP (Rangeland Condition Monitoring Assessment and Projection) dataset quantifies the percent cover of rangeland components across the western U.S. using Landsat imagery from 1985-2021. The RCMAP product suite consists of nine fractional components: annual herbaceous, bare ground, herbaceous, litter, non-sagebrush shrub, perennial herbaceous, sagebrush, shrub, and tree, in addition to the temporal trends of each component. Several enhancements were made to the RCMAP process relative to prior generations. First, we have trained time-series predictions directly from 331 high-resolution sites collected from 2013-2018 from Assessment, Inventory, and Monitoring (AIM) instead of using the 2016 “base” map as an intermediary....
The High Plains aquifer extends from approximately 32 to 44 degrees north latitude and 96 degrees 30 minutes to 106 degrees west longitude. The aquifer underlies about 175,000 square miles in parts of Colorado, Kansas, Nebraska, New Mexico, Oklahoma, South Dakota, Texas, and Wyoming. This digital dataset consists of a raster of water-level changes for the High Plains aquifer, predevelopment (about 1950) to 2019. It was created using water-level measurements from 2,741 wells measured in both the predevelopment period (about 1950) and in 2019, the latest available static water level measured in 2015 to 2018 from 71 wells in New Mexico and using other published information on water-level change in areas with few water-level...
This dataset provides early estimates of 2021 exotic annual grasses (EAG) fractional cover predicted on May 3rd. We develop and release EAG fractional cover map with an emphasis on cheatgrass (Bromus tectrorum) but it also includes number of other species, i.e., Bromus arvensis L., Bromus briziformis, Bromus catharticus Vahl, Bromus commutatus, Bromus diandrus, Bromus hordeaceus L., Bromus japonicus, Bromus madritensis L., Bromus racemosus, Bromus rubens L., Bromus secalinus L., Bromus texensis (Shear) Hitchc., and medusahead (Taeniatherum caput-medusae. The dataset was generated leveraging field observations from Bureau of Land Management (BLM) Assessment, Inventory, and Monitoring data (AIM) plots; Harmonized...
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Arizona,
California,
Colorado,
Great Basin,
Harmonized Landsat Sentinel,
Across the country, public land managers make hundreds of decisions each year that influence landscapes and ecosystems within the lands they manage. Many of these decisions involve vegetation manipulations known as land treatments. Land treatments include activities such as removal or alteration of plant biomass, seeding burned areas, and herbicide applications. Data on these land treatments historically have been stored at local offices and gathering information across large spatial areas was difficult. These valuable data needed to be centralized and stored for Federal agencies involved in land treatments because these data are useful to land managers for policy and management and to scientists for developing...
These data were released prior to the October 1, 2016 effective date for the USGS’s policy dictating the review, approval, and release of scientific data as referenced in USGS Survey Manual Chapter 502.8 Fundamental Science Practices: Review and Approval of Scientific Data for Release. Estimates of area and aerial extent of land-use categories are an essential component for computing the water budget of the High Plains aquifer. These raster land-use land class data represent yearly simulated future land use for the High Plains from 2009 to 2050 These data were developed using the FOREcasting SCEnarios (FORE-SCE) of future land cover model (Sohl and others, 2007; Sohl and Sayler 2008) for two (A2 and B2) of the...
Estimation of irrigation water use provides essential information for the management and conservation of agricultural water resources. The blue water evapotranspiration (BWET) raster dataset at 30-meter resolution is created to estimate agricultural irrigation water consumption. The dataset contains seasonal total (1 May to 30 September) BWET time series (1986 – 2020) for the croplands across the U.S. High Plains aquifer region. The BWET estimates are generated by integrating an energy-balance ET model (Operational Simplified Surface Energy Balance model) and a water-balance ET model (Vegetation ET model). BWET in croplands reflects crop consumptive use of irrigation water extracted from surface water and groundwater...
Climate change over the past century has altered vegetation community composition and species distributions across rangelands in the western United States. The scale and magnitude of climatic influences are largely unknown. We used fractional component cover data for rangeland functional groups and weather data from the 1985 to 2023 reference period in conjunction with soils and topography data to develop empirical models describing the spatio-temporal variation in component cover. To investigate the ramifications of future change across the western US, we extended models based on historical relationships over the reference period to model landscape effects based on future weather conditions from two emissions scenarios...
This child item describes Python code used to estimate average yearly and monthly tourism per 1000 residents within public-supply water service areas. Increases in population due to tourism may impact amounts of water used by public-supply water systems. This data release contains model input datasets, Python code used to develop the tourism information, and output estimates of tourism. This dataset is part of a larger data release using machine learning to predict public supply water use for 12-digit hydrologic units from 2000-2020. Output from this code was used as an input feature in the public supply delivery and water use machine learning models. This page includes the following files: tourism_input_data.zip...
This child item describes a public supply delivery machine learning model that was developed to estimate public-supply deliveries. Publicly supplied water may be delivered to domestic users or to commercial, industrial, institutional, and irrigation (CII) users. This model predicts total, domestic, and CII per capita rates for public-supply water service areas within the conterminous United States for 2009-2020. This child item contains model input datasets, code used to build the delivery machine learning model, and national predictions. This dataset is part of a larger data release using machine learning to predict public-supply water use for 12-digit hydrologic units from 2000-2020. This page includes the following...
This child item describes Python code used to query census data from the TigerWeb Representational State Transfer (REST) services and the U.S. Census Bureau Application Programming Interface (API). These data were needed as input feature variables for a machine learning model to predict public supply water use for the conterminous United States. Census data were retrieved for public-supply water service areas, but the census data collector could be used to retrieve data for other areas of interest. This dataset is part of a larger data release using machine learning to predict public supply water use for 12-digit hydrologic units from 2000-2020. Data retrieved by the census data collector code were used as input...
These datasets provide early estimates of 2022 fractional cover for exotic annual grass (EAG) species and one native perennial grass species on a bi-weekly basis from May to early July. The EAG estimates are developed within one week of the latest satellite observation used for that version. Each bi-weekly release contains four fractional cover maps along with their corresponding confidence maps for: 1) a group of 16 species of EAGs, 2) cheatgrass (Bromus tectorum); 3) medusahead (Taeniatherum caput-medusae); and 4) Sandberg bluegrass (Poa secunda). These datasets were generated leveraging field observations from Bureau of Land Management (BLM) Assessment, Inventory, and Monitoring (AIM) data plots; Harmonized Landsat...
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Arizona,
California,
Colorado,
Great Basin,
Harmonized Landsat Sentinel,
River valley boundary extents were generated for select large river floodplains of the Upper Midwest, United States. These polygons were delineated using a method that incorporated interpolating a water surface elevation that completely over-topped water-control structures within the valley such as levees, flood walls, and roadways. The intersection of this derived water surface and land elevation at the outermost edge of the floodplain was used to delineate the approximate extent of the river valley boundary. We used best professional judgment to approximate this water surface elevation.
Categories: Data;
Types: Downloadable,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
Shapefile;
Tags: Illinois,
Indiana,
Iowa,
Kansas,
Kentucky,
This data release contains input data used in model development and TIF raster files used to predict the probability of high arsenic (As) and high manganese (Mn) in groundwater within the glacial aquifer system in the northern United States. Input data include measured As and Mn concentrations at groundwater wells, and associated predictor variable data. The probability of high As and high Mn was predicted using boosted regression tree methods using the gbm package in R version 4.0.0. The response variables for individual models were the occurrence of: (1) As >10 µg/L, and (2) Mn >300 µg/L. Water-quality data were compiled from three sources, as described in Wilson and others (2019): a compilation of data from numerous...
These data were compiled to provide seed transfer and native plant materials development guidance to managers and practitioners across the Colorado Plateau and in adjacent regions. This data release contains empirical seed transfer zones derived from molecular genetic data for Cleome lutea (syn. Peritoma lutea) and Machaeranthera canescens (syn. Dieteria canescens). These species show distinct population structure (i.e., genetic differentiation) across their ranges; as such, seed transfer zones reflect both patterns of genetic differentiation and information on each species' unique adaptations to climatic gradients. These shapefile data may support successful restoration outcomes if, for example, seed transfer follows...
The U.S. Geological Survey National Wildlife Health Center (NWHC) measured environmental contaminants in bald eagles (Haliaeetus leucocephalus) and golden eagles (Aquila chrysaetos) to evaluate dietary exposure to lead, mercury, and anticoagulant rodenticides (AR), which was identified by U.S. Fish and Wildlife Service (USFWS) as a priority issue of concern for the Mountain Prairie Region 6. Carcasses of bald eagles (n = 172) and golden eagles (n = 142) collected from North and South Dakota, Montana, Wyoming, Colorado, Utah, Nebraska, and Kansas between 2014-2017 were assessed for cause of death and liver lead, mercury, and AR levels. Trauma, electrocution, and lead poisoning were the 3 leading causes of death,...
|
|
