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Whooping cranes (Grus americana) of the Aransas-Wood Buffalo population migrate twice each year through the Great Plains in North America. Recovery activities for this endangered species include providing adequate places to stop and rest during migration, which are generally referred to as stopover sites. To assist in recovery efforts, initial estimates of stopover site use intensity are presented, which provide opportunity to identify areas across the migration range used more intensively by whooping cranes. We used location data acquired from 58 unique individuals fitted with platform transmitting terminals that collected global position system locations. Radio-tagged birds provided 2,158 stopover sites over 10...
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Raw data were collected in Shenandoah National Park during summer 2012. Air and temperature data were collected using temperature loggers at several stations throughout the park. These data were used in the publication of the manuscript "Accounting for groundwater influence on headwater stream thermal sensitivity to climate change" through the journal Ecological Applications. Water temperature data were collected at all 78 reach locations during the summer of 2012 (23 June–7 September). Temperature was measured every hour with a logger.
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Remote camera data on snow presence, snow depth, and wildlife detections on Moscow Mountain in Latah County, ID, USA. Reconyx Hyperfire I and Hyperfire II cameras were used and set to take hourly timelapse images and motion-triggered images. The cameras were deployed from October 2020 - May 2021. Snow presence was assessed up to 15 m from the camera. Snow depth was measured using virtual snow stakes created with the edger R package created by the author. Wildlife were marked as present in all photos in which they appear, and new individuals were counted. Snow density was collected using a federal or prairie snow sampler. Snow hardness was collected using a ram penetrometer. Solar radiation was calculated using hemispherical...
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We collected snow density measurements at camera sites from December 2020 - April 2021, at the same time as snow hardness measurements. We took measurements every few weeks as logistics allowed. We took samples near the camera site in snow visually similar to the snow in the camera viewshed (the geographical area that is visible from a location) to prevent snow conditions from being disturbed beyond normal camera deployment. We took snow density samples using a homemade prairie sampler in snow depths < 100 cm and using a federal snow sampler in snow depths > 100 cm. The sampler was inserted into the snow to remove a snow core. We retained the core if the depth of snow in the sampler was at least 90% of the actual...
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Fish occurrence data to support high-resolution distribution models and test various community and macroecological hypotheses have not been available at the national scale. We present IchthyMaps, a database of high-quality historical fish occurrences covering fishes of the conterminous United States. Designed on the principles of metacommunity ecology, IchthyMaps is a compilation of presence records from atlases up to 1990, at the resolution of the 1:100,000 National Hydrography Database Plus (NHDPlus) inter-confluence stream segment, readily aggregated into hierarchically coarser units (e.g. hydrologic unit code 8-digit and 12-digit watersheds). IchthyMaps contains about 606,550 presence records for 1,038 species...
Categories: Data, Publication; Types: Citation; Tags: Alabama, Arizona, Arkansas, Biological Data, Biological sampling, All tags...
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Attributes of remote camera stations on Moscow Mountain in Latah County, ID including georeferencing information and camera deployment information. Remote cameras were used to collect data on snow presence, snow depth, and wildlife detections on Moscow Mountain in Latah County, ID, USA. Reconyx Hyperfire I and Hyperfire II cameras were used and set to take hourly timelapse images and motion-triggered images. The cameras were deployed from October 2020 - May 2021.
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Drylands cover 40% of the global terrestrial surface and provide important ecosystem services. While drylands as a whole are expected to increase in distribution and aridity in coming decades, temperature and precipitation forecasts vary by latitude and geographic region suggesting different trajectories for tropical, subtropical, and temperate drylands. Uncertainty in the future of tropical and subtropical drylands is well constrained, whereas soil moisture and ecological droughts, which drive vegetation productivity and composition, remain poorly understood in temperate drylands. Here we show that, over the 21st century, temperate drylands may contract by a third, primarily converting to subtropical drylands,...
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Previous research identified species of invasive plants in Hawai'i which are highly flammable and act as fuels in wildfires across Hawai'i. This work aimed to map the distribution of these species (largely grasses) around the islands of Hawai'i with the goal of using the locations for species distribution modeling. All data represents presence data, no absence data were recorded. Data are largely from within the past 20 years, but some georeferenced herbarium specimens go as far back as 1905. Data were obtained from georeferenced herbarium specimens, vegetation plot data, citizen science data (iNaturalist) reviewed by the authors, and data from roadside surveys conducted as part of this research to map these species....
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We took hemispherical photographs (hemiphotos) at each camera station to estimate incoming shortwave radiation. We used a Canon EOS 70D SLR camera with a Sigma 8mm circular fisheye lens. We took hemiphotos on days with little to no wind or precipitation and early in the morning (5AM – 7AM), late in the evening (7PM – 9PM), or on overcast days to maximize the contrast between sky and vegetation. We took hemiphotos in June - July 2021, but nine camera sites were re-photographed in October 2021 due to poor quality of initial photographs. Overstory deciduous vegetation is rare at the study site, so summer changes in canopy cover are negligible. At each camera site, we placed the DSLR camera with attached lens on a tripod...
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Snow hardness measurements were collected at camera sites from December 2020 - April 2021, at the same time as snow density. Camera sites were chosen by stratified non-random sampling. Cameras were never closer than 25m to other cameras, nor were they placed facing trails. Measurements were collected every few weeks as logistics allowed. Samples were collected near the camera site in snow visually similar to the snow in the camera viewshed to prevent snow conditions from being disturbed beyond normal camera deployment. Snow hardness was measured using a ram penetrometer or “ramsonde” (Snowmetrics; Fort Collins, CO). A ramsonde is composed of a hammer, anvil, and rod. The hammer is dropped onto the anvil from a known...
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Numerous wind energy projects have been constructed in the central and southern Great Plains, USA, the main wintering area for midcontinent Sandhill Cranes (Grus canadensis). We assessed exposure of wintering Sandhill Cranes to the current distribution of wind towers in the central and southern Great Plains by estimating overlap using location data from platform transmitting terminals (PTT) collected during winters 1998–2004. Because 90% of wind towers in the region were installed 2004–2013, comparing an established distribution of wind towers (as of January 2014) with pre-construction crane (1998-2004) distribution provides an initial assessment of the midcontinent population’s exposure. Distributions of cranes...
To facilitate camera-based snow depth observations without additional equipment installation, we developed a novel method implemented in an R package called edger to superimpose virtual measurement devices onto images. The virtual snow stakes can be used to derive snow depth measurements. We validated the method for snow depth estimation using camera data from Latah County, Idaho, USA in winter 2020–2021. Physical snow stakes were installed in the camera viewshed with which snow depth measurements were taken. Then, virtual snow stakes were superimposed on the images using edger and images were cropped to exclude the physical snow stake so that the two snow depth measurements could be compared. This dataset contains...
Modeled soil moisture raster maps (4km-pixels) displaying volumetric water content (VWC) and fraction of available water (FAW) in 10-cm depth increments for the 2015-2019 period for the Red River and Rio Grande basins.
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The ascii grids represent regional probabilities that groundwater in a particular location will have dissolved oxygen (DO) concentrations less than selected threshold values representing anoxic groundwater conditions or will have dissolved manganese (Mn) concentrations greater than selected threshold values representing secondary drinking water-quality contaminant levels (SMCL) and health-based screening levels (HBSL) for water quality. The probability models were constrained by the alluvial boundary of the Central Valley to a depth of approximately 300 meters (m). We utilized prediction modeling methods, specifically boosted regression trees (BRT) with a Bernoulli error distribution within a statistical learning...
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Remote camera data on snow presence, snow depth, and wildlife detections on Moscow Mountain in Latah County, ID, USA. Reconyx Hyperfire I and Hyperfire II cameras were set to take hourly timelapse images and motion-triggered images from October 2020 - May 2021 at 5 elevation categories (800-925m, 925-1050m, 1050-1175m, 1775-1300m, and > 1300m), 4 aspects (N, S, E, and W), and 3 canopy densities (Sparse [0-35%], Moderate [35-75%], and Dense [75-100%]), in duplicate, plus 17 selected microclimates (137 locations total), on Moscow Mountain in Latah County, ID. Images from 27 other locations were part of a pilot experiment during January to May 2020. Data in the CSVs include image metadata, camera site characteristics,...
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These model objects are the outputs of three Boosted Regression Tree models (for three different time periods) to explore the role of climate change and variability in driving ecological change and transformation. Response variables were the proportion of sites in each ecoregion with peak rates of change at 100-year time steps. Predictor variables included temperature anomaly, temperature trend, temperature variability, precipitation anomaly, precipitation trend, precipitation variability and ecoregion, also at 100-yr time steps. Models focused on the most distant time periods (0-21000 BP and 7500 - 21000 BP) show that rapid vegetation change was initiated across these landscapes once a 2 ℃ temperature increase...
The baseline map of the Butte Basin, the representative basin from the Central Valley, was generated first by delineating the extent of the landscape to be modeled, in agreement with the basin boundaries identified by the Central Valley Joint Venture.The Butte Basin (CV) encompasses a region approximately 44km x 64 km, and the map used contains 10,698 individual habitat patches and 179,964 acres of possible foreageable area. Patch habitat types were identified by a combination of USDA CropScape data (to identify agricultural habitat patches including rice and corn) and other local mapping data made available through collaboration with USGS. Habitat flood schedules were generated using the Water Evaluation and Planning...
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Landforms along the Pacific, Gulf of Mexico, and Atlantic coastlines for the conterminous United States are attributed with the relative vulnerability of horizontal erosion due to sea-level rise to characterize coastal zone stability. The position and extent of landforms are geospatially indexed as line-events where these coastal zone features are intersected by the linear-referenced 2013 - 2014 U.S. Geological Survey National Hydrography Dataset Coastline, which corresponds to the National Oceanic and Atmospheric Administration (NOAA) 2013 - 2014 mean high water level datum delineated in intertidal zones open to oceans, behind barrier coasts in bays, lagoons, and estuaries, and sometimes where tidal currents reach...
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Predicted snow disappearance dates on Moscow Mountain in Latah County, ID. Predictors used to make the map are elevation, aspect, canopy cover, and cold-air pooling.
Categories: Publication; Types: Citation; Tags: Idaho, Latah, Moscow Mountain, biota


map background search result map search result map Linear-referenced Geomorphology and Relative Vulnerability to Erosion at the 2013 – 2014 conterminous U.S. Pacific Ocean National Hydrography Dataset Coastline Historical Stream Fish Distribution Database for the Conterminous United States (1950-1990): IchthyMaps NHD Swamp/Marsh for the Great Plains Landscape Conservation Cooperative (COPY) 2012 Air and Temperature Data from Shenandoah National Park Wintering sandhill crane exposure to wind energy development in the central and southern Great Plains, USA datasets Probability distribution grids of dissolved oxygen and dissolved manganese concentrations at selected thresholds in drinking water depth zones, Central Valley, California Soil Moisture Data for the Red River and Rio Grande Basins from 2015-2019 Climate drivers of rapid ecological change at the landscape scale over the last 21,000 years in the Middle and Southern Rockies, U.S.A. Snow Density Measurements at Remote Camera Stations on Moscow Mountain in Latah County, ID (12/1/20-4/30/21) Attributes of Remote Camera Stations on Moscow Mountain in Latah County, ID, USA (10/20/20-5/30/21) Snow and Wildlife Detections from Remote Camera Stations on Moscow Mountain in Latah County, ID, USA (10/20/20-6/30/21) Environmental Data at Remote Camera Stations on Moscow Mountain in Latah County, ID, USA (10/20/20-5/30/21) Snow Hardness Measurements at Remote Camera Stations on Moscow Mountain in Latah County, ID (12/1/20-4/30-21) Hemispherical Photographs at Remote Camera Stations on Moscow Mountain in Latah County, ID, USA (6/2/21-11/2/21) Map of predicted relative snow disappearance dates across Moscow Mountain in Latah County, ID Climate Change Habitat Scenarios for the Central Valley of California Validation of the "edger" Virtual Snow Stake Locations of Fire Promoting Alien Plants Across the Islands of Hawaii Based on Field Surveys and Museum Collections from 1903-2023 Snow Density Measurements at Remote Camera Stations on Moscow Mountain in Latah County, ID (12/1/20-4/30/21) Attributes of Remote Camera Stations on Moscow Mountain in Latah County, ID, USA (10/20/20-5/30/21) Snow and Wildlife Detections from Remote Camera Stations on Moscow Mountain in Latah County, ID, USA (10/20/20-6/30/21) Environmental Data at Remote Camera Stations on Moscow Mountain in Latah County, ID, USA (10/20/20-5/30/21) Snow Hardness Measurements at Remote Camera Stations on Moscow Mountain in Latah County, ID (12/1/20-4/30-21) Hemispherical Photographs at Remote Camera Stations on Moscow Mountain in Latah County, ID, USA (6/2/21-11/2/21) Validation of the "edger" Virtual Snow Stake Climate Change Habitat Scenarios for the Central Valley of California 2012 Air and Temperature Data from Shenandoah National Park Probability distribution grids of dissolved oxygen and dissolved manganese concentrations at selected thresholds in drinking water depth zones, Central Valley, California Linear-referenced Geomorphology and Relative Vulnerability to Erosion at the 2013 – 2014 conterminous U.S. Pacific Ocean National Hydrography Dataset Coastline Wintering sandhill crane exposure to wind energy development in the central and southern Great Plains, USA datasets Soil Moisture Data for the Red River and Rio Grande Basins from 2015-2019 Climate drivers of rapid ecological change at the landscape scale over the last 21,000 years in the Middle and Southern Rockies, U.S.A. Locations of Fire Promoting Alien Plants Across the Islands of Hawaii Based on Field Surveys and Museum Collections from 1903-2023 NHD Swamp/Marsh for the Great Plains Landscape Conservation Cooperative (COPY) Historical Stream Fish Distribution Database for the Conterminous United States (1950-1990): IchthyMaps