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These data represent modeled stream temperatures for a portion of a larger dataset known as the Great Northern Landscape Conservation Cooperative (GNLCC) (https://www.fws.gov/science/catalog). This metadata record is a combined description for two spatial data feature types, vector lines and points, which cover the same geographic area. The line features are derived from NHDPlus (http://www.horizon-systems.com/NHDPlus/index.php) (USEPA and USGS, 2010) stream lines and the point data represent 1 km intervals along the NHDPlus stream network. Both datasets contain identical modeled stream temperature attributes. These modeled stream temperatures were generated as part of the U.S. Forest Service NorWeST stream temperature...
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These data represent stream temperature observation locations for a portion of a larger study area known as the Great Northern Landscape Conservation Cooperative (GNLCC) https://www.fws.gov/science/catalog. These data were collected and processed as part of the NorWeST stream temperature project http://www.fs.fed.us/rm/boise/AWAE/projects/NorWeST.htmlThese thermograph locations and the attendant temperature observations were used as the baseline data for the NorWeST stream temperature modeling project. As a result, modeled temperatures will be most reliable in areas with the greatest density of thermographs. These data reside in ESRI shapefile format, ArcGIS version 9.3. The point shapefile extents correspond to...
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This layer represents 5-year relative counts of wildlife carcasses collected by Montana Department of Transportation (MDT) maintenance personnel or U.S. Fish & Wildlife Service Grizzly Bear Recovery Team personnel on or adjacent to on-system (major) routes from 2008 to 2012. To obtain relative counts, the 5-year total counts per mile, which included all wildlife species observed, were divided by the maximum observed calue (98) to give a relative 0-1 risk score. Total counts, which include all wildlife species observed, along with carnivore counts, which include only black bears, grizzly bears, mountain lions, and wolves, are provided. Counts were derived by identifying the nearest mile marker to each carcass point...
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This project had two primary goals: 1) To develop a process for integrating data from multiple sources to improve predictions of climate impacts for wildlife species; and 2) To provide data on climate and related hydrological change, fire behavior under future climates, and species’ distributions for use by researchers and resource managers.We present within this report the process used to integrate species niche models, fire simulations, and vulnerability assessment methods and provide species’ reports that summarize the results of this work. Species niche model analysis provides information on species’ distributions under three climate scenarios and time periods. Niche model analysis allows us to estimate the...
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These heatmaps show a top 3 invasive and problematic plant stressor for riparian areas in the Chihuahuan Desert, as ranked by participants, and the concentration of participants who reported as working in each municipality or county who also voted for that stressor across the landscape. Symbology represents the percentage of participants with 0% = dark green, 0.0001 % - 24.99% = light green, 25% - 49.99% = yellow, 50% - 74.99% = orange, 75% - 100% = red. All counties and municipalities identified by participants as areas where they work were given a tally for each of the top 3 stressors that participants chose. Counties with a small number of participants were not adjusted for small sample size. These results were...
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These heatmaps show a top 3 riparian ecosystem functionality stressor, as ranked by participants, and the concentration of participants who reported as working in each municipality or county who also voted for that stressor across the landscape. Symbology represents the percentage of participants with 0% = dark green, 0.0001 % - 24.99% = light green, 25% - 49.99% = yellow, 50% - 74.99% = orange, 75% - 100% = red. All counties and municipalities identified by participants as areas where they work were given a tally for each of the top 3 stressors that participants chose. Counties with a small number of participants were not adjusted for small sample size. These results were shared via a webinar hosted by the Desert...
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The Great Plains Landscape Conservation Cooperative (GPLCC, https://www.fws.gov/science/catalog) is a partnership that provides applied science and decision support tools to assist natural resource managers conserve plants, fish and wildlife in the mid- and short-grass prairie of the southern Great Plains. It is part of a national network of public-private partnerships — known as Landscape Conservation Cooperatives (LCCs, http://www.fws.gov/science/shc/lcc.html) — that work collaboratively across jurisdictions and political boundaries to leverage resources and share science capacity. The Great Plains LCC identifies science priorities for the region and helps foster science that addresses these priorities to support...
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The Great Plains Landscape Conservation Cooperative (GPLCC, https://www.fws.gov/science/catalog) is a partnership that provides applied science and decision support tools to assist natural resource managers conserve plants, fish and wildlife in the mid- and short-grass prairie of the southern Great Plains. It is part of a national network of public-private partnerships — known as Landscape Conservation Cooperatives (LCCs, http://www.fws.gov/science/shc/lcc.html) — that work collaboratively across jurisdictions and political boundaries to leverage resources and share science capacity. The Great Plains LCC identifies science priorities for the region and helps foster science that addresses these priorities to support...
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The Great Plains Landscape Conservation Cooperative (GPLCC, https://www.fws.gov/science/catalog) is a partnership that provides applied science and decision support tools to assist natural resource managers conserve plants, fish and wildlife in the mid- and short-grass prairie of the southern Great Plains. It is part of a national network of public-private partnerships — known as Landscape Conservation Cooperatives (LCCs, http://www.fws.gov/science/shc/lcc.html) — that work collaboratively across jurisdictions and political boundaries to leverage resources and share science capacity. The Great Plains LCC identifies science priorities for the region and helps foster science that addresses these priorities to support...
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These data represent 1 sq. mile Hexagons and are derived from the Western Governors Association Crucial Habitat Assessment Tool. The hexagons have been attributed with summary values from the datasets described above. Field names correspond to the number datasets above as follows: {1:’wetland_deds’, 2:’wetland_ceds’, 3:’cropland_ceds’, 4:’lasp_grsp_casp_suit’, 5:’lasp_grsp_suit’, 6:’riparian_suit’, 7:’mean_sat_thick_ft’, 8:’tillage_suit’, 9:’wind_suit’, 10:’ann_aq_deplet_ft’, 11:’wetland_deds_2040’, 12:’wetland_ceds_2040’, 13:’lbgrasslands_2017’, 14:’lbgrasslands_2022’, 15:’lbgrasslands_2027’, 16:’mean_sat_thick_2050_ft’, 17:’tillage_suit_2050’}. Zonal statistic attribution methods are as follows: {1:’SUM’, 2:’SUM’,...
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The Great Plains Landscape Conservation Cooperative (GPLCC, https://www.fws.gov/science/catalog) is a partnership that provides applied science and decision support tools to assist natural resource managers conserve plants, fish and wildlife in the mid- and short-grass prairie of the southern Great Plains. It is part of a national network of public-private partnerships — known as Landscape Conservation Cooperatives (LCCs, http://www.fws.gov/science/shc/lcc.html) — that work collaboratively across jurisdictions and political boundaries to leverage resources and share science capacity. The Great Plains LCC identifies science priorities for the region and helps foster science that addresses these priorities to support...
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Fort Hays State University, Kansas massasauga data for the Great Plains Landscape Conservation Cooperative (GPLCC) Landscape Conservation Design (LCD) pilot area.
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The U.S. Geological Survey (USGS) has compiled national shoreline data for more than 20 years to document coastal change and serve the needs of research, management, and the public. Maintaining a record of historical shoreline positions is an effective method to monitor national shoreline evolution over time, enabling scientists to identify areas most susceptible to erosion or accretion. These data can help coastal managers and planners understand which areas of the coast are vulnerable to change. This data release includes one new mean high water (MHW) shoreline extracted from lidar data collected in 2017 for the entire coastal region of North Carolina which is divided into four subregions: northern North Carolina...
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The U.S. Geological Survey (USGS) has compiled national shoreline data for more than 20 years to document coastal change and serve the needs of research, management, and the public. Maintaining a record of historical shoreline positions is an effective method to monitor national shoreline evolution over time, enabling scientists to identify areas most susceptible to erosion or accretion. These data can help coastal managers and planners understand which areas of the coast are vulnerable to change. This data release includes one new mean high water (MHW) shoreline extracted from lidar data collected in 2017 for the entire coastal region of North Carolina which is divided into four subregions: northern North Carolina...
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A model of the lower seismogenic depth distribution of earthquakes in the western United States was developed to support models for seismic hazard assessment that will be included in the 2023 USGS National Seismic Hazard Model. This data release presents a recalibration using the hypocentral depths of events M>1 from the Advanced National Seismic System Comprehensive Earthquake Catalog from 1980 to 2021. For higher precision and better resolution in the model, the data were supplemented with seismicity from southern California that was relocated by Hauksson and others (2012). Along the San Andreas Fault, the deepest seismogenic depths are located at 23 km around the Cholame segment, whereas the shallowest depths...
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Using the horizontal-to-vertical spectral-ratio (HVSR) method, we infer regolith thickness (i.e., depth to bedrock) throughout the Farmington River Watershed, CT, USA. Between Nov. 2019 and Nov. 2020, MOHO Tromino Model TEP-3C (MOHO, S.R.L.) three-component seismometers collected passive seismic recordings along the Farmington River and the upstream West Branch of Salmon Brook. From these recordings, we derived resonance frequencies using the GRILLA software (MOHO, S.R.L.), and then inferred potential regolith thicknesses based on likely shear wave velocities, Vs, intrinsic to the underlying sediment. Three potential shear wave velocities (Vs = 300m/s, 337m/s, 362 m/s) were considered for Farmington River watershed...
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During the spring and summer of 2022, the U.S. Geological Survey collected water-quality samples for nutrient analysis at 45 stations across the state of Connecticut and adjacent areas of New York and Rhode Island to better understand the groundwater discharge component of nitrogen loading to the Long Island Sound. The targeted stations were located in small drainage basins (less than 50 square kilometers) in the southern portion of the Long Island Sound watershed. Sites were selected randomly from groups based on expected drivers or controls on baseflow nitrogen loads. Factors used in the grouping included four metrics calculated for the upstream watershed: percent impervious cover, septic system density, percent...
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In 2012, Hurricane Sandy struck the Northeastern US causing devastation among coastal ecosystems. Post-hurricane marsh restoration efforts have included sediment deposition, planting of vegetation, and restoring tidal hydrology. The work presented here is part of a larger project funded by the National Fish and Wildlife Foundation (NFWF) to monitor the post-restoration ecological resilience of coastal ecosystems in the wake of Hurricane Sandy. The U.S. Geological Survey Woods Hole Coastal and Marine Science Center made in-situ observations during 2018-2019 and 2022-2023 at two sites: Thompsons Beach, NJ and Stone Harbor, NJ. Marsh creek hydrodynamics and water quality including currents, waves, water levels, water...
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This dataset consists of 122 magnetotelluric (MT) soundings collected in 2016 in the northern Harrat Rahat, located near the holy city of Al-Madinah Al-Munawarah in Saudi Arabia. These data were collected as part of a joint project between the U.S. Geological Survey and the Saudi Geological Survey examining the volcanic hazard associated with the harrat. Imaging the 3-D electrical resistivity structure of the crust and upper mantle beneath the harrat will help in understanding the magmatic system at depth.


map background search result map search result map Coalbed Methane Field Boundaries 2007 for the Great Plains Landscape Conservation Cooperative Coalbed Methane Reserves and Production in 2006 for the Great Plains Landscape Conservation Cooperative Oil and Gas Fields for the Great Plains Landscape Conservation Cooperative PLJV's Probable Playas Version 4 NorWeST Predicted Stream Temp Lines Upper Snake Bear NorWeST Observed Temp Points Upper Snake Bear Road-Killed Wildlife Carcass Frequency by Mile of Montana On-System Routes in the U.S. Northern Rockies (2008-2012) Fort Hayes State University - Massasauga Collections Final Report: Vulnerability of Riparian Obligate Species in the Rio Grande to the Interactive Effects of Fire, Hydrological Variation and Climate Change Conservation Parcels Scored - Rio Mora Crucial Habitat Assessment Magnetotelluric data from northern Harrat Rahat, Saudi Arabia, 2016 Ecosystem Functionality Stressors for Riparian Areas in the Chihuahuan Desert Invasive and Problematic Plant Stressors for Riparian Areas in the Chihuahuan Desert Data release for the lower seismogenic depth model of western U.S. earthquakes Passive seismic depth to bedrock data collected along streams of the Farmington River watershed, CT, USA Unvegetated to vegetated ratio at Thompsons Beach and Stone Harbor, New Jersey from 2014 to 2018 Nitrogen Loads, Yields, and Associated Field Data Collected During Baseflow Conditions and Site Attributes for Small Basins Draining to Long Island Sound Baseline for the North Carolina coastal region from Cape Hatteras to Cape Lookout (NCcentral) Long and short-term shoreline change rate transects for the northern North Carolina coastal region (NCnorth), calculated with and without the proxy-datum bias using the Digital Shoreline Analysis System version 5.1 NSHM2025_EQGeoDB_PRVI_v1 shapefile Passive seismic depth to bedrock data collected along streams of the Farmington River watershed, CT, USA Unvegetated to vegetated ratio at Thompsons Beach and Stone Harbor, New Jersey from 2014 to 2018 Fort Hayes State University - Massasauga Collections Long and short-term shoreline change rate transects for the northern North Carolina coastal region (NCnorth), calculated with and without the proxy-datum bias using the Digital Shoreline Analysis System version 5.1 Baseline for the North Carolina coastal region from Cape Hatteras to Cape Lookout (NCcentral) Magnetotelluric data from northern Harrat Rahat, Saudi Arabia, 2016 Nitrogen Loads, Yields, and Associated Field Data Collected During Baseflow Conditions and Site Attributes for Small Basins Draining to Long Island Sound Coalbed Methane Field Boundaries 2007 for the Great Plains Landscape Conservation Cooperative Oil and Gas Fields for the Great Plains Landscape Conservation Cooperative Final Report: Vulnerability of Riparian Obligate Species in the Rio Grande to the Interactive Effects of Fire, Hydrological Variation and Climate Change NSHM2025_EQGeoDB_PRVI_v1 shapefile Conservation Parcels Scored - Rio Mora Crucial Habitat Assessment Road-Killed Wildlife Carcass Frequency by Mile of Montana On-System Routes in the U.S. Northern Rockies (2008-2012) NorWeST Observed Temp Points Upper Snake Bear NorWeST Predicted Stream Temp Lines Upper Snake Bear PLJV's Probable Playas Version 4 Coalbed Methane Reserves and Production in 2006 for the Great Plains Landscape Conservation Cooperative Ecosystem Functionality Stressors for Riparian Areas in the Chihuahuan Desert Invasive and Problematic Plant Stressors for Riparian Areas in the Chihuahuan Desert Data release for the lower seismogenic depth model of western U.S. earthquakes