AndreaBozzo/ceres-open-data-index huggingface dataset:
Serpentoviruses in free-ranging invasive pythons and native colubrids in southern Florida, United States, 2018-2020

The presence of serpentoviruses in Burmese pythons (Python bivittatus)  and native snakes were collected and compiled to characterize serpentovirus in wild free-ranging pythons and free-ranging native snakes within the invasive range of the pythons in southern Florida. Virus presence was tested in 318 pythons and 219 Native snakes, primarily within the Greater Everglades Ecosystem of south Florida. When available, variables collected from submitted samples used for analysis included sampling date, sampling season (Summer/Fall/Winter/Spring), capture date, sample number (if tested more than once), reverse transcription polymerase chain reaction (rtPCR) result (positive/negative), virus type (categorical), sex (male/female), snout-vent length (centimeters), mass (grams), oral mucosal appearance, capture coordinates (Universal Transversal Mercator [UTM] Easting [CaptureUTMx] and Northing [CaptureUTMy]), and capture subpopulation designation (categorical). Snake samples were provided through various local, state, and federal organizations, including the United States Geological Survey (USGS), National Park Service (NPS), United States Department of Agriculture (USDA), the Conservancy of Southwest Florida (CSF), and the Florida Fish and Wildlife Conservation Commission (FWC).

Tags: climatologymeteorologyatmosphere, greater-everglades-ecosystem, invasive-species, southern-florida, usgs-63658cead34ebe442507d0ee
Organization: Department of the Interior
Delaware River Basin Stream Salinity Machine Learning Models and Data

This model archive contains the input data, model code, and model outputs for machine learning models that predict daily non-tidal stream salinity (specific conductance) for a network of 459 modeled stream segments across the Delaware River Basin (DRB) from 1984-09-30 to 2021-12-31. There are a total of twelve models from combinations of two machine learning models (Random Forest and Recurrent Graph Convolution Neural Networks), two training/testing partitions (spatial and temporal), and three input attribute sets (dynamic attributes, dynamic and static attributes, and dynamic attributes and a minimum set of static attributes). In addition to the inputs and outputs for non-tidal predictions provided on the landing page, we also provide example predictions for models trained with additional tidal stream segments within the model archive (TidalExample folder), but we do not recommend our models for this use case. Model outputs contained within the model archive include performance metrics, plots of spatial and temporal errors, and Shapley (SHAP) explainable artificial intelligence plots for the best models. The results of these models provide insights into DRB stream segments with elevated salinity, and processes that drive stream salinization across the DRB, which may be used to inform salinity management.
This data compilation was funded by the USGS.

Tags: de, deep-learning, delaware, environment, explainable-ai-xai, inlandwaters, machine-learning, maryland, md, modeling, new-jersey, new-york, nj, ny, pa, pennsylvania, salinity, stream-salinity, united-states, us, usgs-6365866cd34ebe442507d0c7, water, water-resources
Organization: Department of the Interior
Household survey data about participation in wildfire risk mitigation cost-share in western Colorado 2013-2017

Household survey data about participation in wildfire risk mitigation cost-share programs and related questions, including stated barriers to conducting wildfire risk mitigation, basic demographics, and willingness to pay toward that cost-share program. Data (n=1,689) were collected in 95 communities exposed to wildfire risk in six counties in western Colorado, 2013-2017, with an overall survey response rate of 41.9%. The household surveys providing data were organized and implemented by two regional wildfire risk mitigation organizations, West Region Wildfire Council and Wildfire Adapted Partnership (formerly Firewise of Southwest Colorado).

Tags: archuleta, colorado, delta, equity, financial-assistance, la-plata, montezuma, natural-hazards, ouray, san-miguel, social-vulnerability, society, statistical-surveying, usgs-636583abd34ebe442507d0ab, wildfire, willingness-to-pay
Organization: Department of the Interior
Russian River Integrated Hydrologic Model (RRIHM): Watershed Lakes

This data release is a subset of the National Hydrography Dataset (NHD) water bodies, specifically lakes Mendocino and Sonoma in the Russian River watershed. 
The National Hydrography Dataset (NHD) is a feature-based database that interconnects and uniquely identifies the stream segments or reaches that make up the nation's surface water drainage system. NHD data was originally developed at 1:100,000-scale and exists at that scale for the whole country. This high-resolution NHD, generally developed at 1:24,000/1:12,000 scale, adds detail to the original 1:100,000-scale NHD. (Data for Alaska, Puerto Rico and the Virgin Islands was developed at high-resolution, not 1:100,000 scale.) Local resolution NHD is being developed where partners and data exist. The NHD contains reach codes for networked features, flow direction, names, and centerline representations for areal water bodies. Reaches are also defined on waterbodies and the approximate shorelines of the Great Lakes, the Atlantic and Pacific Oceans and the Gulf of Mexico. The NHD also incorporates the National Spatial Data Infrastructure framework criteria established by the Federal Geographic Data Committee.
The National Hydrography Dataset is a comprehensive set of digital spatial data that encodes information about naturally occurring and constructed bodies of water, paths through which water flows, and related entities. The information encoded about features includes a feature date, classification by type, other characteristics, a unique common identifier, the feature length or area, and (rarely) elevation of the surface of water pools and a description of the stage of the elevation. For reaches, encoded information includes a reach code. Names and their identifiers in the Geographic Names Information System, are assigned to most feature types. The direction of flow is encoded for networked features. The data also contains relations that encode metadata, and information that supports the exchange of future updates and improvements to the data. The names and definitions of all feature types, characteristics, and values are in the Standards for National Hydrography Dataset: Reston, Virginia, U.S. Geological Survey, 1999. The document is available online through http://mapping.usgs.gov/standards/.
The names and definitions of all feature types, characteristics, and values are in U.S. Geological Survey, 1999, Standards for National Hydrography Dataset High Resolution: Reston, Virginia, U.S. Geological Survey. The document is available online through http://mapping.usgs.gov/standards/. Information about tables and fields in the data are available from the user documentation for the National Hydrography Dataset at http://nhd.usgs.gov. The National Map - Hydrography Fact Sheet is also available at: http://erg.usgs.gov/isb/pubs/factsheets/fs06002.html.

Tags: california, environment, hydrology, inlandwaters, modeling, russian-river, united-states, usgs-63655019d34ebe442507d022, water-resources
Organization: Department of the Interior
Groundwater, surface water, and soil data collected near and at the Ammonium Perchlorate Rocket Motor Destruction (ARMD) facility at the Letterkenny Army Depot, Chambersburg, Pennsylvania

Sampling was conducted by the U.S. Geological Survey (USGS) at four wells, one surface water site, and five soil sampling locations near and at the Ammonium Perchlorate Rocket Motor Destruction (ARMD) facility at the Letterkenny Army Depot. Analytical results for groundwater samples collected in 2021 are provided in “ARMD_wells_data_2021.xlsx”. Analytical results for surface-water samples collected in 2021 are provided in “ARMD_sw_data_2021.xlsx”. Analytical results for soil samples collected in 2021 are provided in “ARMD_soil_data_2021.xlsx”. The data files with analytical results also include quality assurance/quality control sample results.

Tags: environment, franklin-coumty, groundwater-quality, pennsylvania, soil-chemistry-quality, surface-water-quality, usgs-63652207d34ebe442507cee8
Organization: Department of the Interior
Washington White-Tailed Deer Selkirk Winter Range

The Selkirk White-tailed Deer Management Zone (WDMZ) is home to the largest population of white-tailed deer in the state and consists of seven Game Management Units (GMU; GMUs 105, 108, 111, 113, 117, 121, and 124) located in northeast Washington. Aside from the southern portion of GMU 124, dominated by the metropolitan area of Spokane, Washington, most of these GMUs have similar rural characteristics. Private landowners manage most of the Selkirk WDMZ (77 percent), primarily for commercial timber harvest. The U.S. Forest Service manages 16 percent of the land, and the U.S. Fish and Wildlife Service, Department of Natural Resources, and Bureau of Land Management manage the remaining 7 percent. White-tailed deer used in this analysis were captured on their winter range in GMUs 117 and 121, where the habitat consists of conifer forest (65 percent of the total land cover within the area) and shrub land. Grassland, pasture, and cultivated crops make up the next highest land cover types (altogether comprising nearly 21 percent of the Selkirk WDMZ). Agriculture in the valley supports high densities of deer adjacent to U.S. Highway 395, which bisects the Selkirk WDMZ from north to south. This white-tailed deer population experiences some of the highest rates of deer-vehicle collisions in the state (Myers and others 2008; G. Kalisz, Washington Department of Transportation, written commun.). Currently, there are no crossing mitigations in place along U.S. Highway 395 and State Route 20 to curtail collisions with wildlife. Other wildlife-human management challenges for this herd include mitigating crop damage complaints, maximizing hunting opportunity, and encroaching human development on the deer’s winter range.
These mapping layers show the location of the winter ranges for White-Tailed Deer (odocoileus virginianus) in the Selkirk population in Washington. They were developed from 149 winter sequences collected from a sample size of 94 animals comprising GPS locations collected every 4 hours.

Tags: animal-behavior, biota, migration-organisms, migration-route, migratory-species, spokane, united-states, usgs-63650c6bd34ebe442507cec5, washington
Organization: Department of the Interior
Washington White-Tailed Deer Selkirk Stopovers

The Selkirk White-tailed Deer Management Zone (WDMZ) is home to the largest population of white-tailed deer in the state and consists of seven Game Management Units (GMU; GMUs 105, 108, 111, 113, 117, 121, and 124) located in northeast Washington. Aside from the southern portion of GMU 124, dominated by the metropolitan area of Spokane, Washington, most of these GMUs have similar rural characteristics. Private landowners manage most of the Selkirk WDMZ (77 percent), primarily for commercial timber harvest. The U.S. Forest Service manages 16 percent of the land, and the U.S. Fish and Wildlife Service, Department of Natural Resources, and Bureau of Land Management manage the remaining 7 percent. White-tailed deer used in this analysis were captured on their winter range in GMUs 117 and 121, where the habitat consists of conifer forest (65 percent of the total land cover within the area) and shrub land. Grassland, pasture, and cultivated crops make up the next highest land cover types (altogether comprising nearly 21 percent of the Selkirk WDMZ). Agriculture in the valley supports high densities of deer adjacent to U.S. Highway 395, which bisects the Selkirk WDMZ from north to south. This white-tailed deer population experiences some of the highest rates of deer-vehicle collisions in the state (Myers and others 2008; G. Kalisz, Washington Department of Transportation, written commun.). Currently, there are no crossing mitigations in place along U.S. Highway 395 and State Route 20 to curtail collisions with wildlife. Other wildlife-human management challenges for this herd include mitigating crop damage complaints, maximizing hunting opportunity, and encroaching human development on the deer’s winter range.
These mapping layers show the location of the migration stopovers for White-Tailed Deer (odocoileus virginianus) in the Selkirk population in Washington. They were developed from 121 migration sequences collected from a sample size of 43 animals comprising GPS locations collected every 4 hours.

Tags: animal-behavior, biota, migration-organisms, migration-route, migratory-species, spokane, united-states, usgs-63650c67d34ebe442507cec3, washington
Organization: Department of the Interior
Northern California 3.2 projections of coastal cliff retreat due to 21st century sea-level

This dataset contains projections of coastal cliff retreat and associated uncertainty across Northern California for future scenarios of sea-level rise (SLR) to include 25, 50, 75, 100, 125, 150, 175, 200, 250, 300, and 500 centimeters (cm) of SLR by the year 2100 and cover coastline from the Golden Gate Bridge to the California-Oregon state border. Present-day cliff-edge positions used as the baseline for projections are also included. Projections were made using numerical models and field observations such as historical cliff retreat rate, nearshore slope, coastal cliff height, and mean annual wave power, as part of Coastal Storm Modeling System (CoSMoS). See cited references and methods for more detail.

Tags: climate-change, climatologymeteorologyatmosphere, cmhrp, coastal-and-marine-hazards-and-resources-program, coastal-erosion, earth-sciences, effects-of-climate-change, erosion, extreme-weather, hazards-planning, mathematical-modeling, northern-california, northern-california-coast, ocean-waves, oceans, pacific-coastal-and-marine-science-center, pcmsc, physical-habitats-and-geomorphology, sea-level-change, sea-level-rise, state-of-california, storms, u-s-geological-survey, usgs, usgs-636d7473d34ed907bf6ba1fc, waves
Organization: Department of the Interior
Washington White-Tailed Deer Selkirk Routes

The Selkirk White-tailed Deer Management Zone (WDMZ) is home to the largest population of white-tailed deer in the state and consists of seven Game Management Units (GMU; GMUs 105, 108, 111, 113, 117, 121, and 124) located in northeast Washington. Aside from the southern portion of GMU 124, dominated by the metropolitan area of Spokane, Washington, most of these GMUs have similar rural characteristics. Private landowners manage most of the Selkirk WDMZ (77 percent), primarily for commercial timber harvest. The U.S. Forest Service manages 16 percent of the land, and the U.S. Fish and Wildlife Service, Department of Natural Resources, and Bureau of Land Management manage the remaining 7 percent. White-tailed deer used in this analysis were captured on their winter range in GMUs 117 and 121, where the habitat consists of conifer forest (65 percent of the total land cover within the area) and shrub land. Grassland, pasture, and cultivated crops make up the next highest land cover types (altogether comprising nearly 21 percent of the Selkirk WDMZ). Agriculture in the valley supports high densities of deer adjacent to U.S. Highway 395, which bisects the Selkirk WDMZ from north to south. This white-tailed deer population experiences some of the highest rates of deer-vehicle collisions in the state (Myers and others 2008; G. Kalisz, Washington Department of Transportation, written commun.). Currently, there are no crossing mitigations in place along U.S. Highway 395 and State Route 20 to curtail collisions with wildlife. Other wildlife-human management challenges for this herd include mitigating crop damage complaints, maximizing hunting opportunity, and encroaching human development on the deer’s winter range.
These mapping layers show the location of the migration routes for White-Tailed Deer (odocoileus virginianus) in the Selkirk population in Washington. They were developed from 121 migration sequences collected from a sample size of 43 animals comprising GPS locations collected every 4 hours.

Tags: animal-behavior, biota, migration-organisms, migration-route, migratory-species, spokane, united-states, usgs-63650c63d34ebe442507cec1, washington
Organization: Department of the Interior
Washington White-Tailed Deer Selkirk Corridors

The Selkirk White-tailed Deer Management Zone (WDMZ) is home to the largest population of white-tailed deer in the state and consists of seven Game Management Units (GMU; GMUs 105, 108, 111, 113, 117, 121, and 124) located in northeast Washington. Aside from the southern portion of GMU 124, dominated by the metropolitan area of Spokane, Washington, most of these GMUs have similar rural characteristics. Private landowners manage most of the Selkirk WDMZ (77 percent), primarily for commercial timber harvest. The U.S. Forest Service manages 16 percent of the land, and the U.S. Fish and Wildlife Service, Department of Natural Resources, and Bureau of Land Management manage the remaining 7 percent. White-tailed deer used in this analysis were captured on their winter range in GMUs 117 and 121, where the habitat consists of conifer forest (65 percent of the total land cover within the area) and shrub land. Grassland, pasture, and cultivated crops make up the next highest land cover types (altogether comprising nearly 21 percent of the Selkirk WDMZ). Agriculture in the valley supports high densities of deer adjacent to U.S. Highway 395, which bisects the Selkirk WDMZ from north to south. This white-tailed deer population experiences some of the highest rates of deer-vehicle collisions in the state (Myers and others 2008; G. Kalisz, Washington Department of Transportation, written commun.). Currently, there are no crossing mitigations in place along U.S. Highway 395 and State Route 20 to curtail collisions with wildlife. Other wildlife-human management challenges for this herd include mitigating crop damage complaints, maximizing hunting opportunity, and encroaching human development on the deer’s winter range.
These mapping layers show the location of the migration corridors for White-Tailed Deer (odocoileus virginianus) in the Selkirk population in Washington. They were developed from 121 migration sequences collected from a sample size of 43 animals comprising GPS locations collected every 4 hours.

Tags: animal-behavior, biota, migration-organisms, migration-route, migratory-species, spokane, united-states, usgs-63650c60d34ebe442507cebf, washington
Organization: Department of the Interior
Washington Mule Deer Wenatchee Mountains Stopovers

Along the eastern slope of the Cascade Mountains in Chelan and Kittitas counties, the Wenatchee Mountains mule deer herd inhabits a matrix of private and public lands. Historically, the Wenatchee Mountains mule deer were separated into two sub-herds, Chelan and Kittitas; however, recent movement data from GPS-collared individuals associated with Secretarial Order 3362 (Department of the Interior, 2018) revealed that the mule deer south of U.S. Highway 2 and north of Interstate 90 represent one population. Their high-use winter range extends along the foothills west and south of Wenatchee, Washington and throughout the foothills of the Kittitas Valley outside Ellensburg, Washington. The low-use winter range occurs along the foothills west of the Columbia River. In the spring, migratory individuals travel west into the Wenatchee Mountains to their summer range, which includes the Alpine Lakes Wilderness Area. Wenatchee Mountains mule deer are partially migratory; a higher proportion of migratory individuals occupy the northern winter range of the Wenatchee Mountains and non-migratory individuals more commonly inhabit the foothills of the Kittitas Valley. The increasing frequency of large-scale wildfires and residential development continue to degrade and reduce available winter range. Disturbance from human recreation on the winter range continues to be a concern. Semipermeable barriers to spring and fall migration include U.S. Highway 97 or State Route 970, both of which experience relatively high volumes of traffic in the region.
These mapping layers show the location of the migration stopovers for Mule Deer (Odocoileus hemionus) in the Wenatchee Mountains population in Washington. They were developed from 107 migration sequences collected from a sample size of 38 animals comprising GPS locations collected every 4 hours.

Tags: animal-behavior, biota, migration-organisms, migration-route, migratory-species, united-states, usgs-63650c5ad34ebe442507cebb, washington, wenatchee
Organization: Department of the Interior
Washington Mule Deer Wenatchee Mountains Routes

Along the eastern slope of the Cascade Mountains in Chelan and Kittitas counties, the Wenatchee Mountains mule deer herd inhabits a matrix of private and public lands. Historically, the Wenatchee Mountains mule deer were separated into two sub-herds, Chelan and Kittitas; however, recent movement data from GPS-collared individuals associated with Secretarial Order 3362 (Department of the Interior, 2018) revealed that the mule deer south of U.S. Highway 2 and north of Interstate 90 represent one population. Their high-use winter range extends along the foothills west and south of Wenatchee, Washington and throughout the foothills of the Kittitas Valley outside Ellensburg, Washington. The low-use winter range occurs along the foothills west of the Columbia River. In the spring, migratory individuals travel west into the Wenatchee Mountains to their summer range, which includes the Alpine Lakes Wilderness Area. Wenatchee Mountains mule deer are partially migratory; a higher proportion of migratory individuals occupy the northern winter range of the Wenatchee Mountains and non-migratory individuals more commonly inhabit the foothills of the Kittitas Valley. The increasing frequency of large-scale wildfires and residential development continue to degrade and reduce available winter range. Disturbance from human recreation on the winter range continues to be a concern. Semipermeable barriers to spring and fall migration include U.S. Highway 97 or State Route 970, both of which experience relatively high volumes of traffic in the region.
These mapping layers show the location of the migration routes for Mule Deer (Odocoileus hemionus) in the Wenatchee Mountains population in Washington. They were developed from 107 migration sequences collected from a sample size of 38 animals comprising GPS locations collected every 4 hours.

Tags: animal-behavior, biota, migration-organisms, migration-route, migratory-species, united-states, usgs-63650c56d34ebe442507ceb9, washington, wenatchee
Organization: Department of the Interior