These data contain selected census tract level demographic indicators (estimates) from the 2015-2019 American Community Survey representing the population density by square mile (land area).

This dataset represents the prevalence of native species as mapped along the Colorado River bottomland from the Colorado state line (San Juan and Grand Counties, Utah) to the southern Canyonlands NP boundary, as of September 2010. This mapping was conducted as part of the Colorado River Conservation Planning Project, a joint effort between the National Park Service, The Nature Conservancy, US Geological Survey, Bureau of Land Management, and Utah Forestry Fire and State Lands.

Feature class representing retail alcohol outlet density at the Health Statistics Region level developed directly from address information from liquor licensee lists that were obtained from the Colorado Department of Revenue-Liquor Enforcement Division (DOR-LED). This file was developed for use in activities and exercises within the Colorado Department of Public Health and Environment (CDPHE), including the Alcohol Outlet Density StoryMap. CDPHE nor DOR-LED are responsible for data products made using this publicly available data. It should be stated that neither agency is acting as an active data steward of this map service/geospatial data layer at this point in time. This dataset is representative of Colorado licensing data gathered in January 2024. This data file contains the following attributes:Health Statistics RegionCOUNTIES (Counties included in Health Statistics Region)RegionNewYear Total Population (Total population of the HSR)Average County Population (Average county population among counties in the HSRAverage Outlet Count (Average number of retail alcohol outlets among the counties in the HSR)Total Outlet Count (Total number of retail alcohol outlets in the HSR)Average Rate of Outlets per 10,000 Residents (Average rate of alcohol outlets per 10,000 residents among the counties in the HSR)

Canopy Density and Canopy Structure Metrics were derived for the San Juan Mountains of Southwest Colorado from Aerial point cloud data at a 1-meter resolution. The aerial Lidar data originated from the ‘CO_Southwest_NRCS_2018’ project prepared by Quantum Spatial for the USGS from a series of flyovers between 2018 and 2019 and were made available in 2021. Canopy Density metrics include Canopy Closure (CC) and Leaf Area Index (LAI). Canopy Structure metrics include total gap area, mean distance to canopy, canopy edginess to the south and canopy edginess to the north.

Discrete snow data were collected during multiple winter field campaigns from 2021 to 2022. This data was collected as part of the U.S. Geological Survey (USGS) Next Generation Water Observing System (NGWOS) project focusing on the relation between snow dynamics and the water cycle of a basin. A Snow Water Equivalent (SWE) Coring Tube was used to measure snow depth and mass of snow within the core. These values were used to calculate snow density and snow water equivalent of the core. These data were released in a comma separated value file.

This dataset represents the prevalence of tamarisk as mapped along the Colorado River bottomland from the Colorado state line (San Juan and Grand Counties, Utah) to the southern Canyonlands NP boundary, as of September 2010. photos, this cover layer reflects conditions that existed when the imagery was collected (September, 2010). This mapping was conducted as part of the Colorado River Conservation Planning Project, a joint effort between the National Park Service, The Nature Conservancy, US Geological Survey, Bureau of Land Management, and Utah Forestry Fire and State Lands.

This dataset represents the relative abundance of non-native, herbaceous cover types in vegetation patches, as mapped from high resolution imagery from 2010. This mapping was conducted as part of the Colorado River Conservation Planning Project, a joint effort between the National Park Service, The Nature Conservancy, US Geological Survey, Bureau of Land Management, and Utah Forestry Fire and State Lands.

This dataset represents the prevalence of native trees as mapped along the Colorado River bottomland from the Colorado state line (San Juan and Grand Counties, Utah) to the southern Canyonlands NP boundary, as of September 2010. This mapping was conducted as part of the Colorado River Conservation Planning Project, a joint effort between the National Park Service, The Nature Conservancy, US Geological Survey, Bureau of Land Management, and Utah Forestry Fire and State Lands.

This dataset is of numerous snow pits that were dug in the spring of 2014 in the Dry Lake study site in northern Colorado. Within each pit bulk measurements were taken for snow depth, snow density, and soil moisture content directly beneath the working face of the pit. Snow density was measured using a snow tube to obtain a single core that was then placed in a bucket and measured for mass and depth was measured using markings on the snow tube to the nearest centimeter. Soil moisture was measured using a handheld TDR for volumetric water content. Volumetric soil samples were taken from test locations for lab confirmation and calibration of field measured data. Location are UTM coordinates in UTM 13N NAD83 datum.

This dataset represents the relative abundance of non-native, woody cover types in vegetation patches, as mapped from high resolution imagery from 2010. This mapping was conducted as part of the Colorado River Conservation Planning Project, a joint effort between the National Park Service, The Nature Conservancy, US Geological Survey, Bureau of Land Management, and Utah Forestry Fire and State Lands.

These data were compiled for research pertaining to the effects of stand density on growth rates in semi-arid forests. Increasing heat and aridity in coming decades is expected to negatively impact tree growth and threaten forest sustainability in dry areas. Maintaining low stand density has the potential to mitigate the negative effects of increasingly severe droughts by minimizing competitive intensity. By inspecting growth rates and the climate and soil moisture conditions that drive these growth rates we can understand better the positive effects of reducing stand density and the specific dynamics that are beneficial to growth.

This resource is a member of a series. The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Census tracts are small, relatively permanent statistical subdivisions of a county or equivalent entity, and were defined by local participants as part of the 2020 Census Participant Statistical Areas Program. The Census Bureau delineated the census tracts in situations where no local participant existed or where all the potential participants declined to participate. The primary purpose of census tracts is to provide a stable set of geographic units for the presentation of census data and comparison back to previous decennial censuses. Census tracts generally have a population size between 1,200 and 8,000 people, with an optimum size of 4,000 people. When first delineated, census tracts were designed to be homogeneous with respect to population characteristics, economic status, and living conditions. The spatial size of census tracts varies widely depending on the density of settlement. Physical changes in street patterns caused by highway construction, new development, and so forth, may require boundary revisions. In addition, census tracts occasionally are split due to population growth, or combined as a result of substantial population decline. Census tract boundaries generally follow visible and identifiable features. They may follow legal boundaries such as minor civil division (MCD) or incorporated place boundaries in some States and situations to allow for census tract-to-governmental unit relationships where the governmental boundaries tend to remain unchanged between censuses. State and county boundaries always are census tract boundaries in the standard census geographic hierarchy. In a few rare instances, a census tract may consist of noncontiguous areas. These noncontiguous areas may occur where the census tracts are coextensive with all or parts of legal entities that are themselves noncontiguous. For the 2010 Census, the census tract code range of 9400 through 9499 was enforced for census tracts that include a majority American Indian population according to Census 2000 data and/or their area was primarily covered by federally recognized American Indian reservations and/or off-reservation trust lands; the code range 9800 through 9899 was enforced for those census tracts that contained little or no population and represented a relatively large special land use area such as a National Park, military installation, or a business/industrial park; and the code range 9900 through 9998 was enforced for those census tracts that contained only water area, no land area.

This dataset represents the prevalence of non-native vegetation species as mapped along the Colorado River bottomland from the Colorado state line (San Juan and Grand Counties, Utah) to the southern Canyonlands NP boundary, as of September 2010. This mapping was conducted as part of the Colorado River Conservation Planning Project, a joint effort between the National Park Service, The Nature Conservancy, US Geological Survey, Bureau of Land Management, and Utah Forestry Fire and State Lands.

No description is available. Visit https://dataone.org/datasets/916b92eba70112a359ec4f87d74b842c for complete metadata about this dataset.

This data package was produced by researchers working on the Shortgrass Steppe Long Term Ecological Research (SGS-LTER) Project, administered at Colorado State University. Long-term datasets and background information (proposals, reports, photographs, etc.) on the SGS-LTER project are contained in a comprehensive project collection within the Digital Collections of Colorado (http://digitool.library.colostate.edu/R/?func=collections&collection_id=3429). The data table and associated metadata document, which is generated in Ecological Metadata Language, may be available through other repositories serving the ecological research community and represent components of the larger SGS-LTER project collection. Six sites approximately 6 km apart were selected at the Central Plains Experimental Range in 1997. Within each site, there was a pair of adjacent ungrazed and moderately summer grazed (40-60% removal of annual aboveground production by cattle) locations. Grazed locations had been grazed from 1939 to present and ungrazed locations had been protected from 1991 to present by the establishment of exclosures. Within grazed and ungrazed locations, all tillers and root crowns of B. gracilis were removed from two treatment plots (3 m x 3 m) with all other vegetation undisturbed. Two control plots were established adjacent to the treatment plots. Plant density was measured annually by species in a fixed 1m x 1m quadrat in the center of treatment and control plots. For clonal species, an individual plant was defined as a group of tillers connected by a crown (Coffin and Lauenroth 1988, Fair et al. 1999). Seedlings were counted as separate individuals. In the same quadrat, basal cover by species, bare soil, and litter were estimated annually using a point frame. A total of 40 points were read from four locations halfway between the center point and corners of the 1m x 1m quadrat. Density was measured from 1998 to 2005 and cover from 1997 to 2006. All measurements were taken in late June/early July. Resources in this dataset:Resource Title: Website Pointer to html file. File Name: Web Page, url: https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-sgs&identifier=703 Webpage with information and links to data files for download

Colorado County BRFSS Binge Drinking Prevalence represents the Percent of Adults who Binge Drink calculated from the 2018-2022 Colorado Behavioral Risk Factor Surveillance System (County Estimates) data set. These data represent the estimated prevalence of Binge Drinking among adults (Age 18+) for each county in Colorado. Binge Drinking is defined for males as having five or more drinks on one occasion and for females as having four or more drinks on one occasion within the past 30 days. Binge Drinking is calculated from the number of days alcohol was consumed in the past 30 days, and the average number of drinks consumed on those days. Data is suppressed if there was not enough data to calculate a reliable estimate. The estimate for each county was derived from multiple years of Colorado Behavioral Risk Factor Surveillance System data (2018-2022). This file was developed for use in activities and exercises within the Colorado Department of Public Health and Environment (CDPHE), including the Alcohol Outlet Density StoryMap. COUNTY (County Name)FULL (Full County Name)LABEL (Proper County Name)County FIPS (County FIPS Code as String)NUM FIPS (County FIPS Code as Number)CENT LAT (County Centroid Latitude)CENT LONG (County Centroid Longitude)US FIPS (Full FIPS Code)Binge Percent (County estimate for prevalence of Binge Drinking among adults Age 18+)Lower Confidence Limit (Lower 95% Confidence Interval for Binge Percent Value)Upper Confidence Limit (Upper 95% Confidence Interval for Binge Percent Value)Years (2018-2022)

The U.S. Geological Survey (USGS) collected rock magnetic susceptibility and density measurements to understand the causative sources of airborne magnetic and ground gravity survey anomalies in the Wet Mountains, Colorado. A total of 609 magnetic susceptibility and 86 density measurements were collected from outcrops and hand samples, respectively, from July 2022 to June 2023. These measurements aid the interpretation of newly collected geophysical data to identify concealed Ediacaran-Ordovician alkaline igneous features and potential rare earth element deposits. On average, 16 magnetic susceptibility and 4 density measurements were taken from each outcrop/hand sample to best represent the lithology. Outcrop/sample lithology was derived from field observations and previously published maps noted in the supplemental information section of the metadata file. Measurement locations were recorded using a handheld Global Position System.

On May 25th, 2014, a 54.5 Mm3 rock avalanche occurred in the West Salt Creek valley in western Colorado following heavy rainfall on top of snow (Coe and others, 2016a). The data in this project includes boulder density in 20-m x 20-m grid cells for the entire West Salt Creek rock avalanche deposit. The grid cells cover 2,154,800 m2, which accounts for nearly the entire surface of the deposit. We estimated boulder density by counting 1-m or larger diameter boulders of sedimentary rock that are visible in high-resolution Unmanned Aircraft System (UAS) imagery collected for the area in July of 2014 (Coe and others, 2016b). Basalt boulders were excluded from the count because field observations indicated that they generally stayed intact as the avalanche moved downslope, whereas the sedimentary boulders showed evidence of fragmentation during downslope movement. Variable clarity, contrast and resolution of the imagery precluded mapping smaller boulders. Experimentation with 5-m, 10-m and 20-m resolution grids showed that 20-m resolution was fine enough to show the spatial pattern of boulder density across the deposit and coarse enough to show statistically meaningful variation in boulder density. The attribute table contains fields containing (1) the boulder count in each grid cell, as well as (2) six categories of successively increasing boulder density. Lewis and others (2022) describe the mapping procedures in greater detail. References cited Lewis, A.C., Baum, R.L., and Coe, J.A., in review, Distribution of large boulders on the deposit of the West Salt Creek rock avalanche, western Colorado: U.S. Geological Survey Data Report 22-XXXX. Coe, J.A., Baum, R.L., Allstadt, K.E., Kochevar, B.F., Jr., Schmitt, R.G., Morgan, M.L., White, J.L., Stratton, B.T., Hayashi, T.A., and Kean, J.W., 2016a, Rock-avalanche dynamics revealed by large-scale field mapping and seismic signals at a highly mobile avalanche in the West Salt Creek valley, western Colorado: Geosphere, v. 12, no. 2, p. 607–631, https://doi.org/10.1130/GES01265.1. Coe, J.A., Baum, R.L., Allstadt, K.E., Kochevar, B.F., Schmitt, R.G., Morgan, M.L., White, J.L., Stratton, B.T., Hayashi, T.A., and Kean, J.W., 2016b, Map data and unmanned aircraft system imagery from the May 25, 2014 West Salt Creek rock avalanche in western Colorado: U.S. Geological Survey data release, http://dx.doi.org/10.5066/F74J0C55.

The USDA-Agricultural Research Service carried out an experiment on water productivity in response to seasonal timing of irrigation of maize (Zea mays L.) at the Limited Irrigation Research Farm (LIRF) facility in northeastern Colorado (40°26’ N, 104°38’ W) starting in 2012. Twelve treatments involved different water availability targeted at specific growth-stages. This dataset includes data from the first two years, which were complete years with intact treatments. Data includes canopy growth and development (canopy height, canopy cover and LAI), irrigation, precipitation, and soil water storage measured periodically through the season; daily estimates of crop evapotranspiration; and seasonal measurement of crop water use, harvest index and crop yield. Hourly and daily weather data are also provided from the CoAgMET, Colorado’s network of meteorological information (https://coagmet.colostate.edu/ ; GLY04 station). Additional soil data can be found in a previous dataset (USDA-ARS Colorado Maize Water Productivity Dataset 2008-2011) also available from the Ag Data Commons. This previous dataset included six targeted treatments that were generally uniform through the season. This new dataset can be used to further validate and refine maize crop models. The data are presented in a spreadsheet format in individual sheets within one workbook. The first sheet in the work book provides a list of data descriptions. Two sheets (one sheet for each of the two years) provide the hourly weather data, with the exception of the precipitation data, which is included in the sheet with daily data per treatment. The weather data is from a weather station on site. Another sheet provides plot level data (harvest index, yield, annual ET, maximum LAI, stand density, total aboveground biomass) taken annually by plot (four plots per treatment). Another sheet provides LAI measured four times over each season per plot. The final sheet provides daily data per treatment over each season, including data needed to compute daily water balance. This sheet has LAI, crop growth stage, plant height, estimated root depth, interpolated canopy cover, ET coefficients, precipitation, and estimated deep percolation, evaporation, and soil water deficit at four soil depths. List of files: LIRF small plots map 2012-2013 LIRF maize annual_daily_hourly data 2012-2013 Resources in this dataset:Resource Title: LIRF 2012-2013 Maize database. File Name: 2012-2013_Maize_Compiled database 06012018.xlsxResource Title: LIRF 2012-2013 Data Description. File Name: Data Description 06012018.xlsxResource Title: LIRF 2012-2013 Plot Map. File Name: Plot map 2012 2013.pdfResource Title: LIRF Data Dictionary. File Name: Data_Dictionary_Water_Prod_2012.csv

Drastic changes in soil physical, chemical, and biotic properties following slash pile burning and their lasting effects on vegetation cover have been well documented in western North American ecosystems. However, processes that inhibit burn scar recovery are poorly understood as are the most effective means for their rehabilitation. This data publication contains the vegetation, soils, and landscape data collected as part of a study to compare plant and soil responses to a number of surface treatments designed to alter microclimate, moisture infiltration, and nutrient status of recently burned slash piles along the Front Range of Colorado. Sites were thinned and slash was hand piled in 2006-2007 and burned during the fall/winter of 2008-2009 by USDA Forest Service crews. Three surface treatments, scarification (scarify), woodchip mulch (chips), or wood slash (branches) were applied with and without the addition of a native species seed mix, with one scar left untreated as a control.

Plant composition data include vegetation cover and above ground biomass, which was assessed in early August of 2010 and 2011. Soils data were assessed between 2009 and 2011 and include soil physical properties (soil structure, bulk density, stability, infiltration, moisture content), chemical properties (carbon, total nitrogen, inorganic nitrogen, cations), and biological properties (decomposition rates). Landscape data, measured in 2010, contain information relating to the landscape context (aspect, slope, elevation, overstory tree basal area) of sites where experimental fire scars were located.The objectives of this study were to 1) assess plant responses to rehabilitation treatments applied to slash pile fire scars, and 2) determine the best approach for restoring soil processes to slash pile fire scars in conifer forests of the Front Range of Colorado where such scars are a prevalent feature.