Microclimate observations associated with snowmelt experiment gradient sites, East River, Colorado, 2017 to 2020 (ess_dive, 2021)
The timing of snowmelt in mountain systems is a main driver of vegetation phenology and production, as well as recharge of soil moisture and ground water. Decreases in maximum snowpack and warmer spring temperatures have led to a higher frequency of early snowmelt. This study combines a natural elevation gradient with an experimental manipulation of snowmelt timing to assess the effect of earlier melt on hillslope and watershed ecohydrological processes. This data package includes csv files with plot and sub-plot level observations of soil temperature (SM_ST.csv), soil moisture (SM_SWC.csv), air temperature (SM_AirT.csv), and relative humidity (SM_rH.csv). The date range of this dataset includes a pre-treatment year (2017), two treatment years (2018 and 2019), and a post-treatment year (2020). Location IDs associated with this data package are: ER-LM, WG-UM, WG-LS, ER-US, and XX-AL. Related data packages include: “Colorado Elevation Gradient Snowmelt Manipulation Plant Phenology 2017-2018” and “Sensor-based phenology from snowmelt experiment gradient, East River, Colorado, 2017 to 2020”

Styled hydrology basemap of the Upper Gunnison domain - Ian K Breckheimer (s3, 2021)
This dataset is a styled basemap depicting hydrologic variables of interest in the Upper Gunnison domain overlaid on high-resolution topography, optimized for fast display on web maps and mobile devices. The underlying datasets are available as part of Release 3 of the RMBL Spatial Data Platform. The color scale for hydrology-related features on this map ranges from gray for dry slopes, light blue for wet slopes and small ephemeral drainages, moderate blue for wet areas and small streams, and dark blue for open water and large streams and rivers. Areas outside of the drainage network are shaded according to the multiscale height-above-stream wetness index. Using this index, areas that have flat topography and are close to the elevation of the local stream network are assumed to be wetter. The download link to this dataset accesses a version of the basemap stored as a Cloud-optimized Geotiff (COG). The web map link accesses a version that can be added to a web map on ArcGIS Online.

Waterlevel, geochemical, and borehole data from Rifle, Colorado from 2006-2016 (ess_dive, 2021)
The files included in this data package provide site wide water level data, geochemical data, and borehole information associated with the Rifle site in Colorado during the Lawrence Berkeley National Lab (LBNL) led Integrated Field Research Challenge (IFRC) and Scientific Focus Area (SFA) research projects. The data informs hydrogeochemical interactions occurring in the watershed. The readme file contains detailed metadata for the files, including naming conventions, column headers, and data validation.The borehole information is provided in the file called rifle_boreholes.csv. It provides names and location for boreholes/wells at the Rifle. The waterlevel data is provided in the folder rifle_waterlevels. The geochemical data is provided in two folders: the rifle_floodplain_geochemistry folder has data which was collected from wells across the floodplain and a variety of offsite locations that contribute solutes to the floodplain given their upgradient locations. The rifle_plotC_geochemistry folder has data which was collected primarily in plot C, which was a focused study area in which a large number of groundwater manipulation / biostimulation experiments were conducted. While not all geochemical constituents are included for each well location and sampling date, they include anions, cations, trace metals, dissolved organic and inorganic carbon, stable isotopes of water and sulfur (as sulfate), and water quality parameters including pH, groundwater electrical conductivity (EC) and dissolved oxygen (DO). All files are in csv or txt format.

Styled landcover basemap for the Upper Gunnison domain - Ian K Breckheimer (s3, 2021)
This dataset is a styled basemap depicting basic landcover classes of the Upper Gunnison domain overlaid on high-resolution topography, optimized for fast display on web maps and mobile devices. The underlying datasets are available as part of Release 3 of the RMBL Spatial Data Platform. The color scale for landcover classes is as follows: dark green: evergreen forest / shrub, light green: deciduous forest, light green-brown: deciduous shrub, light yellow-green: meadow / grassland / subshrub, blue: open water, gray: bare / sparse veg., orange - irrigated pasture / cultivated, pink: paved / impervious, red: building / structure. The contour intervals depicting topography are at 20 m spacing for light lines, and 100 m spacing for dark lines. The download link to this dataset accesses a version of the basemap stored as a Cloud-optimized Geotiff (COG). The web map link accesses a version that can be added to a web map on ArcGIS Online.

Styled canopy structure basemap of the Upper Gunnison domain - Ian K Breckheimer (s3, 2021)
This dataset is a styled basemap depicting vegetation canopy structure variables in the Upper Gunnison domain overlaid on high-resolution topography, optimized for fast display on web maps and mobile devices. The underlying datasets are available as part of Release 3 of the RMBL Spatial Data Platform. The color scale encodes three different aspects of canopy structure, as an RGB composite, coded in the Red, Green, and Blue channels of the composite. Red corresponds to canopy height, with heights of zero represented as dark and heights greater than 20m represented as maximum brightness. Green corresponds to canopy cover or density, with zero density represented as dark, and cover greater than 0.8 represented as maximum brightness. Blue corresponds to understory (0.25 - 2m) cover, with zero represented as dark, and 0.6 represented at maximum brightness. This means that meadows and low vegetation are dark, shrublands are generally blue, tall forests with sparse understory are orange and yellow, short forests with dense understory are green, and tall forests with dense canopy and understory are white. The download link to this dataset accesses a version of the basemap stored as a Cloud-optimized Geotiff (COG). The web map link accesses a version that can be added to a web map on ArcGIS Online.

POLLEN, STARCH, AND ORGANIC RESIDUE (FTIR) ANALYSIS OF SAMPLES FROM SITE 5GN2404, GUNNISON COUNTY, COLORADO. - Linda Cummings (other, 2021)
Site 5GN2404, situated on a south-facing slope overlooking the Gunnison River Valley, was examined as part of work on the Blue Mesa-Skito Transmission Line. This large scatter of flaked lithic and ground stone artifacts also includes several thermal pits (Barb Lockwood, personal communication, August 11, 2010). Samples of ground stone and thermal pit fill were submitted for pollen, starch, and/or organic residue analysis using Fourier Transform Infrared Spectrometry (FTIR).

Using geochemical indicators to distinguish high biogeochemical activity in floodplain soils and sediments, Science of the Total Environment: Dataset. (ess_dive, 2021)
This dataset involves analysis of sediment samples collected in the East River watershed and Rifle floodplain sites, CO. Samples were collected and analyzed as part of two student MS theses at Colorado School of Mines (Kenwell and Prugue) over a time period ranging from 2012 to 2015. Analyses include total organic carbon, leachable Fe and Mn, and total microbial DNA; all analyses performed at Colorado School of Mines.

Groundwater level elevation and temperature across Meander C at the Lower Montane in the East River Watershed, Colorado. (ess_dive, 2021)
This groundwater level elevation and temperature data package is aimed at improving the predictive understanding of hydro-biogeochemical processes at the lower montane site in the East River Watershed, Colorado. The dataset is obtained using pressure transducers placed in shallow wells in the floodplain. This dataset contains data from wells ER-CPA1 to ER-CPA6 (six wells with SFA Location ID's). Each file contains the water level elevation and the water temperature. Water level elevation have been obtained using the barometric pressure from the pressure transducer (Hobos sensor) in the well, barometric pressure from a sensor in air located at the same site (lower montane), depth from top-of-casing (TOC) to sensor measurement point, and TOC elevation. Data have been checked with a few measurements of water table depths. A real-time kinematic (RTK) global positioning system (GPS) has been used to survey the TOC (data in file WellLocation_WLdataArchive2018). The water level elevation is given in UTM13N Geoid2012AB. While depth to water level is not present in the data files, it can be easily calculated with the TOC and distance to ground provided in the GPS coordinate file (WellLocation_WLdataArchive2018). The dataset quality is discussed in Collection/Analysis section of the methods. Time-series of measurements will be added to this data package, so please check back for updates. If you have questions, please contact the author.

Thermal infrared and photogrammetric data collected by small unoccupied aircraft system for hydrogeologic analysis of Oh-be-joyful Creek, Gunnison National Forest, Colorado, August 2017 - Cian Dawson (other, 2021)
The U.S. Geological Survey collected low-altitude airborne thermal infrared data and visual imagery via a multirotor, small unoccupied aircraft system deployed from the northern bank of Oh-be-joyful Creek and adjacent to the Peeler fault, approximately 6 kilometers northwest of the town of Crested Butte, in Gunnison National Forest, Colorado, on August 17, 2017. Thermal infrared still images were collected in jpg and radiometric tiff formats, and non-radiometric thermal infrared video was collected. The radiometric thermal infrared still images were compiled automatically into a larger stitched image (orthomosaic). Visual imagery was collected in jpg format, and the images were compiled automatically into a larger stitched image (orthomosaic). Structure from Motion techniques were applied to the visual imagery to derive a time-specific digital elevation model (DEM).

Depth profiles of soil CO2 Concentrations, soil temperature, and soil moisture (Rocky Mountain Biological Laboratory, Gothic, Colorado, 2011-2016) - Mariah Carbone (other, 2021)
Soil respiration (the flux of CO2 from the soil surface) is one of the largest and most variable fluxes in the global carbon cycle, and yet also one of the least understood, primarily due to methodological difficulties. These are (1) measuring soil respiration at high temporal frequencies and (2) attributing flux variations to its functionally different sources, plants and microbes. In 2009, we installed vertical profiles of automated soil pore space CO2 concentration sensors (Vaisala GMM 222; 5-sensor profile) under two forest cover types (deciduous aspen and evergreen spruce) at the Rocky Mountain Biological Laboratory (RMBL) in Gothic, Coloardo. These sensors are advantageous for the RMBL ecosystem because they have no moving parts, and thus can make measurements throughout the winter and underneath the snowpack. The CO2 profile measurements are paired with soil temperature and moisture measurements. The CO2 concentration sensors were recalibrated in 2018. The concentration data can be converted to estimates of soil CO2 production using a 1-D gas diffusion model. The profile information allows us to spatially separate soil CO2 production within the soil profile, and to assess how soil respiration responds to varying environmental conditions in the different vegetation communities.

Thermal infrared, multispectral, and photogrammetric data collected by drone for hydrogeologic analysis of the East River and Coal Creek beaver-impacted corridors near Crested Butte, Colorado - Martin Briggs (other, 2021)
The U.S. Geological Survey collected low-altitude (typically 200-350 ft als) airborne thermal infrared, multispectral, and visual imagery data via a multirotor, small unoccupied aircraft system deployed along beaver-impacted sections of the East River and Coal Creek stream corridors, near the town of Crested Butte, CO. Visual imagery was collected in jpg format, and the images were compiled automatically into a larger stitched image (orthomosaic). Structure from Motion techniques were also applied to the visual imagery to derive time-specific digital surface models (DSM). Thermal infrared still images were collected in jpg and radiometric tiff formats, while multispectral data were collected in tif format. Although not done yet here, multispectral and thermal data can be compiled into orthomosaics and DSMs in a similar manner to visible light imagery.

3 m Resolution 80th Percentile Canopy Height Estimates for the Upper Gunnison Basin Derived from 2015 and 2019 LIDAR Data - Ian K Breckheimer (s3, 2021)
This is a map of 20th percentile canopy height above the ground for the Upper Gunnison River Basin based on 2015 and 2019 LiDAR data. Height is measured in meters. This dataset was generated from the terrain-normalized point clouds using functions in the R package lidR. The ground-classified points were first used to generate a bare-earth surface, which was subtracted from the point cloud elevation to generate a terrain-normalized point cloud. Percentile heights were calculated for the LiDAR returns in each pixel using a kernel density method implemented using the quantile() R function. Artifacts from steep topography and structures have not been removed from this dataset.

Specific conductivity, pH, dissolved oxygen, water temperature, alkalinity and sulfide in-situ data; Slate River floodplain, Crested Butte, CO; May 2020-October 2020 - Samuel Pierce; John R. Bargar (other, 2021)
This data package includes a time-series of field measurements from May to October 2020 in groundwater and surface water from the Slate River floodplain in Crested Butte, CO, a focus field site for the SLAC Floodplain Hydro-Biogeochemistry SFA. The data was generated as part of the work targeting the overarching research question for the SLAC SFA: How do ubiquitous subsurface interfaces mediate molecular-scale biogeochemical processes and groundwater quality in floodplains and watersheds? The data packade includes 6 data files, one for each measured variable: specific conductivity, pH, dissolved oxygen, water temperature, alkalinity and sulfide. All measurements were recorded in the field immediately after water sampling. Groundwater samples were extracted from a network of installed rhizons (Rhizosphere Research Products, part no. 19.60.21F, 0.6 micrometer mesh size) and piezometer wells within the floodplain. In addition to the data files, there is a terminology file explaining the terms used, a file level metadata file, and a sensor file with metadata about the sensors used.All files are in csv format.

Fiber-optic distributed temperature data collected along the streambed of the East River, Crested Butte, CO, USA - Martin Briggs (other, 2021)
The data set includes temperature data from the base of the water column along the sediment interface of the East River near Crested Butte Colorado, USA, in support of ongoing study regarding groundwater/surface water exchange. The data were collected from 08/09/2016 to 08/31/2016 using a fiber-optic distributed temperature sensing system that has 1.01 m spatial resolution along the linear fiber-optic cable. During data analysis, the original 10 min measurments were averaged (arithmetic mean) for the entire period to potentially indicate colder groundwater inflows. Additionally, the standard devation for the entire measurement period for each distance along the cable was calculated to indicate buffered zones (reduced temperature standard deviation) that might result from upward water flow through the streambed.

Phenological responses to climate change do not exhibit phylogenetic signal in a subalpine plant community - David William Inouye; Paul J. CaraDonna (other, 2021)
Phylogenetic relationships may underlie species-specific phenological sensitivities to abiotic variation and may help to predict these responses to climate change. Although shared evolutionary history may mediate both phenology and phenological sensitivity to abiotic variation, few studies have explicitly investigated whether this is the case. We explore phylogenetic signal in flowering phenology and in phenological sensitivity to temperature and snowmelt using a 39-year record of flowering from the Colorado Rocky Mountains, USA that includes dates of first, peak, and last flowering, and flowering duration for 60 plant species in a subalpine plant community. Consistent with other studies, we found evidence in support of phylogenetic signal in first flowering date. However, the strength and significance of that signal were inconsistent across other measures of flowering in this plant community: peak flowering date exhibited the strongest phylogenetic signal, followed by first flowering date; last flowering date and duration of flowering exhibited patterns indistinguishable from random trait evolution. In contrast to first and peak flowering date, phenological sensitivities of all flowering measures to temperature and snowmelt did not exhibit a phylogenetic signal. These findings show that within ecological communities, phylogenetic signal in phenology does not necessarily imply phylogenetic signal in phenological sensitivities to abiotic variation. Larger data set

Snow Depth on March 31st 2018 for Upper East River Derived from Airborne Snow Observatory Data - Thomas Painter (s3, 2021)
This is a 3m map of snow depth derived from repeat LiDAR data collection by the Airborne Snow Observatory. This dataset has been clipped and resampled to the standard 3m SDP grid, and is derived directly from: Painter, T. 2018. ASO L4 Lidar Snow Depth 3m UTM Grid, Version 1. Boulder, Colorado USA. NASA National Snow and Ice Data Center Distributed Active Archive Center. doi: https://doi.org/10.5067/KIE9QNVG7HP0. Small areas outside of the UER region, but within the extent of this map had missing data. These gaps were filled with linear regression relating 2018 and 2019 ASO snow depths (where one map was available), or regressions related snow depth to elevation (where neither 2018 nor 2019 data was available). Peak snow depths in 2018 were near the 20th percentile of the long-term average estimated from the Butte SNOTEL station.

NOAA/WDS Paleoclimatology - Woodhouse - Cochetopa Dome - PIPO - ITRDB CO594 (other, 2021)
This archived Paleoclimatology Study is available from the NOAA National Centers for Environmental Information (NCEI), under the World Data Service (WDS) for Paleoclimatology. The associated NCEI study type is Tree Ring. The data include parameters of tree ring with a geographic location of Colorado, United States Of America. The time period coverage is from 513 to -52 in calendar years before present (BP). See metadata information for parameter and study location details. Please cite this study when using the data.

Supplementary Material for: MASP-1 and MASP-3 Bind Directly to Aspergillus fumigatus and Promote Complement Activation and Phagocytosis - A. Rosbjerg; M.-O. Skjoedt; P. Garred; R. Würzner; R. Würzner; P. Garred; M.-O. Skjoedt; A. Rosbjerg (other, 2021)
Activation of the complement system is mediated by the interaction between pathogens and pattern recognition molecules (PRMs); mannose-binding lectin (MBL), ficolins, and collectin-10/-11 from the lectin pathway and C1q from the classical pathway. Lectin pathway activation specifically depends on proteases named MBL-associated serine proteases (MASPs) that are found in complexes with PRMs. In this study, we hypothesize that MASPs can recognize selected pathogens independently of PRMs. Using different clinical strains of opportunistic fungi, we have observed that MASPs directly recognize certain fungal pathogens in a way that can facilitate complement activation. Among these were Aspergillus fumigatus – a dangerous pathogen, especially for immunocompromised patients. In flow cytometry and fluorescence microscopy, we found that MASP-1 and -3 bound to all A. fumigatus growth stages (conidia, germ tubes, and hyphae), whereas rMASP-2 and the nonproteolytic rMAP-1 did not. Bound rMASPs could recruit rMBL and rficolin-3 to A. fumigatus conidia in a nonclassical manner and activate complement via rMASP-2. In experiments using recombinant and purified components, rMASP-1 increased the neutrophilic phagocytosis of conidia. In serum where known complement activation pathways were blocked, phagocytosis could be mediated by rMASP-3. We have encountered an unknown pathway for complement activation and found that MASP-1 and MASP-3 have dual functions as enzymes and as PRMs.

Microclimate observations associated with snowmelt experiment gradient sites, East River, Colorado, 2017 to 2020 (ess_dive, 2021)
The timing of snowmelt in mountain systems is a main driver of vegetation phenology and production, as well as recharge of soil moisture and ground water. Decreases in maximum snowpack and warmer spring temperatures have led to a higher frequency of early snowmelt. This study combines a natural elevation gradient with an experimental manipulation of snowmelt timing to assess the effect of earlier melt on hillslope and watershed ecohydrological processes. This data package includes csv files with plot and sub-plot level observations of soil temperature (SM_ST.csv), soil moisture (SM_SWC.csv), air temperature (SM_AirT.csv), and relative humidity (SM_rH.csv). The date range of this dataset includes a pre-treatment year (2017), two treatment years (2018 and 2019), and a post-treatment year (2020). Location IDs associated with this data package are: ER-LM, WG-UM, WG-LS, ER-US, and XX-AL. Related data packages include: “Colorado Elevation Gradient Snowmelt Manipulation Plant Phenology 2017-2018” and “Sensor-based phenology from snowmelt experiment gradient, East River, Colorado, 2017 to 2020”

Supplementary Material for: MASP-1 and MASP-3 Bind Directly to Aspergillus fumigatus and Promote Complement Activation and Phagocytosis (other, 2021)
Activation of the complement system is mediated by the interaction between pathogens and pattern recognition molecules (PRMs); mannose-binding lectin (MBL), ficolins, and collectin-10/-11 from the lectin pathway and C1q from the classical pathway. Lectin pathway activation specifically depends on proteases named MBL-associated serine proteases (MASPs) that are found in complexes with PRMs. In this study, we hypothesize that MASPs can recognize selected pathogens independently of PRMs. Using different clinical strains of opportunistic fungi, we have observed that MASPs directly recognize certain fungal pathogens in a way that can facilitate complement activation. Among these were Aspergillus fumigatus – a dangerous pathogen, especially for immunocompromised patients. In flow cytometry and fluorescence microscopy, we found that MASP-1 and -3 bound to all A. fumigatus growth stages (conidia, germ tubes, and hyphae), whereas rMASP-2 and the nonproteolytic rMAP-1 did not. Bound rMASPs could recruit rMBL and rficolin-3 to A. fumigatus conidia in a nonclassical manner and activate complement via rMASP-2. In experiments using recombinant and purified components, rMASP-1 increased the neutrophilic phagocytosis of conidia. In serum where known complement activation pathways were blocked, phagocytosis could be mediated by rMASP-3. We have encountered an unknown pathway for complement activation and found that MASP-1 and MASP-3 have dual functions as enzymes and as PRMs.

Gunnison sage-grouse habitat suitability of six satellite populations in southwestern Colorado: San Miguel, Crawford, Pinon Mesa, Dove Creek, Cerro Summit-Cimarron-Sims, and Poncha Pass - Michael S. O'Donnell (other, 2021)
We developed habitat selection models for Gunnison sage-grouse (Centrocercus minimus), a threatened species under the U.S. Endangered Species Act. We followed a management-centric modeling approach that sought to balance the need to evaluate the consistency of key habitat conditions and improvement actions across multiple, distinct populations, while allowing context-specific environmental variables and spatial scales to nuance selection responses. Models were developed for six isolated satellite populations (San Miguel, Crawford, Pinon Mesa, Dove Creek, Cerro Summit-Cimarron-Sims, and Poncha Pass) from use locations collected between 1991 and 2016 (see larger citation for map of population boundaries). For each population, models were developed at two life stages (breeding and summer) and at two hierarchical scales (landscape and patch). We used multi-scale and seasonal resource selection analyses to quantify relationships between environmental conditions and sites used by animals. These resource selection function models relied on spatial data describing habitat conditions at different spatial scales, where environmental conditions differ, and habitat selection occur at different spatial scales for different available resources. All models encompass the following satellite populations, seasons (life stages), and scales of resource selection: Populations: San Miguel, Crawford, Pinon Mesa, Poncha Pass, Dove Creek and Cerro Summit-Cimarron-Sims Seasons: Breeding (April 1 and July 15), Summer (July 16 and September 30) Scales: Landscape, Patch All models encompass the following satellite populations, seasons (life stages), and scales of resource selection: Populations: San Miguel, Crawford, Pinon Mesa, Poncha Pass, Dove Creek and Cerro Summit-Cimarron-Sims Seasons: Breeding (April 1 and July 15), Summer (July 16 and September 30) Scales: Landscape, Patch

NEON AOP Imaging Spectroscopy Survey of Upper East River Colorado Watersheds: Raw-Space Radiance and Observational Variable Dataset. (ess_dive, 2021)
Lawrence Berkeley National Laboratory (LBNL) contracted the National Ecological Observatory Network Airborne Observation Platform (NEON AOP) to observe watersheds of interest near Crested Butte, CO with remotely sensed data including imaging spectroscopy. The flight box design encompassed the watersheds, and flight design targeted a minimum of 30% overlap between adjacent flight lines. The total area surveyed was 334 km2 across 72 lines. Flight lines were oriented north-south for consistency in solar illumination geometry. Seven days were required to cover the flight area. Some areas were flown additional times to improve data quality or temporal coincidence between airborne acquisitions and field sampling. In total, 102 lines were collected and can be downloaded here: https://portal.nersc.gov/wfsfa/doi-10-15485-1617204/. The instrument used for the acquisition was an Airborne Visible-Infrared Imaging Spectrometer - Next Generation (AVIRIS-NG), which records radiance within 426 contiguous spectral bands in the wavelength range from 380 to 2510 nm. The instrument was flown at a target aboveground altitude of 1000 m for a processed data spatial resolution of 1 m. These data are non-orthorectified, radiance data that require further processing prior to use as a surface reflectance data set.

Waterlevel, geochemical, and borehole data from Rifle, Colorado from 2006-2016 - Li Yang; Mark J. Robbins; Pe Long; Chad Hobson; M. E. Conrad; Benjamin Potter; Mark J. Robbins; M. E. Conrad; Benjamin Potter; Li Yang; Chad Hobson; Pe Long; et al. (ess_dive, 2021)
The files included in this data package provide site wide water level data, geochemical data, and borehole information associated with the Rifle site in Colorado during the Lawrence Berkeley National Lab (LBNL) led Integrated Field Research Challenge (IFRC) and Scientific Focus Area (SFA) research projects. The data informs hydrogeochemical interactions occurring in the watershed. The readme file contains detailed metadata for the files, including naming conventions, column headers, and data validation.The borehole information is provided in the file called rifle_boreholes.csv. It provides names and location for boreholes/wells at the Rifle. The waterlevel data is provided in the folder rifle_waterlevels. The geochemical data is provided in two folders: the rifle_floodplain_geochemistry folder has data which was collected from wells across the floodplain and a variety of offsite locations that contribute solutes to the floodplain given their upgradient locations. The rifle_plotC_geochemistry folder has data which was collected primarily in plot C, which was a focused study area in which a large number of groundwater manipulation / biostimulation experiments were conducted. While not all geochemical constituents are included for each well location and sampling date, they include anions, cations, trace metals, dissolved organic and inorganic carbon, stable isotopes of water and sulfur (as sulfate), and water quality parameters including pH, groundwater electrical conductivity (EC) and dissolved oxygen (DO). All files are in csv or txt format.

Distributed hydrological, chemical, and microbiological measurements around Meander A of East River, Colorado. (ess_dive, 2021)
In July-August 2018, we collected 88 filtered pore water samples at 20 cm depth and analyzed them for anions, cations, dissolved organic carbon, dissolved organic matter (DOM) quality, and standard water quality parameters. Vertical hydraulic head gradients were measured to assess the potential for upward or downward water flow and sediment grab samples were taken for grain size analyses to constrain the relationship between streambed morphology and water flow. Lastly, DNA was extracted from pore water filters for a 16S rRNA gene sequencing analysis. This allowed for a high-resolution characterization of streambed hydrology and biogeochemistry during base flow. Data.csv includes coordinates, time of sampling, grain size analysis D10 values, vertical hydraulic head gradients, microbiological diversity metrics, and multiple chemical analyses. ReadMe.txt contains all information regarding sampling procedure, analysis instrumentation, and reporting limits. Microbiological sequences analyzed here have been deposited in the NCBI Sequence Read Archive and may be accessed using accession number PRJNA527829.

Locations, metadata, and species cover from field sampling survey associated with NEON AOP survey, East River, CO 2018. (ess_dive, 2021)
Locations and descriptions of the sites where field sampling was conducted during the 2018 National Ecological Observatory Network (NEON) Airborne Observation Platform (AOP) imaging spectroscopy and lidar surveys in Gunnison County, Colorado. The sampling sites were located across East River, Washington Gulch, Slate River, and Coal Creek watersheds and contained a mixture of meadow, shrub, and tree sampling sites. This data package contains the location, metadata, species composition, and vector files for the sampling sites in this project. Species vouchers that have been preserved in the Rocky Mountain Biological Laboratory herbarium can be found on the Consortia of Southern Rocky Mountain Herbaria website: http://soroherbaria.org/portal/collections/index.php. Vector files provided here are for areas delineated based on the AOP reflectance data and mosaic developed by Brodrick et al. (doi: 10.15485/1618131), and use with other datasets should be closely evaluated. Subsequent data packages will contain additional biogeochemical, microbial, and geophysical data as they become available for these sampling sites. For full documentation, please see associated reference and additional references will be added here as they become available.

SnowEx20 Grand Mesa Intensive Observation Period Snow Pit Measurements, Version 1 (other, 2021)

East River Surface and Pore Water FTICR-MS Data Associated with “Implications of sample treatment on characterization of the riverine environmental metabolome” (ess_dive, 2021)
Surface and pore water samples were collected from distributed locations around Meander A in East River (Crested Butte, CO, USA) during the summer of 2018. This dataset consists of the characterization of dissolved organic matter using 12 Tesla Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS; in .xml format) analyzed through the Environmental Molecular Sciences Laboratory (EMSL; https://www.pnnl.gov/environmental-molecular-sciences-laboratory) using two different sample pre-treatment methods (solid phase extraction, no solid phase extraction) and two electrospray ionization methods (ESI-positive, ESI-negative) to identify the impacts of these choices on the final dataset. This study aimed to understand how the different sample processing methods influence the resulting FTICR-MS dataset. Any published work that utilizes data presented in this dataset should cite the dataset using the DOI number. If using the dataset, please acknowledge the U.S. Department of Energy (DOE) Office of Science (BER) Subsurface Biogeochemical Research (SBR) program, the Environmental Molecular Sciences Laboratory (EMSL), and Worldwide Hydrobiogeochemical Observation Network for Dynamic River Systems (WHONDRS). The publication DOI will be added to this abstract when available.

SnowEx20 Grand Mesa IOP BSU Multi-polarization 1 GHz GPR CMP Raw, Version 1 (other, 2021)

Site-level Foliar C, N, delta13C data from samples collected during field survey associated with NEON AOP survey, East River, CO 2018. (ess_dive, 2021)
Carbon (C) and nitrogen (N) weight percent concentrations were obtained from the bulk foliar samples collected across East River, Washington Gulch, Slate River, and Coal Creek watersheds in Gunnison, Colorado during the summer of 2018. These samples were collected from sun-lit leaves of meadow, shrub, and tree vegetation types within 72 hours of the National Ecological Observatory Network Airborne Observation Platform (NEON AOP) hyperspectral survey. These samples were dried and then run on an elemental analyzer coupled to a mass spectrometer for C and N concentrations and delta13C. The intention of these data were to provide ground truth data to develop foliar nutrient models across the imaging spectroscopy domain. Additional associated site metadata and vegetation fractional cover information can be found in the associated data releases (DOI: 10.15485/1618130). Here we provide site level C, N, and delta 13C data in the CN_Results_Foliar.csv. All of these samples were also registered with IGSN codes, and the details from that registration with metadata for the samples is included in foliar_sample_igsn_metadata.csv.

East River Surface and Pore Water FTICR-MS Data Associated with “Implications of sample treatment on characterization of the riverine environmental metabolome” (ess_dive, 2021)
Surface and pore water samples were collected from distributed locations around Meander A in East River (Crested Butte, CO, USA) during the summer of 2018. This dataset consists of the characterization of dissolved organic matter using 12 Tesla Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS; in .xml format) analyzed through the Environmental Molecular Sciences Laboratory (EMSL; https://www.pnnl.gov/environmental-molecular-sciences-laboratory) using two different sample pre-treatment methods (solid phase extraction, no solid phase extraction) and two electrospray ionization methods (ESI-positive, ESI-negative) to identify the impacts of these choices on the final dataset. This study aimed to understand how the different sample processing methods influence the resulting FTICR-MS dataset. Any published work that utilizes data presented in this dataset should cite the dataset using the DOI number. If using the dataset, please acknowledge the U.S. Department of Energy (DOE) Office of Science (BER) Subsurface Biogeochemical Research (SBR) program, the Environmental Molecular Sciences Laboratory (EMSL), and Worldwide Hydrobiogeochemical Observation Network for Dynamic River Systems (WHONDRS). The publication DOI will be added to this abstract when available.

SnowEx20 Grand Mesa Autumn 2019 Gravimetric Soil Moisture, Version 1 (other, 2021)

WRF Large-Eddy Simulation Data from Realtime Runs Used to Support UAS Operations during LAPSE-RATE (other, 2021)
Realtime micro-scale weather simulations were performed to support UAV (Uncrewed Aerial Vehicle) flights during the ISARRA Lower Atmospheric Process Studies at Elevation a Remotely-piloted Aircraft Team Experiment (LAPSE-RATE) field deployment. These simulations were performed by driving a nested grid configuration of the Weather Research and Forecasting model with its innermost mesh being run at 111 m grid spacing. The innermost grid was nested within a grid with 1 km grid spacing. The outermost grid being driven using operational forecast models data as described below. While the MYNN2 PBL scheme is used to parameterize turbulence in the 1 km grid, the PBL scheme is turned off within the 111 m grid, thus, allowing large-scale turbulent eddies to be resolved by WRF primitive equations. Details of the model configuration and data formats are given in Pinto et al. (2021).LAPSE-RATE took place in the San Luis Valley of Colorado during July of 2018. Goals of LAPSE-RATE were to sample the finescale evolution of the boundary layer and associated sub-mesoscale flows across a sub-alpine desert valley using a combination of surface-based instrumentation and in situ data collected using numerous, low-flying small UAVs. The realtime simulations were produced twice per day in order to support mission planning and UAVs flight operations. The simulation used for next-day planning was run using forcing data from NCEP's Global Forecast System (GFS) while the simulation available each morning of the experiment to support in flight operations was run using data from the NCEP High Resolution Rapid Refresh (HRRR), Version 3. Both simulations were valid between 04:00 and 16:00 MDT. The dataset consists of two sets of files: 3D grids and high temporal resolution time series and profiles for a select group of grid points. The 3D grids consist of all relevant basic state parameters (P, T, U, RH) and diagnostics (e.g., sub-grid scale TKE, ceiling height, visibility) that have been interpolated to flight levels AGL using the Unified Post-Processor (UPP). The UPP was used to de-stagger the mass and wind fields, interpolate forecast data to flight levels AGL and to compute diagnostics such as visibility, ceiling height, and radar reflectivity. Point data were stored for select grid points coincident with 3 fixed observation sites set up during LAPSE-RATE (i.e., Saguache, Moffat and Leach Airfield). The 3D grid files are stored every 10 minutes, while grid point data have a time resolution of 0.666 and 6 seconds for the 111 m grid spacing domain and 1 km grid spacing domain, respectively. Please see the README files for more details describing the dataset.

East River Surface and Pore Water FTICR-MS Data Associated with “Implications of sample treatment on characterization of the riverine environmental metabolome” (ess_dive, 2021)
Surface and pore water samples were collected from distributed locations around Meander A in East River (Crested Butte, CO, USA) during the summer of 2018. This dataset consists of the characterization of dissolved organic matter using 12 Tesla Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS; in .xml format) analyzed through the Environmental Molecular Sciences Laboratory (EMSL; https://www.pnnl.gov/environmental-molecular-sciences-laboratory) using two different sample pre-treatment methods (solid phase extraction, no solid phase extraction) and two electrospray ionization methods (ESI-positive, ESI-negative) to identify the impacts of these choices on the final dataset. This study aimed to understand how the different sample processing methods influence the resulting FTICR-MS dataset. Any published work that utilizes data presented in this dataset should cite the dataset using the DOI number. If using the dataset, please acknowledge the U.S. Department of Energy (DOE) Office of Science (BER) Subsurface Biogeochemical Research (SBR) program, the Environmental Molecular Sciences Laboratory (EMSL), and Worldwide Hydrobiogeochemical Observation Network for Dynamic River Systems (WHONDRS). The publication DOI will be added to this abstract when available.

Data from: Ecological factors influence balancing selection on leaf chemical profiles of a wildflower - Judith Wang; Catherine Rushworth; Julius Mojica; Kathryn Ghattas; Baosheng Wang; Chase Nuñez; Rose Keith; Maggie Wagner; Emily Chan; Kasavajhala V. S. K. Prasad; Carrie Olson-Manning (other, 2021)
Balancing selection is frequently invoked as a mechanism to maintain variation within and across populations. However, rigorous tests demonstrating balancing selection operating in nature are scarce, particularly on complex traits, which frequently display high levels of variation. Leveraging a focal polymorphism, leaf chemical profile in a perennial wildflower (Boechera stricta, Brassicaceae), we investigated the ecological and genetic mechanisms that may influence the maintenance of variation in this trait. A suite of common garden and greenhouse experiments showed that the alleles underlying variation in chemical profile have contrasting fitness effects across environments, implicating two ecological drivers of selection on chemical profile: herbivory and drought. Phenotype-environment associations and molecular genetic analyses revealed additional evidence of past selection by these drivers. Together, these data are consistent with balancing selection on chemical profile, likely caused by pleiotropic effects of genes that influence secondary chemical biosynthesis on herbivore defense and drought response.

SnowEx20 Grand Mesa IOP BSU 1 GHz Multi-polarization GPR, Version 1 (other, 2021)

SnowEx20 SnowEx Grand Mesa Automated Meteorological and Snow Station Observations 2016-2021, version 1 (other, 2021)

WRF Large-Eddy Simulation Data from Realtime Runs Used to Support UAS Operations during LAPSE-RATE (other, 2021)
Realtime micro-scale weather simulations were performed to support UAV (Uncrewed Aerial Vehicle) flights during the ISARRA Lower Atmospheric Process Studies at Elevation a Remotely-piloted Aircraft Team Experiment (LAPSE-RATE) field deployment. These simulations were performed by driving a nested grid configuration of the Weather Research and Forecasting model with its innermost mesh being run at 111 m grid spacing. The innermost grid was nested within a grid with 1 km grid spacing. The outermost grid being driven using operational forecast models data as described below. While the MYNN2 PBL scheme is used to parameterize turbulence in the 1 km grid, the PBL scheme is turned off within the 111 m grid, thus, allowing large-scale turbulent eddies to be resolved by WRF primitive equations. Details of the model configuration and data formats are given in Pinto et al. (2021).LAPSE-RATE took place in the San Luis Valley of Colorado during July of 2018. Goals of LAPSE-RATE were to sample the finescale evolution of the boundary layer and associated sub-mesoscale flows across a sub-alpine desert valley using a combination of surface-based instrumentation and in situ data collected using numerous, low-flying small UAVs. The realtime simulations were produced twice per day in order to support mission planning and UAVs flight operations. The simulation used for next-day planning was run using forcing data from NCEP's Global Forecast System (GFS) while the simulation available each morning of the experiment to support in flight operations was run using data from the NCEP High Resolution Rapid Refresh (HRRR), Version 3. Both simulations were valid between 04:00 and 16:00 MDT. The dataset consists of two sets of files: 3D grids and high temporal resolution time series and profiles for a select group of grid points. The 3D grids consist of all relevant basic state parameters (P, T, U, RH) and diagnostics (e.g., sub-grid scale TKE, ceiling height, visibility) that have been interpolated to flight levels AGL using the Unified Post-Processor (UPP). The UPP was used to de-stagger the mass and wind fields, interpolate forecast data to flight levels AGL and to compute diagnostics such as visibility, ceiling height, and radar reflectivity. Point data were stored for select grid points coincident with 3 fixed observation sites set up during LAPSE-RATE (i.e., Saguache, Moffat and Leach Airfield). The 3D grid files are stored every 10 minutes, while grid point data have a time resolution of 0.666 and 6 seconds for the 111 m grid spacing domain and 1 km grid spacing domain, respectively. Please see the README files for more details describing the dataset.

SnowEx20 Grand Mesa IOP BSU Multi-polarization 1 GHz GPR CMP Travel-Times, Version 1 (other, 2021)

Data from: Testing trade-offs and the dominance-impoverishment rule among ant communities - Robert R. Dunn; J. D. Berggreen; Raphael Boulay; Nathan J. Sanders; Annika S. Nelson (other, 2021)
Aim: Ant communities are believed to be structured by competition, with dominant species competitively excluding subordinates (the dominance-impoverishment rule). However, a high number of seemingly similar species coexist, possibly due to interspecific trade-offs. Here, we examine the evidence for the dominance-impoverishment rule across a broad latitudinal gradient and explore whether trade-offs explain coexistence within and among ant communities. Location: 40 sites in 19 countries across Europe, western North America and northern South America. Taxon: Formicidae. Methods: We conducted 2-h baiting experiments at each site. Three dominance scores were calculated for each species at each site where it occurred. We then examined the relationship between ant dominance and diversity and tested for the generality of three trade-offs (dominance-discovery, dominance-thermal tolerance and dominance-generalism) within and among ant communities along with the possible effects of environmental variables on these trade-offs. Results: We found no support for the dominance-impoverishment rule. Instead, overall species richness at baits was positively correlated with the number of dominant species and exhibited a unimodal relationship with the relative abundance of dominant ants. Moreover, we found little consistent evidence for the three interspecific trade-offs. Main conclusion: Although total species richness at baits is positively correlated with species richness of dominant species and, to a point, increasing worker numbers of dominants, trade-offs among species do not appear to shape broad-scale patterns of coexistence among ants. Species richness declines only when the numbers of dominant workers are very high. Together, these results suggest that while trade-offs and the dominance impoverishment rule might promote coexistence or shape ant communities in some locations, the evidence for their being general across communities is scant.

Depth-resolved seasonal porewater chemistry measurements from 3 locations around Meander A of the East River, Colorado (ess_dive, 2021)
Depth-resolved pore water samples were recovered from 3 locations around Meander A in the East River near Crested Butte, CO, USA for a suite of physiochemical analyses. Supplemental_Information.csv contains water quality measurements including pH, conductivity, temperature, ORP, TDS, O2 concentration, metal concentrations, carbon chemistry, and isotopic signatures; Coordinates.csv contains information regarding sampling locations; and Analysis_Notes.csv contains information regarding instrumentation and detection limits.

SnowEx20 Grand Mesa Intensive Observation Period Snow Pit Measurements, Version 1 (other, 2021)

Sensor-based phenology from snowmelt experiment gradient, East River, Colorado, 2017 to 2020 (ess_dive, 2021)
The timing of snowmelt is a critical cue for the initiation of growth in mountain meadow ecosystems and can also impact the duration and magnitude of plant production. High frequency observations of species-level phenology are time consuming and require a high degree of expertise, and publicly available remote sensing products lack the necessary temporal resolution to assess fine-scale growing season dynamics. Near-surface sensing methods provide a middle ground with high temporal frequency and tractable spatial scales (from sub-meter to hillslope scale). This data package includes csv files of Normalized Difference Vegetation Index (NDVI) timeseries (SM_NDVI_dailymax.csv) and phenological thresholds (SM_NDVI_summary.csv) for sub-plots (1m2) and Green Chromatic Coordinate (GCC) phenological thresholds (SM_GCC_summary.csv) at the plot scale (10m x 14m). Location IDs associated with this data package are: ER-LM, WG-UM, WG-LS, ER-US, and XX-AL. Related data packages include: “Microclimate observations associated with snowmelt experiment gradient sites, East River, Colorado, 2017 to 2020” and “Colorado Elevation Gradient Snowmelt Manipulation Plant Phenology 2017-2018”.

SnowEx20 Grand Mesa Autumn 2019 Snow Water Equivalent, Version 1 (other, 2021)

SnowEx20 Grand Mesa Reference GIS Data Sets, Version 1 (other, 2021)

Modeling the impact of riparian hollows on river corridor nitrogen exports (ess_dive, 2021)
This package contains all reactive transport simulation outputs used in "Modeling the impact of riparian hollows on river corridor nitrogen exports" (Rogers, D.B., et al., 2021). The simulation outputs reflect hydrological and biogeochemical behavior of a single, generalized riparian hollow located in the intra-meander region of a sub-alpine floodplain under transient hydrological conditions. The context for, purpose of, and conclusions drawn from this model are detailed in Rogers, D.B., et al., 2021. The .zip file contains simulation outputs for each of the five time periods analyzed (see metadata for specific dates), with each folder representing one continuous simulation period. Within each folder are the raw simulation outputs, which are comprised of hundreds of files. Files ending in ".vtk" are best visualized and analyzed using ParaView (https://www.paraview.org). All other files are best viewed or analyzed using R. For a detailed description of the meaning of each file, refer to the ".fls" file located in each folder.

Shifts in water availability mediate plant-pollinator interactions - M. Kate Gallagher; Diane R. Campbell (other, 2021)
Altered precipitation patterns associated with anthropogenic climate change are expected to have many effects on plants and insect pollinators, but it is unknown if effects on pollination are mediated by changes in water availability. We tested the hypothesis that impacts of climate on plant–pollinator interactions operate through changes in water availability, and specifically that such effects occur through alteration of floral attractants. We manipulated water availability in two naturally occurring Mertensia ciliata (Boraginaceae) populations using water addition, water reduction and control plots and measured effects on vegetative and floral traits, pollinator visitation and seed set. While most floral trait values, including corolla size and nectar, increased linearly with increasing water availability, in this bumblebee-pollinated species, pollinator visitation peaked at intermediate water levels. Visitation also peaked at an intermediate corolla length, while its relationship to corolla width varied across sites. Seed set, however, increased linearly with water. These results demonstrate the potential for changes in water availability to impact plant–pollinator interactions through pollinator responses to differences in floral attractants, and that the effects of water on pollinator visitation can be nonlinear. Plant responses to changes in resource availability may be an important mechanism by which climate change will affect species interactions.

Sapflow and xylem water isotopes from Snodgrass Mountain, East River Watershed, Colorado USA. (ess_dive, 2021)
This dataset includes sapflux and stable water isotopes of soil water and xylem water for aspen, fir and spruce trees along the Snodgrass Mountain transect in the East River Watershed, Colorado USA. The purpose of generating this dataset was to understand: (1) the total flux of water being used by trees in the watershed, (2) separate the component of transpiration that was derived from recent precipitation vs. older water such as winter precipitation of groundwater and (3) understand how total water use and water sources for the trees varies between species and position on a hillslope. This work will be combined with hydrological simulations to place better constraints on the flow paths of water through the East River Watershed. The data were collected from May to September of 2019 though collections are ongoing through 2021. The sap flux data were collected using ICT SFM1 sensors and are presented in units of cm/hour after having been corrected using estimates of wounding diameter, water content of wood and sap wood depth. The xylem water isotope data were collected approximately weekly from each of the trees instrumented with sap flux. The stems were collected and the water extracted using classic cryogenic methods. Isotope measurements were done using a Picarro 2140i analyzer.

Mammalian herbivores restrict the altitudinal range limits of three alpine grass species, West Elk Mountains, Colorado, USA 2015-2018 (other, 2021)
Though rarely experimentally tested, biotic interactions have long been hypothesized to limit low-elevation range boundaries of species. We tested the effects of herbivory on three alpine-restricted plant species by transplanting plants below (novel), at the edge (limit), or in the center (core) of their current elevational range and factorially fencing-out above- and belowground mammals in the West Elk Mountains, Colorado, USA from 2015-2018. Herbivore damage was greater in range limit and novel habitats than in range cores. Exclosures increased plant biomass and reproduction more in novel habitats than in range cores, suggesting demographic costs of novel interactions with herbivores. We then used demographic models to project population growth rates, which increased 5-20% more under herbivore exclosure at range limit and novel sites than in core habitats. Our results identify mammalian herbivores as key drivers of the low-elevation range limits of alpine plants and indicate that upward encroachment of herbivores could trigger local extinctions by depressing plant population growth.

Cytotype and genotype predict mortality and recruitment in Colorado quaking aspen (Populus tremuloides) - K. E. Mock; G. Richard Strimbeck; Savannah Troy; Benjamin Blonder; L. L. Iversen; Marco Castaneda; Madison Lusk; Michael Clyne; J. A. Walton; Pierre Gaüzere; K. Dana Chadwick (other, 2021)
Species responses to climate change depend on environment, genetics, and interactions among these factors. Intraspecific cytotype (ploidy level) variation is a common type of genetic variation in many species. However, the importance of intraspecific cytotype variation in determining demography across environments is poorly known. We studied the tree species quaking aspen (Populus tremuloides), which occurs in diploid and triploid cytotypes. This widespread species is experiencing contractions in its western range, which could potentially be linked to cytotype-dependent drought tolerance. We found that interactions between cytotype and environment drive mortality and recruitment across 503 plots in Colorado. Triploids were more vulnerable to mortality relative to diploids and had reduced recruitment on more drought-prone and disturbed plots relative to diploids. Furthermore, there was substantial genotype-dependent variation in demography. Thus, cytotype and genotype variation are associated with decline in this foundation species. Future assessment of demographic responses under climate change will require knowledge of how genetic and environmental mosaics interact to determine species' ecophysiology and demography.

SnowEx20 Grand Mesa IOP BSU Multi-polarization 1 GHz GPR CMP Travel-Times, Version 1 (other, 2021)

Dissolved Inorganic Carbon and Dissolved Organic Carbon Data for the East River Watershed, Colorado (2015-2021) (ess_dive, 2021)
This data package contains mean values for dissolved organic carbon (DOC) and dissolved inorganic carbon (DIC) for water samples taken from the East River Watershed in Colorado. The East River is part of the Watershed Function Scientific Focus Area (WFSFA) located in the Upper Colorado River Basin, United States. DOC and DIC concentrations in water samples were determined using a TOC-VCPH analyzer (Shimadzu Corporation, Japan). DOC was analyzed as non-purgeable organic carbon (NPOC) by purging HCl acidified samples with carbon-free air to remove DIC prior to measurement. After the acidified sample has been sparged, it is injected into a combustion tube filled with oxidation catalyst heated to 680 degrees C. The DOC in samples is combusted to CO2 and measured by a non-dispersive infrared (NDIR) detector. The peak area of the analog signal produced by the NDIR detector is proportional to the DOC concentration of the sample. DIC was determined by acidifying the samples with HCl first, and then purge with carbon-free air to release CO2 for analysis by NDIR detector. All files are labeled by location and variable, and data reported are the mean values upon minimum three replicate measurements with a relative standard deviation < 3%. All samples were analyzed under a rigorous quality assurance and quality control (QA/QC) process as detailed in the methods. This data package contains (1) a zip file (dic_npoc_data_2014-2021.zip) containing a total of 261 files: 260 data files of DIC and NPOC data from across the Lawrence Berkeley National Laboratory (LBNL) Watershed Function Scientific Focus Area (SFA) which is reported in .csv files per location and a locations.csv (1 file) with latitude and longitude for each location; (2) a file-level metadata (flmd.csv) file that lists each file contained in the dataset with associated metadata; and (3) a data dictionary (dd.csv) file that contains terms/column_headers used throughout the files along with a definition, units, and data type. There are a total of 99 locations containing isotope data. Update on 10/07/2020: Updated the data files to remove times from the timestamps, so that only dates remain. The data values have not changed. Update on 4/11/2021: Added Determination of Method Detection Limits (MDLs) for DIC, NPOC and TDN Analyses document, which can be accessed as a PDF or with Microsoft Word.Update on 6/10/2022: versioned updates to this dataset was made along with these changes: (1) updated dissolved inorganic carbon and dissolved organic carbon data for all locations up to 2021-12-31, (2) removal of units from column headers in datafiles, (3) added row underneath headers to contain units of variables, (4) restructure of units to comply with CSV reporting format requirements, (5) added -9999 for empty numerical cells, and (6) the addition of the file-level metadata (flmd.csv) and data dictionary (dd.csv) were added to comply with the File-Level Metadata Reporting Format. Update on 2022-09-09: Updates were made to reporting format specific files (file-level metadata and data dictionary) to correct swapped file names, add additional details on metadata descriptions on both files, add a header_row column to enable parsing, and add version number and date to file names (v2_20220909_flmd.csv and v2_20220909_dd.csv).

SnowEx20 Grand Mesa IOP BSU Multi-polarization 1 GHz GPR CMP Raw, Version 1 (other, 2021)

SnowEx20 Grand Mesa IOP BSU 1 GHz Multi-polarization GPR, Version 1 (other, 2021)

SnowEx20 Grand Mesa Autumn 2019 Snow Depth, Version 1 (other, 2021)

Mammalian herbivores restrict the altitudinal range limits of three alpine grass species, West Elk Mountains, Colorado, USA 2015-2018 (other, 2021)
Though rarely experimentally tested, biotic interactions have long been hypothesized to limit low-elevation range boundaries of species. We tested the effects of herbivory on three alpine-restricted plant species by transplanting plants below (novel), at the edge (limit), or in the center (core) of their current elevational range and factorially fencing-out above- and belowground mammals in the West Elk Mountains, Colorado, USA from 2015-2018. Herbivore damage was greater in range limit and novel habitats than in range cores. Exclosures increased plant biomass and reproduction more in novel habitats than in range cores, suggesting demographic costs of novel interactions with herbivores. We then used demographic models to project population growth rates, which increased 5-20% more under herbivore exclosure at range limit and novel sites than in core habitats. Our results identify mammalian herbivores as key drivers of the low-elevation range limits of alpine plants and indicate that upward encroachment of herbivores could trigger local extinctions by depressing plant population growth.

SnowEx20 Grand Mesa Autumn 2019 Snow Depth, Version 1 (other, 2021)

Sensor-based phenology from snowmelt experiment gradient, East River, Colorado, 2017 to 2020 (ess_dive, 2021)
The timing of snowmelt is a critical cue for the initiation of growth in mountain meadow ecosystems and can also impact the duration and magnitude of plant production. High frequency observations of species-level phenology are time consuming and require a high degree of expertise, and publicly available remote sensing products lack the necessary temporal resolution to assess fine-scale growing season dynamics. Near-surface sensing methods provide a middle ground with high temporal frequency and tractable spatial scales (from sub-meter to hillslope scale). This data package includes csv files of Normalized Difference Vegetation Index (NDVI) timeseries (SM_NDVI_dailymax.csv) and phenological thresholds (SM_NDVI_summary.csv) for sub-plots (1m2) and Green Chromatic Coordinate (GCC) phenological thresholds (SM_GCC_summary.csv) at the plot scale (10m x 14m). Location IDs associated with this data package are: ER-LM, WG-UM, WG-LS, ER-US, and XX-AL. Related data packages include: “Microclimate observations associated with snowmelt experiment gradient sites, East River, Colorado, 2017 to 2020” and “Colorado Elevation Gradient Snowmelt Manipulation Plant Phenology 2017-2018”.

Low predictability of energy balance traits and leaf temperature metrics in desert, montane, and alpine plant communities - Rozália E Kapás; Sabastian Escobar; S. T. Michaletz; Benjamin Blonder (other, 2021)
Leaf energy balance may influence plant performance and community composition. While biophysical theory can link leaf energy balance to many traits and environment variables, predicting leaf temperature and key driver traits with incomplete parameterizations remains challenging. Predicting thermal offsets (δ, Tleaf – Tair difference) or thermal coupling strengths (β, Tleaf vs. Tair slope) is challenging. We ask: 1) whether environmental gradients predict variation in energy balance traits (absorptance, leaf angle, stomatal distribution, maximum stomatal conductance, leaf area, leaf height); 2) whether commonly-measured leaf functional traits (dry matter content, mass per area, nitrogen fraction, δ13C, height above ground) predict energy balance traits; and 3) how traits and environmental variables predict δ and β among species. We address these questions with diurnal measurements of 41 species co-occurring along an 1100 m elevation gradient spanning desert to alpine biomes. We show that 1) energy balance traits are only weakly associated with environmental gradients, and 2) are not well predicted by common functional traits. We also show that 3) δ and β can be partially approximated using interactions among site environment and traits, with a much larger role for environment than traits. The heterogeneity in leaf temperature metrics and energy balance traits challenges larger-scale predictive models of plant performance under environmental change.

Flowering phenology in subalpine meadows: Does climate variation influence community co-flowering patterns? - James D. Thomson; Jessica R. K. Forrest; David William Inouye (other, 2021)
Climate change is expected to alter patterns of species co-occurrence, in both space and time. Species-specific shifts in reproductive phenology may alter the assemblages of plant species in flower at any given time during the growing season. Temporal overlap in the flowering periods (co-flowering) of animal-pollinated species may influence reproductive success if competitive or facilitative interactions between plant species affect pollinator services. We used a 33-year data set on flowering phenology in subalpine meadows in Colorado, USA, to determine whether interannual variation in snowmelt date, which marks the start of the growing season, affected co-flowering patterns. For two of four species considered, we found a significant relationship between snowmelt timing and composition of the assemblage of co-flowering plants. In years of early snowmelt, Lathyrus lanszwertii var. leucanthus (Fabaceae), the species we investigated in most detail, tended to overlap with earlier-flowering species and with fewer species overall. In particular, overlap with the flowering period of Lupinus polyphyllus var. prunophilus, with which Lathyrus leucanthus shares pollinators, was significantly reduced in early-snowmelt years. The observed association between timing of snowmelt and patterns of flowering overlap could not have been predicted simply by examining temporal trends in the dates of peak flowering of the dominant species in the community, as peak flowering dates have largely shifted in parallel with respect to snowmelt date. However, subtle interspecific differences in responsiveness of flowering time, duration, and intensity to interannual climate variation have likely contributed to the observed relationship. Although much of the year-to-year variation in flowering overlap remains unexplained by snowmelt date, our finding of a measurable signal of climate variation suggests that future climate change may lead to altered competitive environments for these wildflower species.

Mammalian herbivores restrict the altitudinal range limits of three alpine grass species, West Elk Mountains, Colorado, USA 2015-2018 (other, 2021)
Though rarely experimentally tested, biotic interactions have long been hypothesized to limit low-elevation range boundaries of species. We tested the effects of herbivory on three alpine-restricted plant species by transplanting plants below (novel), at the edge (limit), or in the center (core) of their current elevational range and factorially fencing-out above- and belowground mammals in the West Elk Mountains, Colorado, USA from 2015-2018. Herbivore damage was greater in range limit and novel habitats than in range cores. Exclosures increased plant biomass and reproduction more in novel habitats than in range cores, suggesting demographic costs of novel interactions with herbivores. We then used demographic models to project population growth rates, which increased 5-20% more under herbivore exclosure at range limit and novel sites than in core habitats. Our results identify mammalian herbivores as key drivers of the low-elevation range limits of alpine plants and indicate that upward encroachment of herbivores could trigger local extinctions by depressing plant population growth.

Sample Collection Metadata for Soil Cores from the East River Watershed, Colorado collected in 2017. (ess_dive, 2021)
This data package contains sample collection metadata for soil cores from the East River Watershed in Colorado used in biogeochemical analyses by the Watershed Function SFA. Soil cores were collected seasonally during autumn, winter, snowmelt, and spring at a predominately montane meadow, high altitude field site. Information provided for each soil core sample assigned an International Geo Sample Number (IGSN) includes: sample name, IGSN, material, description, collection method, core depth, location, field program, collectors, and date. The full list of 53 IGSN's is listed in the Methods section. There is also a complete core sample list and metadata for the set of baseline data.

Phenology of selected cavity-nesting Hymenoptera and flowering plant taxa in the Colorado Rocky Mountains from 2008 to 2010. - Jessica R. K. Forrest; Rocky Mountain Biological Laboratory; Ecological Society of America (other, 2021)
Data come from fourteen sites in the West Elk Mountains of Colorado, USA. The study aimed to identify the factors regulating phenology of plants and cavity-nesting insects, and to determine the likelihood of asynchrony between flowering and pollinator emergence under climate change. Numbers of flowers or flowering stems of several abundant species were counted 2-3 times weekly along variable-width belt transects in May-July 2008 and 2009. Insect data are from experimental nest blocks colonized naturally by cavity-nesting insects in 2007 and 2008. Emergence traps on these nest blocks were monitored 2-3 times weekly in 2008 (for 2007 nests) and 2009-2010 (2008 nests) to characterize insect phenology. All Hymenoptera, excluding Ichneumonoidea, were identified to species, if possible. A reciprocal transplant experiment was conducted using nest blocks at two of the sites in 2007-2008, and a study of nest-height effects on emergence phenology was conducted at one site in 2008-2010. For each individual nest or nest block on each sampling date, we recorded the number of individuals, their sex, the number already dead at the time of capture, and the experimental treatment (when appropriate). Dataloggers recorded temperature and light hourly at each study site; these data are deposited separately with Ecological Archives.

Effects of flowers on land surface albedo and soil microclimate - Amy M. Iler (other, 2021)
The phenology of vegetation, namely leaf-out and senescence, can influence the Earth’s climate over regional spatial scales and long time periods (e.g., over 30 years or more), in addition to microclimates over local spatial scales and shorter time periods (weeks to months). However, the effects of flowers on climate and microclimate are unknown. We investigate whether flowers can influence light reflected by the land surface and soil microclimate in a subalpine meadow. We conducted a flower removal experiment with a common sunflower species, Helianthella quinquenervis, for 3 years (2015, 2017, and 2019). The flower removal treatment simulates the appearance of the meadow when Helianthella flowers earlier under climate change and loses its flowers to frost (other plant structures are not damaged by frost). We test the hypotheses that a reduction in cover of yellow flowers leads to a greener land surface, lower reflectance, warmer and drier soils, and increased plant water stress. Flower removal plots are greener, reflect less light, exhibit up to 1.2 °C warmer soil temperatures during the warmest daylight hours, and contain ca. 1% less soil moisture compared to controls. However, soils were warmer in only 2 of the 3 years, when flower abundance was high. Helianthella water use efficiency did not differ between removal and control plots. Our study provides evidence for a previously undocumented effect of flowers on soil microclimate, an effect that is likely mediated by climate change and flowering phenology. Many anthropogenic environmental changes alter landscape albedo, all of which could be mediated by flowers: climate change, plant invasions, and agriculture. This study highlights how further consideration of the effects of flowers on land surface albedo could improve our understanding of the effects of vegetation on microclimate.

Plant species distribution within the Upper Colorado River Basin estimated by using hyperspectral and LiDAR airborne data. (ess_dive, 2021)
This package is part of the Watershed Function SFA project and contains a remote sensing dataset acquired at the East River, Colorado. The remote sensing dataset is composed of vegetation maps computed from hyperspectral and LiDAR airborne data acquired by the NEON team in June 2018. The maps show the spatial distribution of plant species among trees, shrubs, and meadows at 1-meter resolution, covering four main catchments located in the Upper Colorado River Basin: the East River (67.5 km2), Washington Gulch (93.0 km2), Oh-be-Joyful Creek-Slate River (86.9 km2), and Coal Creek (53.2 km2). The maps were obtained through a supervised classification approach based on the support vector machine learning algorithm. The data input to the algorithm is the hyperspectral and LiDAR dataset. As pre-processing, an NDVI-based threshold was applied to mask bare soil, man-made structures, water, and shadows. The classification algorithm was applied following a hierarchical strategy. In the first step, the tree species were estimated. The algorithm was then applied to the remaining areas for the identification of shrubs and meadow plants. The various estimations were then merged to provide the final vegetation map. Some of the files are geotiffs, which require GIS software to visualize. jpeg files are extracted geotiffs.

East River Surface and Pore Water FTICR-MS Data Associated with “Implications of sample treatment on characterization of the riverine environmental metabolome” (ess_dive, 2021)
Surface and pore water samples were collected from distributed locations around Meander A in East River (Crested Butte, CO, USA) during the summer of 2018. This dataset consists of the characterization of dissolved organic matter using 12 Tesla Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS; in .xml format) analyzed through the Environmental Molecular Sciences Laboratory (EMSL; https://www.pnnl.gov/environmental-molecular-sciences-laboratory) using two different sample pre-treatment methods (solid phase extraction, no solid phase extraction) and two electrospray ionization methods (ESI-positive, ESI-negative) to identify the impacts of these choices on the final dataset. This study aimed to understand how the different sample processing methods influence the resulting FTICR-MS dataset. Any published work that utilizes data presented in this dataset should cite the dataset using the DOI number. If using the dataset, please acknowledge the U.S. Department of Energy (DOE) Office of Science (BER) Subsurface Biogeochemical Research (SBR) program, the Environmental Molecular Sciences Laboratory (EMSL), and Worldwide Hydrobiogeochemical Observation Network for Dynamic River Systems (WHONDRS). The publication DOI will be added to this abstract when available.

East River Surface and Pore Water FTICR-MS Data Associated with “Implications of sample treatment on characterization of the riverine environmental metabolome” (ess_dive, 2021)
Surface and pore water samples were collected from distributed locations around Meander A in East River (Crested Butte, CO, USA) during the summer of 2018. This dataset consists of the characterization of dissolved organic matter using 12 Tesla Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS; in .xml format) analyzed through the Environmental Molecular Sciences Laboratory (EMSL; https://www.pnnl.gov/environmental-molecular-sciences-laboratory) using two different sample pre-treatment methods (solid phase extraction, no solid phase extraction) and two electrospray ionization methods (ESI-positive, ESI-negative) to identify the impacts of these choices on the final dataset. This study aimed to understand how the different sample processing methods influence the resulting FTICR-MS dataset. Any published work that utilizes data presented in this dataset should cite the dataset using the DOI number. If using the dataset, please acknowledge the U.S. Department of Energy (DOE) Office of Science (BER) Subsurface Biogeochemical Research (SBR) program, the Environmental Molecular Sciences Laboratory (EMSL), and Worldwide Hydrobiogeochemical Observation Network for Dynamic River Systems (WHONDRS). The publication DOI will be added to this abstract when available.

Geophysical borehole logging data of wells ER-GLS1, ER-GUM1, ER-PLM7, and ER-PLM8 at the East River Watershed, Colorado. - Sebastian Uhlemann (ess_dive, 2021)
The purpose of this data set is to provide a means of characterizing the bedrock variability both within a single borehole location and across the East River Watershed. The East River is part of the Watershed Function Scientific Focus Area (WFSFA) located in the Upper Colorado River Basin, United States, and all boreholes are located within Mancos shale bedrock. The data set contains geophysical borehole logging data acquired in October 2018 in boreholes ER-GUM1 (East River- Gothic Upper Montane Borehole #1) and ER-GLS1 (East River- Gothic Lower Subalpine Borehole #1), and acquired in October 2019 in boreholes ER-PLM7 (East River- Pumphouse Lower Montane Borehole #7) and ER-PLM8 (East River- Pumphouse Lower Montane Borehole #8). It contains depth, natural gamma ray emission, spectral gamma ray emission(Th, K, U), magnetic susceptibility, fluid temperature and electrical conductivity, electromagnetic (EM) induction derived rock electrical resistivity, heat pulse and spinner flow measurements to estimate groundwater flow, and Nuclear Magnetic Resonance (NMR) derived water content and hydraulic conductivity. Data for each borehole are provided as comma delimited text files. For each borehole accurate location information is provided (based on RTK GPS (Real Time Kinematic Global Positioning System) surveying). Borehole logging data were acquired using Mount Sopris borehole tools, and Vista Clara Javelin for NMR data.

bblonder/aspen_neon: Code supporting Blonder et al., "Remote sensing of cytotype and its consequences for canopy damage in quaking aspen" - Benjamin Blonder (other, 2021)
No description provided.

Effects of Plant Removal on Mineralization Rates at the Rocky Mountain Biological Laboratory, Gunnison County, Colorado: 2018 (2021)
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Time-domain reflectometer survey across the East River Watershed, Colorado. (ess_dive, 2021)
Lawrence Berkeley National Laboratory (LBNL) collected near-surface point-measurements of soil temperature (file variable TDR_T(C)), volumetric water content (file variable TDR_SM(VWC%)), and soil electrical conductivity (file variable TDR_EC(mS/m)) using a time-domain reflectometer (TDR) at a depth of 25 cm. The survey aimed to characterize the spatial heterogeneity of near-surface hydrological properties at the hillslope scale considering sites with different aspects and elevation within the watershed. The East River is part of the Watershed Function Scientific Focus Area (WFSFA) located in the Upper Colorado River Basin, United States. These data were collected in early July 2019 over four hillslope sites: Pumphouse (north-east facing slope), Bradley (west and east-facing slopes), and Snodgrass (east-facing slope) within the East River watershed. Part of this survey was used to investigate soil-plant interactions at the hillslope scale in Jashvina et al. 2020.

Estimated Darcy Velocities Using Temperature Time Series for Meander A of East River, Colorado. (ess_dive, 2021)
Heat was used as a tracer to quantify seasonal changes in vertical Darcy velocity through the streambed at three different locations about Meander A of East River, Colorado. The file Raw_Temp.csv represents raw temperature data (in degrees Celsius) collected from the three locations, A, B, and C, at depths of 5, 10, 20, and 35 cm below the sediment-water interface. Darcy velocity estimates were calculated from these data using 1DTempPro and are shown in 1DTempPro_estimates.csv file. Positive values represent upwelling conditions, while negative values indicate downwelling conditions.

EXAMINATION OF BULK SOIL/DETRITAL CHARCOAL AND AMS RADIOCARBON AGE DETERMINATION OF MATERIAL FROM SITES TRCR1, TRCR2, TRCR4, TRCR5, AND TRCR6 ALONG TAYLOR RIVER, COLORADO. - Peter Kováčik (other, 2021)
Six bulk soil samples and seventeen detrital charcoal samples from sites TRCR1, TRCR2, TRCR4, TRCR5, and TRCR6 along Taylor River in Gunnison County, central Colorado, were analyzed to recover organic remains suitable for radiocarbon age determination. Samples were collected from Holocene terraces at a reach downstream of Taylor Park Reservoir. Botanic components and detrital charcoal were identified, and potentially radiocarbon datable material was separated. Five radiocarbon dates were obtained on charcoal and charred botanic remains recovered from these samples.

Custom NEON AOP reflectance mosaics and maps of shade masks, canopy water content. - Philip G. Brodrick; Tristan Goulden; K. Dana Chadwick (other, 2021)
This mosaic of visible to shortwave infrared (VSWIR) data was derived from the assignable asset NEON AOP radiance data that was collected by LBNL’s Watershed Function SFA during the summer of 2018 (DOI: 10.15485/1617204). This atmospheric correction was completed to take into account site-specific terrain variability in the 334 km2 survey area centered around Crested Butte, CO. The atmospheric correction was completed using ACORN atmospheric correction software executed on 200 x 200 pixel kernels rather than line by line in order to capture local flight altitude conditions. Manual cloud delineation removed any small shaded areas that occurred within the data collection areas. Mosaics were developed based on preference for days that were in close timing proximity to the coincident ground campaign and with mosaicing criteria that minimized the angle between the sun and the sensor to retrieve the most consistent reflectance (min_phase_refl_tiled). Finally, we generated shade masks based on the geometry between the sun angle at time of flight, the ground surface, and the sensor. Here we provide the orthomosaiced estimated reflectance data (https://portal.nersc.gov/wfsfa/doi-10-15485-16181314/), canopy water content (wtrl), estimated atmospheric water vapor (wtrv), the observational data (obs) for this particular mosaic, the estimated visibility (vis), shade masks derived from the digital surface elevation model (shade) and the digital terrain model (shade_tch) added to the canopy height model (DOI: 10.15485/1617203), and a wavelength metadata file. Each image file is provided as a GeoTiff with internal tiling and LZW compression. These data can also be found on Google Earth Engine for extraction, download, and analysis of smaller extents: DSM Shade: https://code.earthengine.google.com/?asset=users/pgbrodrick/SFA/collections/shade_priority. DTM + CHM Shade: https://code.earthengine.google.com/?asset=users/pgbrodrick/SFA/collections/shade_tch_priority. Custom Reflectance: https://code.earthengine.google.com/?asset=users/pgbrodrick/SFA/collections/ciacorn_priority OBS data: https://code.earthengine.google.com/?asset=users/pgbrodrick/SFA/collections/obs_priority Water vapor estimates: https://code.earthengine.google.com/?asset=users/pgbrodrick/SFA/collections/wtrv_priority Canopy water content: https://code.earthengine.google.com/?asset=users/pgbrodrick/SFA/collections/wtrl_priority All data visualization: https://code.earthengine.google.com/5c96bbc96ffd50e3c8b1433b34a0bb86

Impacts of beekeeping on wild bee diversity and pollination networks in the Aegean Archipelago - Theodora Petanidou; Andreas Mueller; Jelle Devalez; Holger Dathe; Thomas Tscheulin; Carmelo Gómez-Martínez; Erwin Scheuchl; Stephan Risch; Andreas Ebmer; Maximilian Schwarz; Evangelos Papas; John Pickering; et al. (other, 2021)
Maintaining the diversity of wild bees is a priority for preserving ecosystem function and promoting stability and productivity of agroecosystems. However, wild bee communities face many threats and beekeeping could be one of them, because honey bees may have a strong potential to outcompete wild pollinators when placed at high densities. Yet, we still know little about how beekeeping intensity affects wild bee diversity and their pollinator interactions. Here, we explore how honey bee density relates to wild bee diversity and the structure of their pollination networks in 41 sites on 13 Cycladic Islands (Greece) with similar landscapes but differing in beekeeping intensity. Our large-scale study shows that increasing honey bee visitation rate had a negative effect on wild bee species richness and abundance, although the latter effect was relatively weak compared to the effect of other landscape variables. Competition for flowering resources (as indicated by a resource sharing index) increased with the abundance of honey bees, but the effect was more moderate for wild bees in family Apidae than for bees in other families, suggesting a stronger niche segregation in Apidae in response to honey bees. Honey bees also influenced the structure of wild bee pollination networks indirectly, through changes in wild bee richness. Low richness of wild bees in sites with high honey bee abundance resulted in wild bee networks with fewer links and lower linkage density. Our results warn against beekeeping intensification in these islands and similar hotspots of bee diversity, and shed light on how benefits to pollination services of introducing honey bees may be counterbalanced by detriments to wild bees and their ecosystem services.

Geochemical characterization of floodplain sediments from Meander C and O in the East River Watershed, CO, USA. (ess_dive, 2021)
This data package is part of the Watershed Function SFA data collection and contains geochemical characterization of sediments as a function of depth in the pumphouse vicinity, including Meander C and Meander O (oxbow). This data was used in the manuscript "Fox, P.M., Bill, M., Heckman, K., Conrad, M., Anderson, C., Keiluweit, M., and Nico, P.S.Shale as a Source of Organic Carbon in Floodplain Sediments of a Mountainous Watershed" published in Journal of Geophysical Research: Biogeosciences. Data includes sieving, total organic carbon (TOC), total inorganic carbon (TIC), total nitrogen (TN), carbon isotopes (14C and 13C) of whole sediment. Sediment density fractionation data is also included, with measurements of TOC, TN, 14C and 13C on density fractions. Metal and carbon concentrations from various sediment extractions (HCl, dithionite, oxalate, water, and pyrophosphate) are included. Characterization of extracted carbon by fourier transform infrared spectroscopy (FTIR) and UV-Visible light spectroscopy. Characterization of density fractionated (light fractions) organic carbon by FTIR. Carbon X-ray spectroscopy (C near edge X-ray absorption fine structure spectroscopy [NEXAFS] and scanning transmission X-ray microscopy [STXM]) is also included for shale samples and sediment samples. Additional acknowledgements: 1. M.K. and C.A. were supported by the Department of Energy, Office of Biological and Environmental Research, Subsurface Biosphere Research program (award no. DE-SC0016544). 2. STXM and NEXAFS data was collected at the Canadian Light Source, which is supported by the Canada Foundation for Innovation, Natural Sciences and Engineering Research Council of Canada, the University of Saskatchewan, the Government of Saskatchewan, Western Economic Diversification Canada, the National Research Council Canada, and the Canadian Institutes of Health Research. 3. Radiocarbon analysis was supported in part by the Radiocarbon Collaborative, which is jointly sponsored by the USDA Forest Service Northern Research Station, the KCCAMS Facility at UC Irvine, and Michigan Technological University. Update 11/06/2019: An .kml file was added with the GPS locations for all the sampling sites.

Elevation alters outcome of competition between resident and range-shifting species (2021)
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East River Surface and Pore Water FTICR-MS Data Associated with “Implications of sample treatment on characterization of the riverine environmental metabolome” (ess_dive, 2021)
Surface and pore water samples were collected from distributed locations around Meander A in East River (Crested Butte, CO, USA) during the summer of 2018. This dataset consists of the characterization of dissolved organic matter using 12 Tesla Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS; in .xml format) analyzed through the Environmental Molecular Sciences Laboratory (EMSL; https://www.pnnl.gov/environmental-molecular-sciences-laboratory) using two different sample pre-treatment methods (solid phase extraction, no solid phase extraction) and two electrospray ionization methods (ESI-positive, ESI-negative) to identify the impacts of these choices on the final dataset. This study aimed to understand how the different sample processing methods influence the resulting FTICR-MS dataset. Any published work that utilizes data presented in this dataset should cite the dataset using the DOI number. If using the dataset, please acknowledge the U.S. Department of Energy (DOE) Office of Science (BER) Subsurface Biogeochemical Research (SBR) program, the Environmental Molecular Sciences Laboratory (EMSL), and Worldwide Hydrobiogeochemical Observation Network for Dynamic River Systems (WHONDRS). The publication DOI will be added to this abstract when available.

Digital Data from Mineral Investigation of Sangre de Cristo Wilderness Study Area, Alamosa, Custer, Fremont, Huerfano, and Saguache Counties, Colorado, USA (other, 2021)
This Data Release provides tabular and geospatial data digitized by the U.S. Geological Survey (USGS) from a U.S. Bureau of Mines (USBoM) report titled Mineral Investigation of Sangre de Cristo Wilderness Study Area, Alamosa, Custer, Fremont, Huerfano, and Saguache Counties, Colorado. The original preliminary paper report, numbered Mineral Land Assessment 65-83 (MLA 65-83; Ellis and others, 1983), presented the results of a mineral resource potential survey of areas in and around the Sangre de Cristo Range flanking the northeastern extent of San Luis Valley in south-central Colorado. Included in this Data Release are georeferenced scans of the regional plate maps, digitized sample site locations, analytical chemistry, and structural geologic data from MLA 65-83 in a modern and searchable geospatial database. In addition to the maps and associated point locations, the dataset contains 1,262 rows and 58 columns of contextual and numeric information in the main data table, as well as a table describing 97 samples excluded from the MLA report, a table of summary deposit information, a table of USBoM inventory data for the prepared and stored rock samples, and geospatial boundary data of the Sangre de Cristo Wilderness, Wilderness Study Area (WSA), and mineralized sampling areas. Prospecting, claiming, and some mining of largely polymetallic precious- and base-metal veins occurred in the Sangre de Cristo Range from the late 1800s through the early 1930s, with sporadic prospecting and some mining through the late 1980s (Ellis and others, 1983). Many of the vein networks are found along the western side of the mountains that are bounded by the Sangre de Cristo normal fault, a principal structure delineating a major segment of the Rio Grande rift. There also are mines along the crest and the northeast side of the range such as the Rita Alta copper mine. However, the locations of many claims, prospects, and mines were hand located on topographic and mine maps without modern spatial coordinate data and there were few analytical chemistry data available with properly associated geologic context. As a mandated component of the 1964 Wilderness Act, the USGS and USBoM were charged with identifying and assessing mineral resources in Federal lands known as Wilderness Study Areas (WSA; for example, Johnson and others, 1984). The Sangre de Cristo WSA included the mountainous areas from Poncha Pass in the north to the Blanca Peak area in the south. Approximately 75 to 85 percent of the study area was covered by aerial photographic inspection and sites were visited by Ellis and others (1983) as access allowed. One thousand three hundred and ten samples were fire assayed for gold and silver and spectrographically analyzed for 40 other elements including copper, lead, molybdenum, tungsten, and uranium. Select samples were also analyzed for specific elements by various other state-of-the-art analytic methods of the time: copper, lead, and molybdenum by atomic absorption, tungsten by colorimetry, and uranium by fluorimetry. Integration of mapping, field characterization, mineralogical, and chemical data resulted in the identification of 18 more or less distinct mineralized areas. Sample locations and a variety of site and mine maps were compiled and integrated into the MLA 65-83 report along with extensive tabulation on paper with all data organized by mineralized area. Most of the study area was ultimately designated as Wilderness in 1980 and the unique sand dunes and associated watersheds on the western side of the central portion of the range, originally designated Great Sand Dunes National Monument in 1932, were redesignated as a National Park and Preserve in 2004. During the late 1990's and 2000's the USGS completed extensive research in the Rio Grande Rift (for example, Hudson and Grauch, 2013) including the Sangre de Cristo Mountains and adjacent San Luis Valley. Much of the work focused on interpretation of new geophysical data and new geologic mapping as well as new analyses of mineralized areas and associated geologic structures. Overall, the absolute age, petrogenetic, and metallogenic affinities of the mineralized areas are poorly understood. However, some combination of magmatic, hydrothermal, structural, chemical, and fluid-related processes all contributed to the formation of the Sangre de Cristo mineral system. The digital data and information provided in this Data Release allows for public access to the information contained in the archived paper data record, report, and plates. This publication is useful in developing a better understanding of the geologic and tectonic framework, occurrences and controls on mineralization, and other Earth resources such as groundwater. References Cited Above Ellis, C.E., Hannigan, B.J., and Thomson, J.R., 1983, Mineral Investigation of Sangre de Cristo Wilderness Study Area, Alamosa, Custer, Fremont, Huerfano, and Saguache Counties, Colorado: U.S. Bureau of Mines Mineral Land Assessment preliminary report MLA 65-83, 190 p., 2 plates. Hudson, M.R., and Grauch, V.J.S., 2013, Introduction, in Hudson, M.R., and Grauch, V.J.S., eds., New Perspectives on Rio Grande Rift Basins: From Tectonics to Groundwater: Geological Society of America Special Paper, v. 494, p. v-xii, https://doi.org/10.1130/SPE494. Johnson, B.R., Lindsey, D.A., Ellis, C.E., Hannigan, B.J., and Thompson, J.R., 1984, Mineral Resource Potential of the Sangre de Cristo Wilderness Study Area, South-central Colorado: U.S. Geological Survey Miscellaneous Field Studies Map MF-1635-A and Pamphlet, 13 p., https://doi.org/10.3133/mf1635A.

Groundwater level elevation and temperature at the Lower Montane in the East River Watershed, Colorado. (ess_dive, 2021)
This groundwater level elevation and temperature data package is aimed at improving the predictive understanding of hydro-biogeochemical processes at the lower montane site in the East River Watershed, Colorado. The dataset is obtained using pressure transducers placed in shallow wells in the floodplain. This dataset contains data from wells with Location ID's ER-DOW (alias DO1West), ER-DOE (alias DO2East), ER-MBA1 (alias M1Bend1), ER-MBA2 (alias M1Bend2), ER-UPW (alias UP1West), ER-UPM (alias UP2), ER-UPE (alias UP3East). Another dataset contains the data from wells with Location ID's ER-CPA1 to ER-CPA6. Each file contains the water level elevation and the water temperature. Water level elevation have been obtained using the barometric pressure from the pressure transducer (Hobos sensor) in the well, barometric pressure from a sensor in air located at the same site (lower montane), depth from top-of-casing (TOC) to sensor measurement point, and TOC elevation. Data have been checked with a few measurements of water table depths. A real-time kinematic (RTK) global positioning system (GPS) has been used to survey the TOC (data in file WellLocation_WLdataArchive2018). The water level elevation is given in UTM13N Geoid2012AB. While depth to water level is not present in the data files, it can be easily calculated with the TOC and distance to ground provided in the GPS coordinate file. The dataset quality is discussed in Collection/Analysis section of the methods. Time-series of measurements will be added to this data package, so please check back for updates. If you have questions, please contact the author.

SnowEx20 Grand Mesa In Situ Dielectric Soil Moisture, Version 1 (other, 2021)

Biological, chemical, and physical data from the Phytoplankton Monitoring Network from 2001-09-13 to 2013-03-07 (NCEI Accession 0117942) - NCEI (other, 2021)
The Phytoplankton Monitoring Network (PMN) is a part of the National Centers for Coastal Ocean Science (NCCOS). The PMN was created as an outreach program to connect volunteers and professional scientists in the monitoring of marine phytoplankton and harmful algal blooms (HABs). NOAA staff train volunteers on sampling techniques and identification methods for marine phytoplankton. There are over 50 genera, including 10 potentially toxin producing genera, of dinoflagellates and diatoms on the volunteers watch list. A qualitative collection of data that includes salinity, temperature, depth, wind speed and direction, phytoplankton counts and abundance ratios obtained from surface tows in the estuarine and marine environments.

Surface soil temperature and water content from warming experiment located at the Rocky Mountain Biological Laboratory, Colorado, 2015 to 2019 - Chelsea Wilmer; Heidi Steltzer; Amanda Henderson; Kenneth Hurst Williams (ess_dive, 2021)
This data package consists of soil temperature and soil water content sensor data from the warming experiment near the Rocky Mountain Biological Laboratory. Data range is from summer 2015 to summer 2019, when the warming manipulation was terminated. The location of the warming experiment is in the upper montane life zone and consists of meadow vegetation with a mixture of sagebrush (Artemisia tridentata), forb species (Erigeron speciosus, Helianthella quinquenervis, Lathyrus lanszwertii), and graminoid species (Festuca thurberi, Carex spps). Early studies showed that the heating treatment led to earlier snowmelt as well as warmer and drier surface soils, and changes in the functional composition of aboveground biomass favoring sagebrush over forb species (Harte and Shaw, 1995). These changes were mainly observed in the upper, naturally drier zone for the experimental plots. More recent observations of aboveground biomass, soil carbon, and microbial composition require concurrent information about the abiotic environment for interpretation and extrapolation to process-based models. This data package provides the plot- and zone-level abiotic context for the final years of the experiment and consists of csv files with hourly soil temperature (WM_ST.csv) and soil water content (WM_SWC.csv).

East River Watershed Stable Water Isotope Data in Precipitation, Snowpack and Snowmelt 2016-2020 - Curtis Buetler; Curtis Buetler; Curtis Buetler; Wesley M. Brown; Wesley M. Brown; Wesley M. Brown; Alexander W. Newman; Alexander W. Newman; Alexander W. Newman; Kenneth Hurst Williams; Kenneth Hurst Williams; Kenneth Hurst Williams (ess_dive, 2021)
Stable water isotopes (d18O, d2H and d-excess) are important tracers in hydrologic research to understand water partitioning between vegetation, groundwater, and runoff but are rarely applied to large watersheds with persistent snowpack and complex topopgraphy. Data were collected for the Lawrence Berkeley National Laboratory Watershed Function Science Focus Area supported by the U.S Department of Energy in the East River, CO Hydrologic Unit Code (140200010) with limited data also collected in adjacent watersheds Ohio Creek and Taylor River. Data are provided in csv and includes isotopic information for precipitation (years 2014-2016), snowmelt (years 2016-2017) and snowpits (years 2016-2020). Snowpit data contain depth resolved information at 10 cm intervals for density, snow water equivalent (SWE) and stable water isotopes. Bulk isotopic data for 86 snowpits contain depth, SWE, density and SWE-weighted isotope values. Sampling locations and elevations are provided within the data files, while kmz files are provided to view sampling locations using Google Earth software.

SnowEx20 Grand Mesa IOP UNM 800 and 1600 MHz MALA GPR, Version 1 (other, 2021)

SnowEx20 Grand Mesa IOP CSU 1GHz GPR, Version 1 (other, 2021)

Soil bulk density and texture data collected during field survey associated with NEON AOP survey, East River, CO 2018. (ess_dive, 2021)
The purpose of soil core sampling was to determine soil bulk density, volumetric water content, and soil texture across the sites that were sampled in association with the National Ecological Observatory Network's Airborne Observation Platform (NEON AOP) in 2018. Soil cores were collected from surface (2.5-7.5 cm) and subsurface (50-55cm) depths at sampling sites across East River, Washington Gulch, Slate River, and Coal Creek watersheds in Gunnison, Colorado during the summer of 2018. Surface samples were weighed for determination of soil water content prior to dry down for bulk density calculations. For all samples, we measured dry weight and weight of < 2mm fraction and conducted soil textural analysis. We provide metadata for the samples, raw data files, python code that was used to calculate bulk density, water content, and texture fraction densities from primary datasets, and a final csv file with the calculated soil bulk density, volumetric water content, and soil texture data. Additional associated site metadata and vegetation fractional cover information can be found in the associated data release.

WHONDRS Surface Water Sampling for Metabolite Biogeography (Geochemistry and Aligned FTICR-MS). (ess_dive, 2021)
This dataset is from an ongoing global survey of surface water metabolites to provide understanding of the character of organic matter that may be delivered to subsurface sediments via hydrologic exchange. Data from this survey are published in batches. This first batch contains data from 27 sites. To implement the global survey, free stream sampling kits were provided to interested researchers throughout the world. Samples were collected with minimal constraints in terms of location, but following strict protocols, and shipped to the Environmental Molecular Sciences Laboratory (EMSL) for metabolomic analysis via Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS). In addition, basic geochemistry analyses (e.g., dissolved organic carbon concentration, cations, anions) were conducted, standardized photos of each field system were taken, surface water hydrographs were collated from existing instrumentation, and extensive metadata were captured. All data types are provided in a standard format.The data package contains an R function that will launch a GUI that can be used to easily search, visualize, compile, and download data. The data are free to be used for any purpose, such as for manuscripts, presentations, and grant proposals. Please use the data package’s DOI to cite the data package. Note that individual hydrographs have separate DOIs, which are provided in the associated hydrograph files. These hydrograph-specific DOIs should also be cited when using those data. We ask that you email us at WHONDRS@pnnl.gov to let us know that you're using the data and acknowledge WHONDRS and the U.S. Department of Energy's Subsurface Biogeochemical Research program—which generously provides funding to WHONDRS—in your documents, presentations, etc. There is no obligation to include WHONDRS members as co-authors. Please note that this data package was originally published in November 2018. It was updated in May 2020. See the readme file in the data package for details. None of the geochemistry or FTICR-MS data were altered between versions. The GUI was updated.

Mammalian herbivores restrict the altitudinal range limits of three alpine grass species (transplant and herbivore exclusion experiment and demographic data from natural populations), West Elk Mountains, Colorado, USA 2015-2018 (other, 2021)
Though rarely experimentally tested, biotic interactions have long been hypothesized to limit low-elevation range boundaries of species. We tested the effects of herbivory on three alpine-restricted plant species by transplanting plants below (novel), at the edge (limit), or in the center (core) of their current elevational range and factorially fencing-out above- and belowground mammals in the West Elk Mountains, Colorado, USA from 2015-2018. Herbivore damage was greater in range limit and novel habitats than in range cores. Exclosures increased plant biomass and reproduction more in novel habitats than in range cores, suggesting demographic costs of novel interactions with herbivores. We then used demographic models to project population growth rates, which increased 5-20% more under herbivore exclosure at range limit and novel sites than in core habitats. Our results identify mammalian herbivores as key drivers of the low-elevation range limits of alpine plants and indicate that upward encroachment of herbivores could trigger local extinctions by depressing plant population growth.

Subcanopy Potential Solar Radiation on Day of Year 265 for the Upper East River Derived from 2018 NEON AOP Data - Ian K Breckheimer (s3, 2021)
This dataset represents potential clear-sky incident solar radiation (in w/m^2) for day of year 265 (fall equinox), taking into account shading from topography, buildings, and vegetation greater than 1m in height. This map was generated with the GRASS GIS program r.sun and a subcanopy solar radiation model from Bode et al. 2014: Bode, C. A., Limm, M. P., Power, M. E., & Finlay, J. C. (2014). Subcanopy Solar Radiation model: Predicting solar radiation across a heavily vegetated landscape using LiDAR and GIS solar radiation models. Remote Sensing of Environment, 154, 387-397. The model assumes deciduous vegetation is in it's leaf-on condition (as is typical on that date).

Sub-Basin Delineation for the Upper East River, Colorado, United States. (ess_dive, 2021)
Upper East sub-basins are delineated as area contributing flow to SFA 2016 stream gage locations. Shapefile attributes include sub-basin ID, name, area (m2 and km2) and codes for spatial contributions to EBC and PH used by Carroll et al. (2018). Geospatial reference is UTM 1983 zone 13. JPEG image provided to show sub-basin delineation with respect to surface geology (Gothic Quadrangle: Gaskill et al., 1991; Maroon Bells Quadrangle: Bryant, 1969). This dataset can be opened using any GIS software (e.g. QGIS, ArcGIS).

Soil Environmental Conditions in the East River Watershed, CO. (ess_dive, 2021)
This dataset contains depth-resolved soil environmental variables collected between June 2016 and October 2018 from the Bradley Meadow site in the East River watershed. Datalogger output from 7 Campbell CS655 12 cm Soil Moisture and Temperature Sensors including depth, temperature, volumetric water content, and electrical conductivity are included in ‘BM_Merged_T_VWC_0616_10_18.csv’. Sensors were installed in June 2016. Data have been processed to merge raw sensor data and to remove additional variables. No additional QA/QC was performed. Measured pCO2 and depth are contained in ‘BM_EGM_WELL_CO2.csv’. These data represent gas well samples measured via injection using a PP Systems EGM-5 infra-red gas analyzer as described in the methods section. Measured CO2 surface flux values are contained in 'BM_EGM_Surface_Flux.csv'. These were measured using the PP Systems EGM-5 with the Soil Respiration Chamber attachment. Multiple reps are reported for each measurement including CO2 flux rate calculations using built-in linear and quadratic function methods, and average and standard deviations are taken across all reps and calculation methods.

Pollinator visitation rate and effectiveness vary with flowering phenology - Diane Cambell; M. Kate Gallagher (other, 2021)
Premise of the Study – Flowering time may influence pollination success and seed set through a variety of mechanisms, including seasonal changes in total pollinator visitation or the composition and effectiveness of pollinator visitors. Methods – We investigated mechanisms by which changes in flowering phenology influence pollination and reproductive success of Mertensia ciliata (Boraginaceae). We manipulated flowering onset of potted plants and assessed the frequency and composition of pollinator visitors, as well as seed set. We tested whether floral visitors differed in their effectiveness as pollinators by measuring pollen receipt and seed set resulting from single visits to virgin flowers. Key Results – Despite a five-fold decrease in pollinator visitation over four weeks, we detected no significant difference in seed set among plants blooming at different times. On a per-visit basis, each bumblebee transferred more conspecific pollen than did a solitary bee or a fly. The proportion of visits by bumblebees increased over the season, countering the decrease in visitation rate so that flowering time had little net effect on seed set. Conclusions – This work illustrates the need to consider pollinator effectiveness, along with changes in pollinator visitation and species composition to understand the mechanisms by which phenology impacts levels of pollination.

SnowEx20 Grand Mesa IOP UNM 800 and 1600 MHz MALA GPR, Version 1 (other, 2021)

Microclimate observations associated with snowmelt experiment gradient sites, East River, Colorado, 2017 to 2020 - Chelsea Wilmer; Heidi Steltzer; Chelsea Wilmer; Heidi Steltzer; Heidi Steltzer; Chelsea Wilmer; Heidi Steltzer; Amanda Henderson; Chelsea Wilmer; Heidi Steltzer; Chelsea Wilmer; Amanda Henderson; et al. (ess_dive, 2021)
The timing of snowmelt in mountain systems is a main driver of vegetation phenology and production, as well as recharge of soil moisture and ground water. Decreases in maximum snowpack and warmer spring temperatures have led to a higher frequency of early snowmelt. This study combines a natural elevation gradient with an experimental manipulation of snowmelt timing to assess the effect of earlier melt on hillslope and watershed ecohydrological processes. This data package includes csv files with plot and sub-plot level observations of soil temperature (SM_ST.csv), soil moisture (SM_SWC.csv), air temperature (SM_AirT.csv), and relative humidity (SM_rH.csv). The date range of this dataset includes a pre-treatment year (2017), two treatment years (2018 and 2019), and a post-treatment year (2020). Location IDs associated with this data package are: ER-LM, WG-UM, WG-LS, ER-US, and XX-AL. Related data packages include: “Colorado Elevation Gradient Snowmelt Manipulation Plant Phenology 2017-2018” and “Sensor-based phenology from snowmelt experiment gradient, East River, Colorado, 2017 to 2020”

Waterlevel, geochemical, and borehole data from Rifle, Colorado from 2006-2016 (ess_dive, 2021)
The files included in this data package provide site wide water level data, geochemical data, and borehole information associated with the Rifle site in Colorado during the Lawrence Berkeley National Lab (LBNL) led Integrated Field Research Challenge (IFRC) and Scientific Focus Area (SFA) research projects. The data informs hydrogeochemical interactions occurring in the watershed. The readme file contains detailed metadata for the files, including naming conventions, column headers, and data validation.The borehole information is provided in the file called rifle_boreholes.csv. It provides names and location for boreholes/wells at the Rifle. The waterlevel data is provided in the folder rifle_waterlevels. The geochemical data is provided in two folders: the rifle_floodplain_geochemistry folder has data which was collected from wells across the floodplain and a variety of offsite locations that contribute solutes to the floodplain given their upgradient locations. The rifle_plotC_geochemistry folder has data which was collected primarily in plot C, which was a focused study area in which a large number of groundwater manipulation / biostimulation experiments were conducted. While not all geochemical constituents are included for each well location and sampling date, they include anions, cations, trace metals, dissolved organic and inorganic carbon, stable isotopes of water and sulfur (as sulfate), and water quality parameters including pH, groundwater electrical conductivity (EC) and dissolved oxygen (DO). All files are in csv or txt format.

Talus Surface & Subsurface Temperature Data from Oregon & Colorado, USA, 2011-2019 (other, 2021)
Between 2011 and 2019, temperature data loggers were buried in rocky talus patches (hereafter “sites”) potentially occupied by American pikas (Ochotona princeps). Data collection spanned three ecoregions: Grand Mesa, Colorado (GRME), Mt. Hood, Oregon (MTHO), and the Columbia River Gorge, Oregon (CRGO). Sensors were placed either near the surface of the talus (shaded from sunlight) or in the interstices (75-80 cm deep) and programmed to record the temperature every 2-hours. At some sites when noted, surface sensors were placed directly above a paired interstitial sensor at the same GPS coordinate, and sensors were replaced each year. MTHO sites were located near or within the burn scar from the 2011 Dollar Lake Fire and spanned a range of burn severities (Varner et al. 2015, dx.doi.org/10.1071/WF15050). All CRGO sites except Mosier were within the range of pikas in this ecoregion and complement or extend previous analyses of talus microclimates in this ecoregion (Varner & Dearing 2014, dx.doi.org/10.1371/journal.pone.0104648; those data are available at https://collections.lib.utah.edu/ark:/87278/s63b984d).

Mammalian herbivores restrict the altitudinal range limits of three alpine grass species, West Elk Mountains, Colorado, USA 2015-2018 (other, 2021)
Though rarely experimentally tested, biotic interactions have long been hypothesized to limit low-elevation range boundaries of species. We tested the effects of herbivory on three alpine-restricted plant species by transplanting plants below (novel), at the edge (limit), or in the center (core) of their current elevational range and factorially fencing-out above- and belowground mammals in the West Elk Mountains, Colorado, USA from 2015-2018. Herbivore damage was greater in range limit and novel habitats than in range cores. Exclosures increased plant biomass and reproduction more in novel habitats than in range cores, suggesting demographic costs of novel interactions with herbivores. We then used demographic models to project population growth rates, which increased 5-20% more under herbivore exclosure at range limit and novel sites than in core habitats. Our results identify mammalian herbivores as key drivers of the low-elevation range limits of alpine plants and indicate that upward encroachment of herbivores could trigger local extinctions by depressing plant population growth.

1 m Resolution 4-band orthomosaic for the Upper Gunnison Basin derived from September 2019 NAIP Imagery - Ian K Breckheimer (s3, 2021)
This is a 1m resolution aerial imagery orthomosaic resampled from 0.6m 4-band orthoimagery collected on September 14th 2019 as part of the USDA National Aerial Imagery Program. The original NAIP tiles were reprojected, mosaiced and bilinearly resampled to the standard UG 1m grid, and compressed using a JPEG algorithm (90% quality) to reduce the resulting file size. The 4 bands correspond to brightness in Red (band 1), Green (band 2), Blue (band 3), and Near-IR (band 4), recorded as digital numbers scaled between 0 and 255.

Talus Surface & Subsurface Temperature Data from Oregon & Colorado, USA, 2011-2019 (other, 2021)
Between 2011 and 2019, temperature data loggers were buried in rocky talus patches (hereafter “sites”) potentially occupied by American pikas (Ochotona princeps). Data collection spanned three ecoregions: Grand Mesa, Colorado (GRME), Mt. Hood, Oregon (MTHO), and the Columbia River Gorge, Oregon (CRGO). Sensors were placed either near the surface of the talus (shaded from sunlight) or in the interstices (75-80 cm deep) and programmed to record the temperature every 2-hours. At some sites when noted, surface sensors were placed directly above a paired interstitial sensor at the same GPS coordinate, and sensors were replaced each year. MTHO sites were located near or within the burn scar from the 2011 Dollar Lake Fire and spanned a range of burn severities (Varner et al. 2015, dx.doi.org/10.1071/WF15050). All CRGO sites except Mosier were within the range of pikas in this ecoregion and complement or extend previous analyses of talus microclimates in this ecoregion (Varner & Dearing 2014, dx.doi.org/10.1371/journal.pone.0104648; those data are available at https://collections.lib.utah.edu/ark:/87278/s63b984d).

SnowEx20 Grand Mesa Reference GIS Data Sets, Version 1 (other, 2021)

Data release for Surficial Geology of the Northern San Luis Valley, Saguache, Fremont, Custer, Alamosa, Rio Grande, Conejos, and Costilla Counties, Colorado (other, 2021)
The San Luis Valley and associated underlying basin of south-central Colorado and north-central New Mexico is the largest structural and hydrologic basin of the Rio Grande Rift and fluvial system. The surrounding San Juan and Sangre de Cristo Mountains reveal evidence of widespread volcanism and transtensional tectonism beginning in the Oligocene and continuing to the present, as seen in fault displacement of Pleistocene to Holocene deposits along the eastern basin-bounding Sangre de Cristo fault system and fault zones along the western margin of the basin. The San Luis basin can generally be subdivided into northern and southern basins at the structural and physiographic high terrain of the San Luis Hills in the center of the basin, proximal to the Colorado-New Mexico stateline. The northern San Luis Valley can be subdivided into two subbasins at approximately the latitude of the Great Sand Dunes and San Luis Lakes, where the endorheic northern subbasin surface and subsurface flow currently accumulate in a series of playa lakes. To the south of this playa region, the Rio Grande has captured basin hydrology into a through-going fluvial system cutting through the San Luis Hills, carving the Rio Grande gorge, and ultimately flowing into the Gulf of Mexico. This surficial geologic map of the northern San Luis Valley, paired with the Alamosa, CO 1:100,000-scale geologic map (U.S. Geological Survey Scientific Investigations Map 3342) provides new and compiled geologic mapping that characterizes basin deposits and locates the traces of active faults, with the goal to provide geospatial data for future investigations related to western North American neotectonics, Pleistocene paleoclimate, and related geomorphic processes. In addition, present natural and anthropogenic water bodies have been located and updated for hydrologic modeling and water-usage investigations.

xprecipradar (00) (2021)
[object Object]

Sensor-based phenology from snowmelt experiment gradient, East River, Colorado, 2017 to 2020 (ess_dive, 2021)
The timing of snowmelt is a critical cue for the initiation of growth in mountain meadow ecosystems and can also impact the duration and magnitude of plant production. High frequency observations of species-level phenology are time consuming and require a high degree of expertise, and publicly available remote sensing products lack the necessary temporal resolution to assess fine-scale growing season dynamics. Near-surface sensing methods provide a middle ground with high temporal frequency and tractable spatial scales (from sub-meter to hillslope scale). This data package includes csv files of Normalized Difference Vegetation Index (NDVI) timeseries (SM_NDVI_dailymax.csv) and phenological thresholds (SM_NDVI_summary.csv) for sub-plots (1m2) and Green Chromatic Coordinate (GCC) phenological thresholds (SM_GCC_summary.csv) at the plot scale (10m x 14m). Location IDs associated with this data package are: ER-LM, WG-UM, WG-LS, ER-US, and XX-AL. Related data packages include: “Microclimate observations associated with snowmelt experiment gradient sites, East River, Colorado, 2017 to 2020” and “Colorado Elevation Gradient Snowmelt Manipulation Plant Phenology 2017-2018”.

Hillslope subsurface flow and transport data for the PLM transect in East River, Colorado. (ess_dive, 2021)
This file contains data used to calculate subsurface flow and transport at the Pumphouse Lower Montane (PLM) hillslope transect. Information includes locations, weather data, hydraulic conductivities, hydraulic head profiles, soil water profiles, depths to the water table, specific conductance (SC) and dissolved organic carbon (DOC) in pore waters, water isotopic composition, calculated subsurface fluxes, calculated subsurface transport concentrations for SC and DOC, East River discharge and SC, transect soil particle-size distributions, and moisture characteristic curves. Files were updated on 2019-12-03: Figure 7 now includes data on the hydraulic gradient (data added in column N of the sheet for Fig. 7). There is a new Figure 14 that shows impacts of assigning different hydraulic conductivities to the soil and weathering zone. The old Figure 14 is now Figure 15. In the supporting Information, Figures S3 is added (on pressure responses of samplers) and S4 (on water table depth relations with hydraulic gradients and transmissivity fluxes. Revised Supporting Information is now attached.

East River Surface and Pore Water FTICR-MS Data Associated with “Implications of sample treatment on characterization of the riverine environmental metabolome” (ess_dive, 2021)
Surface and pore water samples were collected from distributed locations around Meander A in East River (Crested Butte, CO, USA) during the summer of 2018. This dataset consists of the characterization of dissolved organic matter using 12 Tesla Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS; in .xml format) analyzed through the Environmental Molecular Sciences Laboratory (EMSL; https://www.pnnl.gov/environmental-molecular-sciences-laboratory) using two different sample pre-treatment methods (solid phase extraction, no solid phase extraction) and two electrospray ionization methods (ESI-positive, ESI-negative) to identify the impacts of these choices on the final dataset. This study aimed to understand how the different sample processing methods influence the resulting FTICR-MS dataset. Any published work that utilizes data presented in this dataset should cite the dataset using the DOI number. If using the dataset, please acknowledge the U.S. Department of Energy (DOE) Office of Science (BER) Subsurface Biogeochemical Research (SBR) program, the Environmental Molecular Sciences Laboratory (EMSL), and Worldwide Hydrobiogeochemical Observation Network for Dynamic River Systems (WHONDRS). The publication DOI will be added to this abstract when available.

SnowEx20 Grand Mesa Autumn 2019 Snow Pits, Version 1 (other, 2021)

Sea surface temperature (SST) and surface current data collected from the Mar Mostro during the around-the-world Volvo Ocean Race (VOR) from 2011-11-05 to 2012-07-12 (NCEI Accession 0130694) - NCEI (other, 2021)
Navigation, surface current, sea surface temperature, wind, and atmospheric pressure data collected by the Mar Mostro during the around-the-world Volvo Ocean Race (VOR) 2011-2012 (http://www.volvooceanrace.com/en/home.html). The Mar Mostro is a 21.5m sail-powered racing yacht that was manned by the Puma Ocean Racing team (sponsored by the PUMA sports apparel company) and powered by Berg Propulsion of Sweden. Data were provided to the Center for Ocean-Atmospheric Prediction Studies at the Florida State University by Robert Hopkins, Jr. who served as the performance analyst and coach for the Mar Mostro during the 2011-2012 VOR. Co-author for the data was Tom Addis, Navigator and crew member for the team.

SnowEx20 Grand Mesa IOP CSU 1GHz GPR, Version 1 (other, 2021)

East River Surface and Pore Water FTICR-MS Data Associated with “Implications of sample treatment on characterization of the riverine environmental metabolome” (ess_dive, 2021)
Surface and pore water samples were collected from distributed locations around Meander A in East River (Crested Butte, CO, USA) during the summer of 2018. This dataset consists of the characterization of dissolved organic matter using 12 Tesla Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS; in .xml format) analyzed through the Environmental Molecular Sciences Laboratory (EMSL; https://www.pnnl.gov/environmental-molecular-sciences-laboratory) using two different sample pre-treatment methods (solid phase extraction, no solid phase extraction) and two electrospray ionization methods (ESI-positive, ESI-negative) to identify the impacts of these choices on the final dataset. This study aimed to understand how the different sample processing methods influence the resulting FTICR-MS dataset. Any published work that utilizes data presented in this dataset should cite the dataset using the DOI number. If using the dataset, please acknowledge the U.S. Department of Energy (DOE) Office of Science (BER) Subsurface Biogeochemical Research (SBR) program, the Environmental Molecular Sciences Laboratory (EMSL), and Worldwide Hydrobiogeochemical Observation Network for Dynamic River Systems (WHONDRS). The publication DOI will be added to this abstract when available.

Marmot mass gain rates relate to their group’s social structure - Conner S. Philson; Daniel T. Blumstein; Sophia Todorov (other, 2021)
Mass gain is an important fitness correlate for survival in highly seasonal species. While many physiological, genetic, life history, and environmental factors can influence mass gain, more recent work suggests the specific nature of an individual’s own social relationships also influences mass gain. However, less is known about consequences of social structure for individuals. We studied the association between social structure, quantified via social network analysis, and annual mass gain in yellow-bellied marmots (Marmota flaviventer). Social networks were constructed from 31,738 social interactions between 671 individuals in 125 social groups from 2002 to 2018. Using a refined dataset of 1,022 observations across 587 individuals in 81 social groups, we fitted linear mixed models to analyze the relationship between attributes of social structure and individual mass gain. We found that individuals residing in more connected and unbreakable social groups tended to gain proportionally less mass. However, these results were largely age dependent. Adults, who form the core of marmot social groups, residing in more spread apart networks had greater mass gain than those in tighter networks. Yearlings, involved in a majority of social interactions, and those who resided in socially homogeneous and stable groups had greater mass gain. These results show how the structure of the social group an individual resides in may have consequences for a key fitness correlate. But, importantly, this relationship was age-dependent.

Oceanographic temperature profiles from the HMS CHALLENGER in the Antarctic, North Atlantic and other locations from 1873-02-15 to 1876-05-06 (NCEI Accession 0126754) - NCEI (other, 2021)
From 1872 to 1876, the HMS Challenger sailed around the world studying ocean features such as ocean temperature and chemistry, wildlife, and sounding the ocean, discovering undersea features like seamounts and ocean trenches. This expedition marked the beginning of the modern study of oceanography. The temperature and meteorology data were digitized from the historical cruise report at http://www.19thcenturyscience.org/HMSC/HMSC-Reports/1895-Summary/htm/doc.html.

1 m Resolution 4-band orthoimagery for the Upper Gunnison Basin derived from October 2017 NAIP imagery - Ian K Breckheimer (s3, 2021)
This is a 1m resolution map of Normalized Differential Vegetation Index (NDVI) derived from resampled 0.6m 4-band orthoimagery collected as part of the USDA National Aerial Imagery Program. The NAIP tiles were mosaiced and bilinearly resampled to the standard UG 1m grid before calculating NDVI as (NIR-Red) / (NIR+Red). The NAIP Imagery for this area was collected on October 10th, 2017.

Ecological causes and consequences of flower color polymorphism in a self-pollinating plant (Boechera stricta) - Priya; Vaidya (other, 2021)
Intraspecific variation in flower color is often attributed to pollinator-mediated selection, yet this mechanism cannot explain flower color polymorphisms in self-pollinating species. Indirect selection mediated via biotic and abiotic stresses could maintain flower color variation in these systems. The selfing forb, Boechera stricta, typically displays white flowers, but some individuals produce purple flowers. We quantified environmental correlates of flower color in natural populations. To disentangle plasticity from genotypic variation, we performed a multiyear field experiment in five gardens. In controlled conditions, we evaluated herbivore preferences and the effects of drought stress and soil pH on flower color expression. In natural populations, purple-flowered individuals experienced lower foliar herbivory than did their white-flowered counterparts. This pattern also held in the common gardens. Additionally, low-elevation environments induced pigmented flowers (plasticity), and the likelihood of floral pigmentation decreased with source elevation of maternal families (genetic cline). Viability selection favored families with pigmented flowers. In the laboratory, herbivores exerted greater damage on tissue derived from white- vs purple-flowered individuals. Furthermore, drought induced pigmentation in white-flowered lineages, and white-flowered plants had a fecundity advantage in the well-watered control. Flower color variation in selfing species is probably maintained by herbivory, drought stress, and other abiotic factors that vary spatially.

SnowEx20 Grand Mesa Autumn 2019 Snow Water Equivalent, Version 1 (other, 2021)

Mask for the Upper Gunnison SDP Domain at 1m resolution - Ian K Breckheimer (s3, 2021)
This is a 1m resolution binary map representing areas within the Upper Gunnison Domain of the RMBL Spatial Data Platform.

1 m Resolution topographic slope for the Upper Gunnison Basin derived from 2015 and 2019 LiDAR data. - Ian K Breckheimer (s3, 2021)
This is a 1 m resolution map of topographic slope (measured in degrees) computed using a 3*3 pixel kernel and Horn's formula. It is derived from a 1m resolution Digital Elevation Model (DEM) for the Upper Gunnison River derived from public LiDAR datasets. The primary data source was a 2019 LiDAR collection for Gunnison County. A small portion of the upper basin was not covered by this dataset, and for those areas, data from a 2015 acquisition was substituted.

Digital Data from Mineral Investigation of Sangre de Cristo Wilderness Study Area, Alamosa, Custer, Fremont, Huerfano, and Saguache Counties, Colorado, USA (other, 2021)
This Data Release provides tabular and geospatial data digitized by the U.S. Geological Survey (USGS) from a U.S. Bureau of Mines (USBoM) report titled Mineral Investigation of Sangre de Cristo Wilderness Study Area, Alamosa, Custer, Fremont, Huerfano, and Saguache Counties, Colorado. The original preliminary paper report, numbered Mineral Land Assessment 65-83 (MLA 65-83; Ellis and others, 1983), presented the results of a mineral resource potential survey of areas in and around the Sangre de Cristo Range flanking the northeastern extent of San Luis Valley in south-central Colorado. Included in this Data Release are georeferenced scans of the regional plate maps, digitized sample site locations, analytical chemistry, and structural geologic data from MLA 65-83 in a modern and searchable geospatial database. In addition to the maps and associated point locations, the dataset contains 1,262 rows and 58 columns of contextual and numeric information in the main data table, as well as a table describing 97 samples excluded from the MLA report, a table of summary deposit information, a table of USBoM inventory data for the prepared and stored rock samples, and geospatial boundary data of the Sangre de Cristo Wilderness, Wilderness Study Area (WSA), and mineralized sampling areas. Prospecting, claiming, and some mining of largely polymetallic precious- and base-metal veins occurred in the Sangre de Cristo Range from the late 1800s through the early 1930s, with sporadic prospecting and some mining through the late 1980s (Ellis and others, 1983). Many of the vein networks are found along the western side of the mountains that are bounded by the Sangre de Cristo normal fault, a principal structure delineating a major segment of the Rio Grande rift. There also are mines along the crest and the northeast side of the range such as the Rita Alta copper mine. However, the locations of many claims, prospects, and mines were hand located on topographic and mine maps without modern spatial coordinate data and there were few analytical chemistry data available with properly associated geologic context. As a mandated component of the 1964 Wilderness Act, the USGS and USBoM were charged with identifying and assessing mineral resources in Federal lands known as Wilderness Study Areas (WSA; for example, Johnson and others, 1984). The Sangre de Cristo WSA included the mountainous areas from Poncha Pass in the north to the Blanca Peak area in the south. Approximately 75 to 85 percent of the study area was covered by aerial photographic inspection and sites were visited by Ellis and others (1983) as access allowed. One thousand three hundred and ten samples were fire assayed for gold and silver and spectrographically analyzed for 40 other elements including copper, lead, molybdenum, tungsten, and uranium. Select samples were also analyzed for specific elements by various other state-of-the-art analytic methods of the time: copper, lead, and molybdenum by atomic absorption, tungsten by colorimetry, and uranium by fluorimetry. Integration of mapping, field characterization, mineralogical, and chemical data resulted in the identification of 18 more or less distinct mineralized areas. Sample locations and a variety of site and mine maps were compiled and integrated into the MLA 65-83 report along with extensive tabulation on paper with all data organized by mineralized area. Most of the study area was ultimately designated as Wilderness in 1980 and the unique sand dunes and associated watersheds on the western side of the central portion of the range, originally designated Great Sand Dunes National Monument in 1932, were redesignated as a National Park and Preserve in 2004. During the late 1990's and 2000's the USGS completed extensive research in the Rio Grande Rift (for example, Hudson and Grauch, 2013) including the Sangre de Cristo Mountains and adjacent San Luis Valley. Much of the work focused on interpretation of new geophysical data and new geologic mapping as well as new analyses of mineralized areas and associated geologic structures. Overall, the absolute age, petrogenetic, and metallogenic affinities of the mineralized areas are poorly understood. However, some combination of magmatic, hydrothermal, structural, chemical, and fluid-related processes all contributed to the formation of the Sangre de Cristo mineral system. The digital data and information provided in this Data Release allows for public access to the information contained in the archived paper data record, report, and plates. This publication is useful in developing a better understanding of the geologic and tectonic framework, occurrences and controls on mineralization, and other Earth resources such as groundwater. References Cited Above Ellis, C.E., Hannigan, B.J., and Thomson, J.R., 1983, Mineral Investigation of Sangre de Cristo Wilderness Study Area, Alamosa, Custer, Fremont, Huerfano, and Saguache Counties, Colorado: U.S. Bureau of Mines Mineral Land Assessment preliminary report MLA 65-83, 190 p., 2 plates. Hudson, M.R., and Grauch, V.J.S., 2013, Introduction, in Hudson, M.R., and Grauch, V.J.S., eds., New Perspectives on Rio Grande Rift Basins: From Tectonics to Groundwater: Geological Society of America Special Paper, v. 494, p. v-xii, https://doi.org/10.1130/SPE494. Johnson, B.R., Lindsey, D.A., Ellis, C.E., Hannigan, B.J., and Thompson, J.R., 1984, Mineral Resource Potential of the Sangre de Cristo Wilderness Study Area, South-central Colorado: U.S. Geological Survey Miscellaneous Field Studies Map MF-1635-A and Pamphlet, 13 p., https://doi.org/10.3133/mf1635A.

SnowEx20 Grand Mesa Autumn 2019 Snow Pits, Version 1 (other, 2021)

East River Surface and Pore Water FTICR-MS Data Associated with “Implications of sample treatment on characterization of the riverine environmental metabolome” (ess_dive, 2021)
Surface and pore water samples were collected from distributed locations around Meander A in East River (Crested Butte, CO, USA) during the summer of 2018. This dataset consists of the characterization of dissolved organic matter using 12 Tesla Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS; in .xml format) analyzed through the Environmental Molecular Sciences Laboratory (EMSL; https://www.pnnl.gov/environmental-molecular-sciences-laboratory) using two different sample pre-treatment methods (solid phase extraction, no solid phase extraction) and two electrospray ionization methods (ESI-positive, ESI-negative) to identify the impacts of these choices on the final dataset. This study aimed to understand how the different sample processing methods influence the resulting FTICR-MS dataset. Any published work that utilizes data presented in this dataset should cite the dataset using the DOI number. If using the dataset, please acknowledge the U.S. Department of Energy (DOE) Office of Science (BER) Subsurface Biogeochemical Research (SBR) program, the Environmental Molecular Sciences Laboratory (EMSL), and Worldwide Hydrobiogeochemical Observation Network for Dynamic River Systems (WHONDRS). The publication DOI will be added to this abstract when available.

SnowEx20 SnowEx Grand Mesa Automated Meteorological and Snow Station Observations 2016-2021, version 1 (other, 2021)

East River Surface and Pore Water FTICR-MS Data Associated with “Implications of sample treatment on characterization of the riverine environmental metabolome” (ess_dive, 2021)
Surface and pore water samples were collected from distributed locations around Meander A in East River (Crested Butte, CO, USA) during the summer of 2018. This dataset consists of the characterization of dissolved organic matter using 12 Tesla Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS; in .xml format) analyzed through the Environmental Molecular Sciences Laboratory (EMSL; https://www.pnnl.gov/environmental-molecular-sciences-laboratory) using two different sample pre-treatment methods (solid phase extraction, no solid phase extraction) and two electrospray ionization methods (ESI-positive, ESI-negative) to identify the impacts of these choices on the final dataset. This study aimed to understand how the different sample processing methods influence the resulting FTICR-MS dataset. Any published work that utilizes data presented in this dataset should cite the dataset using the DOI number. If using the dataset, please acknowledge the U.S. Department of Energy (DOE) Office of Science (BER) Subsurface Biogeochemical Research (SBR) program, the Environmental Molecular Sciences Laboratory (EMSL), and Worldwide Hydrobiogeochemical Observation Network for Dynamic River Systems (WHONDRS). The publication DOI will be added to this abstract when available.

SnowEx20 Grand Mesa IOP CSU 1GHz GPR Raw, Version 1 (other, 2021)

SnowEx20 Grand Mesa IOP CSU 1GHz GPR Raw, Version 1 (other, 2021)

Data from: Selection of floral traits by pollinators and seed predators during sequential life history stages - Heather M. Briggs; Paula Sosenski; Mascha Bischoff; Robert A. Raguso; Diane R. Campbell (other, 2021)
Organismal traits often influence fitness via interactions with multiple species. That selection is not necessarily predictable from pairwise interactions, such as when interactions occur during different lifecycle stages. Theoretically, directional selection during two sequential episodes, e.g., pollination and seed survival, can generate quadratic or correlational selection for a set of traits that passes both selective filters. We compared strength of selection during pollination versus seed predation in the field and tested whether interactions with multiple species give rise to non-linear selection on floral traits. We planted common gardens with seeds of two species of Ipomopsis and hybrids in sites where pollination was primarily by hummingbirds or also included hawkmoths. We examined selection on six floral traits, including corolla width, sepal width, color, nectar, and two scent compounds. Female fitness (seeds) was broken down into fitness during (1) pollination (seeds initiated) and (2) seed predation (proportion seeds escaping fly predation). All traits showed evidence of selection. Directional and quadratic selection were stronger during seed initiation than seed predation. Correlational selection occurred mostly during seed initiation rather than arising from combining species interactions at two points in the lifecycle. These results underscore how multispecies interations can combine to exert selection on trait combinations.

Bee phenology is predicted by climatic variation and functional traits - Stemkovski; Michael (other, 2021)
Climate change is shifting the environmental cues that determine the phenology of interacting species. Plant-pollinator systems may be susceptible to temporal mismatch if bees and flowering plants differ in their phenological responses to warming temperatures. While the cues that trigger flowering are well-understood, little is known about what determines bee phenology. Using Generalized Additive Models, we analyzed time-series data representing 67 bee species collected over nine years in the Colorado Rocky Mountains to perform the first community-wide quantification of the drivers of bee phenology. Bee emergence was sensitive to climatic variation, advancing with earlier snowmelt timing, while later phenophases were best explained by functional traits including overwintering stage and nest location. Comparison of these findings to a long-term flower study showed that bee phenology is less sensitive than flower phenology to climatic variation, indicating potential for reduced synchrony of flowers and pollinators under climate change.

Basin Characteristic Layers for the Upper Colorado & Gunnison Rivers Pilot Project for StreamStats 2020 - Taylor H Rowley; Katharine R Kolb; Theodore B Barnhart (other, 2021)
The U.S. Geological Survey (USGS) calculated multiple basin characteristics as part of preparing the Upper Colorado & Gunnison Rivers Pilot StreamStats application. These datasets are raster representations of various environmental, geological, and land use attributes within the Upper Colorado & Gunnison Rivers study area (also known as the Next-Generation Water Observing System, or NGWOS), and will be served in the National StreamStats application (https://streamstats.usgs.gov) to describe delineated watersheds. The StreamStats application provides access to spatial analysis tools that are useful for water-resources planning and management, and for engineering and design purposes. The map-based user interface can be used to delineate drainage areas, to retrieve basin characteristics, to estimate flow statistics, and more.

1 m Resolution WGS84 UTM Zone 13N Y Coordinate for the Upper Gunnison Domain - Ian K Breckheimer (s3, 2021)
This map records the UTM Y Coordinate (in meters) for every pixel in the Upper Gunnison Domain, as measured using the WGS84 UTM Zone 13N Coordinate System (EPSG:32613). This map is useful for spatial prediction in models that explicitly incorporate geographic relationships, such as regression models that include a linear or non-linear spatial trend. UTM is a projected coordinate system that preserves distances.

1m Resolution NDVI for the Upper Gunnison Basin derived from October 2017 NAIP Imagery - Ian K Breckheimer (s3, 2021)
This is a 1m resolution map of Normalized Differential Vegetation Index (NDVI) derived from resampled 0.6m 4-band orthoimagery collected as part of the USDA National Aerial Imagery Program. The NAIP tiles were mosaiced and bilinearly resampled to the standard UG 1m grid before calculating NDVI as (NIR-Red) / (NIR+Red). The NAIP Imagery for this area was collected on October 10th, 2017.

Depth and elevation of floodplain fine sediment along the East River near Crested Butte, Colorado measured in 2016 and 2017. (ess_dive, 2021)
The depth of floodplain fine sediment was measured at 1,601 points along the East River near Crested Butte, Colorado spanning a study reach approximately 800 m in length in 2016 and 2017. These depths are being used to estimate the volume of floodplain sediment present along the study reach, converted into mass of sediment using bulk density measurements, and finally used to estimate the mass of organic carbon stored in the floodplain based on elemental analysis of percent organic carbon content. Recorded depths include a minimum of 1 cm, a median of 56 cm, a maximum of 175 cm, and a mean with standard deviation of 61 ± 34 cm. This data include a csv file of the coordinates for each point in NAD 83 UTM zone 13, measured sediment depths, distance from the river channel active during 2015 measured using geographic information systems, the elevation of the floodplain surface derived from 0.5-m resolution lidar, and the elevation of the underlying gravel/bedrock surface, and in some cases the distance from the active channel measured in the field along the sampling transect. Also included is an ESRI ArcMap shapefile of the measurement points complete with the data listed above.

Sensor-based phenology from snowmelt experiment gradient, East River, Colorado, 2017 to 2020 (ess_dive, 2021)
The timing of snowmelt is a critical cue for the initiation of growth in mountain meadow ecosystems and can also impact the duration and magnitude of plant production. High frequency observations of species-level phenology are time consuming and require a high degree of expertise, and publicly available remote sensing products lack the necessary temporal resolution to assess fine-scale growing season dynamics. Near-surface sensing methods provide a middle ground with high temporal frequency and tractable spatial scales (from sub-meter to hillslope scale). This data package includes csv files of Normalized Difference Vegetation Index (NDVI) timeseries (SM_NDVI_dailymax.csv) and phenological thresholds (SM_NDVI_summary.csv) for sub-plots (1m2) and Green Chromatic Coordinate (GCC) phenological thresholds (SM_GCC_summary.csv) at the plot scale (10m x 14m). Location IDs associated with this data package are: ER-LM, WG-UM, WG-LS, ER-US, and XX-AL. Related data packages include: “Microclimate observations associated with snowmelt experiment gradient sites, East River, Colorado, 2017 to 2020” and “Colorado Elevation Gradient Snowmelt Manipulation Plant Phenology 2017-2018”.

National Assessment of Oil and Gas Project - Southwestern Wyoming Province (037) Boundary - U.S. Geological Survey - CERSC Data Management Services Project (other, 2021)
The USGS Central Region Energy Team assesses oil and gas resources of the United States. The onshore and State water areas of the United States comprise 71 provinces. Within these provinces, Total Petroleum Systems are defined and Assessment Units are defined and assessed. Each of these provinces is defined geologically, and most province boundaries are defined by major geologic changes. The Southwestern Wyoming Province is located in northeastern Utah, northwestern Colorado and southwestern Wyoming, encompassing all or parts of Eagle, Garfield, Moffat, Rio Blanco, and Routt Counties in Colorado and all or parts of Carbon, Fremont, Lincoln, Sweetwater, Sublette, Teton, and Uintah Counties in Wyoming and all or parts of Summit and Daggett [...]

An organizing feature of bumble bee life history: worker emergence promotes queen reproduction and survival in young nests - Naoki Yamanaka; Kerry Mauck; Penglin Sun; Damaris Rodriguez-Arellano; S. Hollis Woodard (other, 2021)
Bumble bee queens initiate nests solitarily and transition to living socially once they successfully rear their first cohort of offspring. Bumble bees are disproportionately important for early season pollination, and many populations are experiencing dramatic declines. In this system, the onset of the social stage is critical for nest survival, yet the mechanisms that facilitate this transition remain understudied. Further, the majority of conservation efforts targets the social stage of the bumble bee life cycle and do not address the solitary founding stage. We experimentally manipulated the timing of worker emergence in young nests of bumble bee (Bombus impatiens) queens to determine whether and how queen fecundity and survival are impacted by the emergence of workers in the nest. We found that queens with workers added to the nest exhibit increased ovary activation, accelerated egg laying, elevated juvenile hormone (JH) titres and also lower mortality relative to solitary queens. We also show that JH is more strongly impacted by the social environment than associated with queen reproductive state, suggesting that this key regulator of insect reproduction has expanded its function in bumble bees to also influence social organization. We further demonstrate that these effects are independent of queen social history, suggesting that this underlying mechanism promoting queen fecundity is reversible and short lived. Synchronization between queen reproductive status and emergence of workers in the nest may ultimately increase the likelihood of early nesting success in social systems with solitary nest founding. Given that bumble bee workers regulate queen physiology as we have demonstrated, the timing of worker emergence in the nest likely impacts queen fitness, colony developmental trajectories and ultimately nesting success. Collectively, our findings underline the importance of conservation interventions for bumble bees that support the early nesting period and facilitate the production and maintenance of workers in young nests.

NEON AOP foliar trait maps, maps of model uncertainty estimates, and conifer map, East River, CO 2018. (ess_dive, 2021)
This data package contains mapped trait estimates and their uncertainties, and conifer map, for the National Ecological Observatory Network's Airborne Observation Platform survey data acquired over the Upper East River, Colorado in 2018. For full details, please see associated reference. in brief, trait models were developed independently for needle and non-needle leaf species using partial least squares regression (PLSR) using ground data from additional datasets: doi:10.15485/1618130, doi:10.15485/1618132, and doi:10.15485/1631278, merged with extracted spectral data from doi:10.15485/1618131. We separated vegetated pixels into needle and non-needle classes in order to generate a classification map based on the spectral differences between these leaf types (conifer.tif). We trained a deep learning model with custom architecture, detailed in Chadwick et al. In Press. The model performed with 0.998 true positive rate and 0.982 true negative rate, with ‘positives’ being non-needle identification. We then utilized PLSR to generate models of foliar traits for each leaf type. So that we could also map uncertainty in these predictions, we generated ten different models for needle and non-needle leaf species using different testing holdout sets of discrete sites. Each of these models was developed with a 100-fold cross validation procedure that utilized a 70% training set and 30% validation set with each fold, and then assessed based on the 10% of testing sites that were not included in that model’s development. The mean predicted value across the 10 models is used for the trait estimate in each pixel across the study area. The models are applied according to the leaf type designation in the conifer.tif map. The errors are the standard deviation across the 10 different models developed, with high error suggesting instability in model prediction and areas where values may not be reliable for ecological inference. These maps are only applied to areas with a NDVI > 0.5 to exclude non-vegetated areas. Shade masks could be applied to these data (doi:10.15485/1618131), but have not been for this data package. These data are also available on Google Earth Engine: https://code.earthengine.google.com/?asset=users/kdc/ER_NEON

1 m Resolution WGS84 UTM Zone 13N X Coordinate for the Upper Gunnison Domain - Ian K Breckheimer (s3, 2021)
This map records the UTM X Coordinate (measured in meters) for every pixel in the Upper Gunnison Domain, as measured using the WGS84 UTM Zone 13N Coordinate System (EPSG:32613). This map is useful for spatial prediction in models that explicitly incorporate geographic relationships, such as regression models that include a linear or non-linear spatial trend. UTM is a projected coordinate system that preserves distances.

Assessment of Spatiotemporal Variability of Evapotranspiration and Its Governing Factors in a Mountainous Watershed at the East River, Colorado, Water: Dataset. (ess_dive, 2021)
This data package contains simulation results of daily evapotranspiration for 17 locations of meteorological stations with different precipitation, air temperature and vegetation within the East River Watershed, Colorado (CLMResult.csv). Daily precipitation data is included for reference. These are the main results of the paper Tran, 2019. Meteorological stations names, latitude and longitude coordinates of meteorological stations, types of lands from the National Land Cover Database, and a comparison with the community land model (CLM) data are also included (Met_LC.csv). The purpose of this data is to analyze the spatio-temporal variations of evapotranspiration at the East River Watershed and understand the factors that control these variations. More information regarding the study, methods, and findings can be found in the Related Reference paper.

Bare-earth Potential Solar Radiation on Day of Year 265 for the Upper East River Derived from 2018 NEON AOP Data - Ian K Breckheimer (s3, 2021)
This dataset represents potential clear-sky incident solar radiation (in w/m^2) for day of year 265 (fall equinox), taking into account shading from topography and man-made structures, but not vegetation. This map was generated with the GRASS GIS program r.sun.

Soil Nitrogen, Water Content, Microbial Biomass, and Archaeal, Bacterial and Fungal Communities from the East River Watershed, Colorado collected in 2016-2017. (ess_dive, 2021)
This data set contains soil measurements made at the Pumphouse Hillslope to Floodplain transect at the locations of the early snowmelt-timing manipulation experiments in the East River Watershed in Colorado, USA. The data were collected in 2016 and 2017 to determine soil microbial responses to snow accumulation, snowmelt, and transition from winter to spring. Some additional data from the Washington Gulch snowmelt manipulation experiment lcoations are also included here. Data were collected on soil cores collected in the field at three soil depths (0 to 5 cm, 5 to 15 cm, 15 cm +) below the soil surface and analyzed in the on homogenized samples with roots and gravel removed. Data include gravimetric soil water content (48 hr oven-dried) and soil pH measurements (1:1 w/vol in ddH2O), dissolved nitrogen pools measured in soil extracts (2M KCl extractant), microbial biomass carbon and nitrogen (0.5M K2SO4 extractant), and archaeal, bacterial, and fungal species determined by Illumina 300 bp paired-read marker gene sequencing (16S rDNA for archaea and bacteria and ITS for fungi).

Supplemental Data for "Using Fission-Track Radiography Coupled with Scanning Electron Microscopy for Efficient Identification of Solid-Phase Uranium Mineralogy at a Former Uranium Pilot Mill (Grand Junction, Colorado)" (2021)
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3 m Resolution Canopy Cover Estimates for the Upper Gunnison Basin derived from 2015 and 2019 LiDAR Data - Ian K Breckheimer (s3, 2021)
This is a map of vegetation canopy cover or density for the Upper Gunnison River Basin based on 2015 and 2019 LiDAR data. Cover is measured as a proportion (0 representing no cover, and 1 representing complete cover). This measure of cover is the inverse of the canopy gap fraction. This dataset was generated from the normalized, elevation-corrected LiDAR point clouds, and was calculated as Density = N / T Where N in the number of LiDAR returns greater than 2 m above the ground surface, and T is the total number of returns. Calculation was implemented in the R package lidR. The ground-classified points were first used to generate a bare-earth surface, which was subtracted from the point cloud elevation to generate the normalized point cloud.  Topographic artifacts and structures have not been removed from this dataset.

Airborne electromagnetic, magnetic, and radiometric survey, upper East River and surrounding watersheds near Crested Butte, Colorado, 2017 - Burke J Minsley (other, 2021)
This data release consists of 1,984 line-kilometers of airborne electromagnetic (AEM), magnetic data and radiometric data collected from October to November 2017 in the upper East River and surrounding watersheds in central Colorado. The U.S. Geological Survey contracted Geotech Ltd. to acquire these data as part of regional investigations into the geologic structure and hydrologic framework of the area. The AEM data have been inverted to produce a series of regional cross-sections that constrain the electrical properties of the subsurface to a depth of ~500m. Data were acquired using the VTEM ET time-domain helicopter-borne electromagnetic system along flight lines that cross important geological structures over a 483 square kilometer [...]

Distinct Source Water Chemistry Shapes Contrasting Concentration Discharge Patterns, Water Resources Research: Dataset. - Wei Zhi (ess_dive, 2021)
This data package contains discharge and water quality data and model results at Coal Creek Watershed in the central Rocky Mountains of Colorado, USA. Files include high-frequency stream chemistry data collected during the period of Dec 2015 to Jun 2018, and model results of water storage and flux. The dataset also includes dissolved organic carbon and sodium stream chemistry data for the period of 2016. Our model then incorporates the USGS datasets of discharge and stream chemistry, for which data and citations are provided in the dataset files and related reference field. The resulting model BioRT-Flux-PIHM is the biogeochemical reactive transport model of the PIHM family code MM-PIHM for watershed processes and is detailed in the reference paper (doi.org/10.1029/2018WR024257) and in Github (https://github.com/PSUmodeling/BioRT-Flux-PIHM).

Mask for the Upper Gunnison SDP Domain at 3 m resolution - Ian K Breckheimer (s3, 2021)
This is a 3m resolution binary map representing areas within the Upper Gunnison Domain of the RMBL Spatial Data Platform.

East River Surface and Pore Water FTICR-MS Data Associated with “Implications of sample treatment on characterization of the riverine environmental metabolome” (ess_dive, 2021)
Surface and pore water samples were collected from distributed locations around Meander A in East River (Crested Butte, CO, USA) during the summer of 2018. This dataset consists of the characterization of dissolved organic matter using 12 Tesla Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS; in .xml format) analyzed through the Environmental Molecular Sciences Laboratory (EMSL; https://www.pnnl.gov/environmental-molecular-sciences-laboratory) using two different sample pre-treatment methods (solid phase extraction, no solid phase extraction) and two electrospray ionization methods (ESI-positive, ESI-negative) to identify the impacts of these choices on the final dataset. This study aimed to understand how the different sample processing methods influence the resulting FTICR-MS dataset. Any published work that utilizes data presented in this dataset should cite the dataset using the DOI number. If using the dataset, please acknowledge the U.S. Department of Energy (DOE) Office of Science (BER) Subsurface Biogeochemical Research (SBR) program, the Environmental Molecular Sciences Laboratory (EMSL), and Worldwide Hydrobiogeochemical Observation Network for Dynamic River Systems (WHONDRS). The publication DOI will be added to this abstract when available.

Sensor-based phenology from snowmelt experiment gradient, East River, Colorado, 2017 to 2020 (ess_dive, 2021)
The timing of snowmelt is a critical cue for the initiation of growth in mountain meadow ecosystems and can also impact the duration and magnitude of plant production. High frequency observations of species-level phenology are time consuming and require a high degree of expertise, and publicly available remote sensing products lack the necessary temporal resolution to assess fine-scale growing season dynamics. Near-surface sensing methods provide a middle ground with high temporal frequency and tractable spatial scales (from sub-meter to hillslope scale). This data package includes csv files of Normalized Difference Vegetation Index (NDVI) timeseries (SM_NDVI_dailymax.csv) and phenological thresholds (SM_NDVI_summary.csv) for sub-plots (1m2) and Green Chromatic Coordinate (GCC) phenological thresholds (SM_GCC_summary.csv) at the plot scale (10m x 14m). Location IDs associated with this data package are: ER-LM, WG-UM, WG-LS, ER-US, and XX-AL. Related data packages include: “Microclimate observations associated with snowmelt experiment gradient sites, East River, Colorado, 2017 to 2020” and “Colorado Elevation Gradient Snowmelt Manipulation Plant Phenology 2017-2018”.

Subcanopy Potential Solar Radiation on Day of Year 355 for the Upper East River Derived from 2018 NEON AOP Data - Ian K Breckheimer (s3, 2021)
This dataset represents potential clear-sky incident solar radiation (in w/m^2) for day of year 355 (winter solstice), taking into account shading from topography, buildings, and vegetation greater than 1m in height. This map was generated with the GRASS GIS program r.sun and a subcanopy solar radiation model from Bode et al. 2014: Bode, C. A., Limm, M. P., Power, M. E., & Finlay, J. C. (2014). Subcanopy Solar Radiation model: Predicting solar radiation across a heavily vegetated landscape using LiDAR and GIS solar radiation models. Remote Sensing of Environment, 154, 387-397. The model assumes deciduous vegetation is in it's leaf-off condition (as is typical on that date).

Shale drilling field notes, lithologic descriptions, and core photographs of wells PLM5, PLM8, GUM1, and GLS1 at the East River Watershed, Colorado. (ess_dive, 2021)
The purpose of this dataset is to maintain a record of the shale drilling field notes, lithologic descriptions, and core photographs taken at the PLM5 (Pumphouse Lower Montane Borehole #5), PLM8 (Pumphouse Lower Montane Borehole #8), GUM1 (Gothic Upper Montane Borehole #1), and GLS1 (GLS1 = Gothic Lower Subalpine Borehole #1) wells at the East River Watershed, Colorado during October 2018 through November 2019. The wells were created as part of data collection for the Lawrence Berkeley National Laboratory Watershed Function Scientific Focus Area (WF SFA). This dataset consists of (1) detailed field notes and metadata (well locations, elevations, completion depths, and pressure transducer deployments) associated with drilling and coring activities accompanying the 2018 and 2019 installations of wells PLM5, PLM8, GUM1, and GLS1 and (2) high resolution photographs (*.png format) of all shale core recovered during the installations. Core photographs are labeled with location- and depth-specific names (e.g. PLM5_134-144ft), with the prefix (e.g. PLM5) indicating the well location and the suffix (e.g. 134-144ft) indicating the depth below ground surface of the recovered core. With the exception of core collected from well PLM5 from depths 0-59 feet, which were photographed by Tetsu Tokunaga in Berkeley, CA, all core was photographed by Kenneth H. Williams at the US Geological Survey core repository in Denver, Colorado, where all core samples are permanently archived.

3 m Resolution Understory Cover for the Upper Gunnison Basin derived from 2015 and 2019 LiDAR Data - Ian K Breckheimer (s3, 2021)
This is a map of vegetation understory cover or density for the Upper Gunnison River Basin based on 2015 and 2019 LiDAR data. Cover is measured as a proportion (0 representing no cover, and 1 representing complete cover).  This dataset was generated from the normalized, elevation-corrected LiDAR point clouds, and was calculated as Density = N_2 / T_2 Where N_2 is the number of LiDAR returns between 0.25 and 2 m above the ground surface, and T is the total number of returns less than 2m above the surface. Calculation was implemented in the R package lidR. The ground-classified points were first used to generate a bare-earth surface, which was subtracted from the point cloud elevation to generate the normalized point cloud.  Topographic artifacts and structures have not been removed from this dataset.

Subcanopy Potential Solar Radiation on Day of Year 80 for the Upper East River Derived from 2018 NEON AOP Data - Ian K Breckheimer (s3, 2021)
This dataset represents potential clear-sky incident solar radiation (in w/m^2) for day of year 265 (fall equinox), taking into account shading from topography, buildings, and vegetation greater than 1m in height. This map was generated with the GRASS GIS program r.sun and a subcanopy solar radiation model from Bode et al. 2014: Bode, C. A., Limm, M. P., Power, M. E., & Finlay, J. C. (2014). Subcanopy Solar Radiation model: Predicting solar radiation across a heavily vegetated landscape using LiDAR and GIS solar radiation models. Remote Sensing of Environment, 154, 387-397. The model assumes deciduous vegetation is in it's leaf-on condition (as is typical on that date).

Partial pressure of carbon dioxide, sea surface salinity, temperature and barometric pressure collected from surface underway observations during the racing sailing vessel Seaexplorer (Malizia II) cruises in the Atlantic Ocean, Indian Ocean and Pacific Ocean from 2020-07-03 to 2021-01-05 (NCEI Accession 0235681) - NCEI (other, 2021)
This dataset includes surface underway data collected during the racing sailing vessel Seaexplorer (Malizia II) cruises in the Atlantic Ocean, Indian Ocean and Pacific Ocean from 2020-07-03 to 2021-01-05. These data include partial pressure of carbon dioxide in the water, sea surface salinity, sea surface temperature and barometric pressure. The instruments used to collect these data include carbon dioxide (CO2) gas analyzer, Flat membrane (PDMS) equilibrator for autonomous carbon dioxide (CO2) measurement.

Bare-earth Potential Solar Radiation on Day of Year 172 for the Upper East River Derived from 2018 NEON AOP Data - Ian K Breckheimer (s3, 2021)
This dataset represents potential clear-sky incident solar radiation (in w/m^2) for day of year 172 (summer solstice), taking into account shading from topography and man-made structures, but not vegetation. This map was generated with the GRASS GIS program r.sun.

Vegetation Structure Maps for the Upper East River Domain Derived from 2015 and 2019 LiDAR Data - Ian K Breckheimer (s3, 2021)
This is a map of various vegetation canopy structure metrics derived from high-density airborne LiDAR scans collected in August - September 2015 and 2019. The different raster bands represent statistical summaries of the normalized LiDAR point cloud. In the normalized point cloud, ground elevations have been subtracted, leaving the Z coordinate to represent heights above the ground surface. T he 14 raster bands represent: 1. "maxht", the maximum height above ground (in m) of points in a raster cell. 2. "meanht",the mean height above ground (in m) of points in a raster cell. 3. "ht99", 99th-percentile height above ground (in m) of points in a raster cell. 4. "ht80", 80th-percentile height above ground (in m) of points in a raster cell. 5. "ht20", 20th-percentile height above ground (in m) of points in a raster cell. 6. "htsd", standard deviation of point heights. 7. "intmean", mean of return intensities. 8. "intmax", maximum of return intensities. 9. "intsd", standard deviation of return intensities. 10. "intcan_ratio", ratio of summed return intensities from the canopy (> 2m height) to total summed intensities. 11. "intund_ratio", ratio of summed return intensities from the understory (0.25 - 2 m height) to total summed intensities below 2m height. 12. "prop_can", ratio of return numbers from the canopy (> 2m height) to total number of returns. 13. "prop_und", ratio of return numbers from the understory (0.25 - 2 m height) to the total number of returns below 2m height. 14. "p_crown", ratio of the number of returns inside vegetation crowns to the total number of returns. Processing summary: Classified LiDAR point clouds from both datasets were re-projected to a common coordinate system (EPSG:32613, WGS84 UTM Zone 13N). A 0.33m canopy height model was constructed for each dataset by triangulating ground returns and subtracting the elevation of the ground surface. Statistical summaries described above were then calculated from the normalized point cloud. All point cloud processing was done using the R package lidR version 2.1. The two summary datasets from the 2015 and 2019 LiDAR datasets were mosaiced to produce a continous dataset, with the 2019 data taking priority where there was coverage (approximately 80% of the domain). Note that this causes visible inconsistencies in return intensity data between the two domains because of the different characteristics of the LiDAR instruments used.

National Assessment of Oil and Gas Project - Uinta-Piceance Province (020) Boundary - U.S. Geological Survey - CERSC Data Management Services Project (other, 2021)
The USGS Central Region Energy Team assesses oil and gas resources of the United States. The onshore and State water areas of the United States comprise 71 provinces. Within these provinces, Total Petroleum Systems are defined and Assessment Units are defined and assessed. Each of these provinces is defined geologically, and most province boundaries are defined by major geologic changes. The Uinta-Piceance Province is located in eastern Utah and western Colorado, encompassing all or parts of Delta, Garfield, Gunnison, Mesa, Moffat, Montrose, Ouray, Rio Blanco, and Routt Counties in Colorado and all or parts of Carbon, Duchesne, Emery, Grand, Sanpete, Sevier, Uintah, Utah, and Wasatch Counties in Utah. The main population centers within [...]

Microclimate observations associated with snowmelt experiment gradient sites, East River, Colorado, 2017 to 2020 (ess_dive, 2021)
The timing of snowmelt in mountain systems is a main driver of vegetation phenology and production, as well as recharge of soil moisture and ground water. Decreases in maximum snowpack and warmer spring temperatures have led to a higher frequency of early snowmelt. This study combines a natural elevation gradient with an experimental manipulation of snowmelt timing to assess the effect of earlier melt on hillslope and watershed ecohydrological processes. This data package includes csv files with plot and sub-plot level observations of soil temperature (SM_ST.csv), soil moisture (SM_SWC.csv), air temperature (SM_AirT.csv), and relative humidity (SM_rH.csv). The date range of this dataset includes a pre-treatment year (2017), two treatment years (2018 and 2019), and a post-treatment year (2020). Location IDs associated with this data package are: ER-LM, WG-UM, WG-LS, ER-US, and XX-AL. Related data packages include: “Colorado Elevation Gradient Snowmelt Manipulation Plant Phenology 2017-2018” and “Sensor-based phenology from snowmelt experiment gradient, East River, Colorado, 2017 to 2020”

Quality Assurance and Quality Control (QA/QC) of Meteorological Time Series Data for Billy Barr, East River, Colorado USA - Gilberto Pastorello; Deb Agarwal; Charuleka Varadharajan; Boris Faybishenko; Roelof Versteeg; Dipankar Dwivedi (ess_dive, 2021)
A comprehensive Quality Assurance (QA) and Quality Control (QC) statistical framework consists of three major phases: Phase 1—Preliminary raw data sets exploration, including time formatting and combining datasets of different lengths and different time intervals; Phase 2—QA of the datasets, including detecting and flagging of duplicates, outliers, and extreme values; and Phase 3—the development of time series of a desired frequency, imputation of missing values, visualization and a final statistical summary. The time series data collected at the Billy Barr meteorological station (East River Watershed, Colorado) were analyzed. The developed statistical framework is suitable for both real-time and post-data-collection QA/QC analysis of meteorological datasets.The files that are in this data package include one excel file, converted to CSV format (Billy_Barr_raw_qaqc.csv) that contains the raw meteorological data, i.e., input data used for the QA/QC analysis. The second CSV file (Billy_Barr_1hr.csv) is the QA/QC and flagged meteorological data, i.e., output data from the QA/QC analysis. The last file (QAQC_Billy_Barr_2021-03-22.R) is a script written in R that implements the QA/QC and flagging process. The purpose of the CSV data files included in this package is to provide input and output files implemented in the R script.

Subcanopy Potential Solar Radiation on Day of Year 172 for the Upper East River Derived from 2018 NEON AOP Data - Ian K Breckheimer (s3, 2021)
This dataset represents potential clear-sky incident solar radiation (in w/m^2) for day of year 172 (summer solstice), taking into account shading from topography, buildings, and vegetation greater than 1m in height. This map was generated with the GRASS GIS program r.sun and a subcanopy solar radiation model from Bode et al. 2014: Bode, C. A., Limm, M. P., Power, M. E., & Finlay, J. C. (2014). Subcanopy Solar Radiation model: Predicting solar radiation across a heavily vegetated landscape using LiDAR and GIS solar radiation models. Remote Sensing of Environment, 154, 387-397. The model assumes deciduous vegetation is in it's leaf-off condition (as is typical on that date).

Drone ortho basemap of the Gothic Townsite, November 15th, 2019 - Ian K Breckheimer (s3, 2021)
<qgis stylecategories="AllStyleCategories" maxscale="0" minscale="1e+08" hasscalebasedvisibilityflag="0" version="3.18.1-Zürich">This is a visible (RGB) orthomosaic derived from UAV imagery via Structure from Motion processing. UAV flights were performed in Sunny conditions on November 15th, 2019, collecting RGB images using the built-in camera on a DJI Mavic 2 Pro. The raw imagery had an approximately 3cm ground sample distance (GSD). Images were processed in Agisoft Metashape Software (version 1.6) to derive a georeferenced dense point cloud and 3D model. Images were orthorectified and combined into a mosaic using the 3D model. This dataset has been georeferenced using 14 ground-control points, but has not been radiometrically calibrated.<blendmode></blendmode></qgis>

Predicting sedimentary bedrock subsurface weathering fronts and weathering rates: Dataset. (ess_dive, 2021)
Although bedrock weathering strongly influences water quality and global carbon and nitrogen budgets, the weathering depths and rates within subsurface are not well understood nor predictable. Determination of both porewater chemistry and subsurface water flow are needed in order to develop more complete understanding and obtain weathering rates. In a long-term field study, we applied a multiphase approach along a mountainous watershed hillslope transect underlain by marine shale. Here we report three findings. First, the deepest extent of the water table determines the weathering front, and the range of annually water table oscillations determines the thickness of the weathering zone. Below the lowest water table, permanently water-saturated bedrock remains reducing, preventing deeper pyrite oxidation. Secondly, carbonate minerals and potentially rock organic matter share the same weathering front depth with pyrite, contrary to models where weathering fronts are stratified. Thirdly, the measurements-based weathering rates from subsurface shale are high, amounting to base cation exports of about 70 kmolc ha−1 y−1, yet consistent with weathering of marine shale. Finally, by integrating geochemical and hydrological data we present a new conceptual model that can be applied in other settings to predict weathering and water quality responses to climate change.

National Assessment of Oil and Gas Project - Denver Basin Province (039) Boundary - U.S. Geological Survey - CERSC Data Management Services Project (other, 2021)
The USGS Central Region Energy Team assesses oil and gas resources of the United States. The onshore and State water areas of the United States comprise 71 provinces. Within these provinces, Total Petroleum Systems are defined and Assessment Units are defined and assessed. Each of these provinces is defined geologically, and most province boundaries are defined by major geologic changes. The Denver Basin Province is located in eastern Colorado, western Nebraska, southern South Dakota, and eastern Wyoming encompassing all or parts of Pueblo, El Paso, Crowley, Lincoln, Kit Carson, Elbert, Teller, Douglas, Jefferson, Denver, Arapahoe, Adams, Washington, Yuma, Morgan, Weld, Broomfield, Boulder, Larimer, Logan, Sedwick, Freemont, and Phillips [...]

Minimally processed AEM, magnetic and radiometric data - Burke J Minsley (other, 2021)
This data release consists of 1,984 line-kilometers of airborne electromagnetic (AEM), magnetic data and radiometric data collected from October to November 2017 in the upper East River and surrounding watersheds in central Colorado. The U.S. Geological Survey contracted Geotech Ltd. to acquire these data as part of regional investigations into the geologic structure and hydrologic framework of the area. The AEM data have been inverted to produce a series of regional cross-sections that constrain the electrical properties of the subsurface to a depth of ~500m. Data were acquired using the VTEM ET time-domain helicopter-borne electromagnetic system along flight lines that cross important geological structures over a 483 square kilometer [...]

Total Dissolved Nitrogen and Ammonia Data for the East River Watershed, Colorado (2015-2022) (ess_dive, 2021)
This data package contains mean values for total dissolved nitrogen (TDN) and ammonia concentrations for water samples taken from the East River Watershed in Colorado. The East River is part of the Watershed Function Scientific Focus Area (WFSFA) located in the Upper Colorado River Basin, United States. TDN was analyzed using a Shimadzu Total Nitrogen Module (TNM-1) combined with the TOC-VCSH analyzer (Shimadzu Corporation, Japan). TNM-1 is a non-specific measurement of total nitrogen (TN). All nitrogen species in samples are combusted to nitrogen monoxide and nitrogen dioxide, then reacted with ozone to form an excited state of nitrogen dioxide. Upon returning to ground state, light energy is emitted. Then, TDN is measured using a chemiluminescence detector. Ammonia was determined using a Lachat's QuikChem 8500 Series 2 Flow Injection Analysis System (LACHAT Instruments, QuckChem 8500 series 2, Automated Ion Analyzer, Loveland, Colorado). When ammonia in water samples is heated (60 degrees C) with salicylate and hypochlorite in an alkaline phosphate buffer, an emerald green color is produced which is proportional to the ammonia concentration. The color is intensified by the addition of nitroprusside. Ethylenediaminetetraacetic acid (EDTA) is added to the buffer to prevent the interference of metal ions (Ca, Mg, and Fe etc.). Ammonia-N is then determined by LACHAT flow injection and a colorimetric assay at an absorbance wavelength 660 nm. (Reference: LACHAT Instruments: QuickChem Method 90-107-06-3-A, Determination of Ammonia by Flow Injection Analysis (High Throughput, Salicylate Method/DCIC) (Multi Matrix method). Written by Lynn Egan (Application group), February 08, 2011.) All files are labeled by location and variable, and data reported are the mean values upon replicate measurements. All samples were analyzed under a rigorous quality assurance and quality control (QA/QC) process as detailed in the methods. This data package contains (1) a zip file (tdn_ammonia_data_2015-2022.zip) containing a total of 224 data files of ammonia and TDN data from across the Lawrence Berkeley National Laboratory (LBNL) Watershed Function Scientific Focus Area (SFA) which is reported in .csv files per location; (2) a file-level metadata (flmd.csv) file that lists each file contained in the dataset with associated metadata; and (3) a data dictionary (dd.csv) file that contains terms/column_headers used throughout the files along with a definition, units, and data type. Update 10/07/2020: Updated the data files to remove times from the timestamps, so that only dates remain. The data values have not changed. Update 4/11/2021: Added Determination of Method Detection Limits (MDLs) for DIC, NPOC and TDN Analyses and Determination of Method Detection Limit for Ammonia and the Interferences by LACHAT Flow Injection Analysis documents, which can be accessed as PDFs or with Microsoft Word.Update on 6/10/2022: versioned updates to this dataset was made along with these changes: (1) updated total dissolved nitrogen and ammonia data for all locations up to 2021-12-31, (2) removal of units from column headers in datafiles, (3) added row underneath headers to contain units of variables, (4) restructure of units to comply with CSV reporting format requirements, (5) added -9999 for empty numerical cells, and (6) the addition of the file-level metadata (flmd.csv) and data dictionary (dd.csv) were added to comply with the File-Level Metadata Reporting Format. Update on 2022-09-09: Updates were made to reporting format specific files (file-level metadata and data dictionary) to correct swapped file names, add additional details on metadata descriptions on both files, add a header_row column to enable parsing, and add version number and date to file names (v2_20220909_flmd.csv and v2_20220909_dd.csv). Update on 2022-12-20: Updates were made to both the data files and reporting format specific files. Units were listed incorrectly, but have been fixed to reflect correct units (ug/L). File level metadata (flmd) and data dictionary (dd) files were updated to reflect the updated versions of these files. Available data was added up until 2022-06-01.

SnowEx20 Grand Mesa Autumn 2019 Gravimetric Soil Moisture, Version 1 (other, 2021)

SnowEx20 Grand Mesa In Situ Dielectric Soil Moisture, Version 1 (other, 2021)

Inverted resistivity and IP models - Burke J Minsley (other, 2021)
This data release consists of 1,984 line-kilometers of airborne electromagnetic (AEM), magnetic data and radiometric data collected from October to November 2017 in the upper East River and surrounding watersheds in central Colorado. The U.S. Geological Survey contracted Geotech Ltd. to acquire these data as part of regional investigations into the geologic structure and hydrologic framework of the area. The AEM data have been inverted to produce a series of regional cross-sections that constrain the electrical properties of the subsurface to a depth of ~500m. Data were acquired using the VTEM ET time-domain helicopter-borne electromagnetic system along flight lines that cross important geological structures over a 483 square kilometer [...]

Processed AEM data - Burke J Minsley (other, 2021)
This data release consists of 1,984 line-kilometers of airborne electromagnetic (AEM), magnetic data and radiometric data collected from October to November 2017 in the upper East River and surrounding watersheds in central Colorado. The U.S. Geological Survey contracted Geotech Ltd. to acquire these data as part of regional investigations into the geologic structure and hydrologic framework of the area. The AEM data have been inverted to produce a series of regional cross-sections that constrain the electrical properties of the subsurface to a depth of ~500m. Data were acquired using the VTEM ET time-domain helicopter-borne electromagnetic system along flight lines that cross important geological structures over a 483 square kilometer [...]

Copper Creek Baseflow Age Experiment using Environmental Gas Tracers in the East River Watershed, CO. (ess_dive, 2021)
Groundwater contributions to streams, or baseflow, represents a mix of numerous flow paths through the subsurface of varying ages that are important to understanding system hydrologic lag and solute export. To better constrain numerical estimates of baseflow age, we used a novel experiment from Sanford et al. (2015) based on stream water concentrations of environmental gases (SF6, N2 and Ar) and an assumed Weibull distribution for a Colorado (CO) River headwater basin, Copper Creek (24 km2). The data package contains steam data collected over a 12-hour period on August 27, 2017 and the finite difference approximation for the mass balance approach.

Drone ortho basemap of the Gothic Townsite, August 27th 2019 - Ian K Breckheimer (s3, 2021)
This is a visible (RGB) orthomosaic derived from UAV imagery via Structure from Motion processing. UAV flights were performed in Sunny conditions on August 27th, 2019, collecting RGB images using the built-in camera on a DJI Mavic 2 Pro. The raw imagery had an approximately 3cm ground sample distance (GSD). Images were processed in Agisoft Metashape Software (version 1.6) to derive a georeferenced dense point cloud and 3D model. Images were orthorectified and combined into a mosaic using the 3D model. This dataset has been georeferenced using 14 ground-control points, but has not been radiometrically calibrated.

Annual floodplain sediment deposition recorded using feldspar clay marker horizons along the East River, Colorado, 2015-2017. (ess_dive, 2021)
White feldspar clay was placed along 24 transects defining a ~9-km long study reach along the meandering snowmelt-dominated East River in Colorado, USA. Feldspar markers horizons were placed in the fall of 2015 and 2016 along transects with the space between them increasing with distance from the channel. Depths of floodplain deposition were measured the following summers of 2016 and 2017 following annual peak flow after peak snowmelt. This dataset includes individual and average measurements made in the field along with coordinates in NAD 83 UTM Zone 13.

Bare Earth Potential Solar Radiation on Day of Year 80 for the Upper East River Derived from 2018 NEON AOP Data - Ian K Breckheimer (s3, 2021)
This dataset represents potential clear-sky incident solar radiation (in w/m^2) for day of year 80 (spring equinox), taking into account shading from topography and buildings, but not vegetation. This map was generated with the GRASS GIS program r.sun.

East River Watershed Stable Water Isotope Data in Precipitation, Snowpack and Snowmelt 2016-2020 (ess_dive, 2021)
Stable water isotopes (d18O, d2H and d-excess) are important tracers in hydrologic research to understand water partitioning between vegetation, groundwater, and runoff but are rarely applied to large watersheds with persistent snowpack and complex topopgraphy. Data were collected for the Lawrence Berkeley National Laboratory Watershed Function Science Focus Area supported by the U.S Department of Energy in the East River, CO Hydrologic Unit Code (140200010) with limited data also collected in adjacent watersheds Ohio Creek and Taylor River. Data are provided in csv and includes isotopic information for precipitation (years 2014-2016), snowmelt (years 2016-2017) and snowpits (years 2016-2020). Snowpit data contain depth resolved information at 10 cm intervals for density, snow water equivalent (SWE) and stable water isotopes. Bulk isotopic data for 86 snowpits contain depth, SWE, density and SWE-weighted isotope values. Sampling locations and elevations are provided within the data files, while kmz files are provided to view sampling locations using Google Earth software.

Bare Earth Potential Solar Radiation on Day of Year 355 for the Upper East River Derived from 2018 NEON AOP Data - Ian K Breckheimer (s3, 2021)
This dataset represents potential clear-sky incident solar radiation (in w/m^2) for day of year 355 (winter solstice), taking into account shading from topography and buildings, but not vegetation. This map was generated with the GRASS GIS program r.sun.

Appendix C. Relationships between temperature and arrival of Broad-tailed Hummingbirds and flowering onset in its early-season nectar resources at the Rocky Mountain Biological Laboratory in Colorado, USA. - C. David Bertelsen; Amy M. McKinney; David William Inouye; Billy Barr; Paul J. CaraDonna; Nickolas M. Waser (other, 2021)
Phenological advancements driven by climate change are especially pronounced at higher latitudes, so that migrants from lower latitudes may increasingly arrive at breeding grounds after the appearance of seasonal resources. To explore this possibility, we compared dates of first arrival of Broad-tailed Hummingbirds (Selasphorus platycercus) to dates of flowering of plants they visit for nectar. Near the southern limit of the breeding range, neither hummingbird arrival nor first flowering dates have changed significantly over the past few decades. At a nearby migration stopover site, first flowering of a major food plant has advanced, but peak flowering has not. Near the northern limit of the breeding range, first and peak flowering of early-season food plants have shifted to earlier dates, resulting in a shorter interval between appearance of first hummingbirds and first flowers. If phenological shifts continue at current rates, hummingbirds will eventually arrive at northern breeding grounds after flowering begins, which could reduce their nesting success. These results support the prediction that migratory species may experience the greatest phenological mismatches at the poleward limits of their migration. A novel hypothesis based on these results posits that the poleward limit for some species may contract toward lower latitudes under continued warming.

Rainbow trout diet and invertebrate drift data from 2012-2015 for the Colorado River, Grand Canyon, Arizona (other, 2021)
These data were compiled to explore the foraging ecology of Rainbow Trout (Oncorhynchus mykiss) in the Colorado River, Grand Canyon, Arizona. These data represent samples characterizing the availability of drifting invertebrate prey (hereafter, drift) and use of these invertebrate prey by rainbow trout determined by gut samples (hereafter, diets). Drift and diet sampling occurred in five distinct reaches downstream of Glen Canyon Dam (river kilometer (rkm) from the dam): (I) rkm 16.3-21.7; (II) rkm 52.8-58.3; (III) rkm 86.6-91.9; (IV) rkm 122.0-123.6; and (V) rkm 127.1-129.6. Samples were taken on 12 trips in April, July, September and January from April 2012 through January 2015. The aquatic prey base consists of 5 primary taxa; two [...]

Drone ortho basemap of the Gothic Townsite, June 17th, 2019 - Ian K Breckheimer (s3, 2021)
This is a visible (RGB) orthomosaic derived from UAV imagery via Structure from Motion processing. UAV flights were performed in sunny conditions on June 17th 2019, collecting RGB images using the built-in camera on a DJI Mavic 2 Pro. The raw imagery had an approximately 3cm ground sample distance (GSD). Images were processed in Agisoft Metashape Software (version 1.6) to derive a georeferenced dense point cloud and 3D model. Images were orthorectified and combined into a mosaic using the 3D model. This dataset has been georeferenced using 14 ground-control points, but has not been radiometrically calibrated.

Lek Disturbance Buffer Analysis data, Western Colorado, Derived from Gunnison Sage Grouse Location Data 2010 - 2014 (other, 2021)
This data release consists of three files (Crawford_and_WGB_Location_Data_S1.csv, Lek_Dist_S2.csv, and Home_Range_Area_S3.csv). The first data set represents specifics about each GPS location representing temporal and spatial relationships used in our analysis including the Month, day and year and local time each location was collected along with distance between locations, elevation in meters, distance to nearest lek and corresponding Buffer designation. The second data set represents the distance for each of the Leks, by population, used in our analysis to the nearest active lek. Distance measure in meters. The third data set provides area in hectares for minimum convex polygon (MCP) seasonal home ranges by population. The "All" category represents the MCP for the entire GPS location data set for each population.

Diversity and abundance of phyllosphere bacteria are linked to insect herbivory - Parris T Humphrey; Martha M Villalobos; Trang T Nguyen; Noah K Whiteman (other, 2021)
Simultaneous or sequential attack by herbivores and microbes is common in plants. Many seed plants exhibit a defence trade-off against chewing herbivorous insects and leaf-colonizing (‘phyllosphere’) bacteria, which arises from cross-talk between the phytohormones jasmonic acid (JA, induced by many herbivores) and salicylic acid (SA, induced by many bacteria). This cross-talk may promote reciprocal susceptibility in plants between phyllosphere bacteria and insect herbivores. In a population of native bittercress (Cardamine cordifolia, Brassicaceae), we tested whether simulating prior damage with JA or SA treatment induced resistance or susceptibility (respectively) to chewing herbivores. In parallel, we conducted culture-dependent surveys of phyllosphere bacteria to test the hypothesis that damage by chewing herbivores correlates positively with bacterial abundance in leaves. Finally, we tested whether bacterial infection induced susceptibility to herbivory by a major chewing herbivore of bittercress, Scaptomyza nigrita (Drosophilidae). Overall, our results suggest that reciprocal susceptibility to herbivory and microbial attack occurs in bittercress. We found that JA treatment reduced and SA treatment increased S. nigrita herbivory in bittercress in the field. Bacterial abundance was higher in herbivore-damaged vs. undamaged leaves (especially Pseudomonas syringae). However, Pedobacter spp. and Pseudomonas fluorescens infections were negatively associated with herbivory. Experimental Pseudomonas spp. infections increased S. nigrita herbivory in bittercress. Thus, plant defence signalling trade-offs can have important ecological consequences in nature that may be reflected in a positive correlation between herbivory and phyllosphere bacterial abundance and diversity. Importantly, the strength and direction of this association varies within and among prevalent bacterial groups.

East River Surface and Pore Water FTICR-MS Data Associated with “Implications of sample treatment on characterization of the riverine environmental metabolome” (ess_dive, 2021)
Surface and pore water samples were collected from distributed locations around Meander A in East River (Crested Butte, CO, USA) during the summer of 2018. This dataset consists of the characterization of dissolved organic matter using 12 Tesla Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS; in .xml format) analyzed through the Environmental Molecular Sciences Laboratory (EMSL; https://www.pnnl.gov/environmental-molecular-sciences-laboratory) using two different sample pre-treatment methods (solid phase extraction, no solid phase extraction) and two electrospray ionization methods (ESI-positive, ESI-negative) to identify the impacts of these choices on the final dataset. This study aimed to understand how the different sample processing methods influence the resulting FTICR-MS dataset. Any published work that utilizes data presented in this dataset should cite the dataset using the DOI number. If using the dataset, please acknowledge the U.S. Department of Energy (DOE) Office of Science (BER) Subsurface Biogeochemical Research (SBR) program, the Environmental Molecular Sciences Laboratory (EMSL), and Worldwide Hydrobiogeochemical Observation Network for Dynamic River Systems (WHONDRS). The publication DOI will be added to this abstract when available.

An examination of synchrony between insect emergence and flowering in Rocky Mountain meadows. - James D. Thomson; Jessica R. K. Forrest (other, 2021)
One possible effect of climate change is the generation of a mismatch in the seasonal timing of interacting organisms, owing to species-specific shifts in phenology. Despite concerns that plants and pollinators might be at risk of such decoupling, there have been few attempts to test this hypothesis using detailed phenological data on insect emergence and flowering at the same localities. In particular, there are few data sets on pollinator flight seasons that are independent of flowering phenology, because pollinators are typically collected at flowers. To address this problem, we established standardized nesting habitat (trap nests) for solitary bees and wasps at sites along an elevational gradient in the Rocky Mountains, and monitored emergence during three growing seasons. We also recorded air temperatures and flowering phenology at each site. Using a reciprocal transplant experiment with nesting bees, we confirmed that local environmental conditions are the primary determinants of emergence phenology. We were then able to develop phenology models to describe timing of pollinator emergence or flowering, across all sites and years, as a function of accumulated degree-days. Although phenology of both plants and insects is well described by thermal models, the best models for insects suggest generally higher threshold temperatures for development or diapause termination than those required for plants. In addition, degree-day requirements for most species, both plants and insects, were lower in locations with longer winters, indicating either a chilling or vernalization requirement that is more completely fulfilled at colder sites, or a critical photoperiod before which degree-day accumulation does not contribute to development. Overall, these results suggest that phenology of plants and trap-nesting bees and wasps is regulated in similar ways by temperature, but that plants are more likely than insects to advance phenology in response to springtime warming. We discuss the implications of these results for plants and pollinators, and suggest that phenological decoupling alone is unlikely to threaten population persistence for most species in our study area.

Multi-year census of arthropod abundance on the plant Ligusticum porteri near Crested Butte, CO - M. L. Mullins; James H Den Uyl; Emily H Mooney (other, 2021)
The purpose of this study was to track year-to-year variation in aphid abundance on the host plant Ligusticum porteri (Apiaceae). We censused arthropod abundance on the flowering stalks of L. porteri weekly in June-August from 2017 to 2020. The censuses took place in ten L. porteri populations near Crested Butte, CO. The sites were by Brush Creek, Lake Irwin, and Washington Gulch. While the same populations were used across years, we randomly selected ten flowering plants in each population in each year (N = 100 plants per year). Observations focused on colonization by the aphid Aphis asclepiadis, its mutualist ants, and natural enemies. When found, we counted other arthropods as well, identifying them to Family or Order in the field. We also counted the number of host plant flowering stalks and inflorescences (umbel). We tracked flowering phenology using a numerical score (0-8). To track senescence, we used a qualitative score (TB=turning brown and AB=all brown) for terminal and primary umbels.

Geochemical analyses of surface water, groundwater and springs surrounding Mount Emmons near Crested Butte, Colorado (ver. 2.0, September 2020) - Michaela Johnson (other, 2021)
The U.S. Geological Survey (USGS), Colorado Division of Reclamation, Mining and Safety (DRMS), and Coal Creek Watershed Coalition (CCWC) working independently, have intermittently collected samples of surface- and groundwater and springs around Mount Emmons, near Crested Butte, Colorado. This data release is a compilation of the comprehensive inorganic chemical analyses conducted as a result of that sampling. The earliest samples were collected in the summer of 1997, and subsequent sampling has continued through 2019. Water samples collected in the Elk Creek basin, sample identifiers starting with EC, have been previously published in three U.S. Geological Survey reports; Verplanck and others, 2007, Manning and others, 2008, and Verplanck and others, 2010. These reports contain figures showing locations of samples including samples from underground in the Standard Mine. The geochemical analyses for this compilation were conducted by several analytical laboratories, so potential users of the data should be aware of uncertainties introduced by direct comparison of data from more than one lab. Nevertheless, these data serve as a record of potential changes and trends in water chemistry over a 20-plus year period that may be useful for evaluation of long-term environmental changes. Mount Emmons is interesting because it is host to a number of mineral deposits of various types, including polymetallic vein systems (primarily Pb-Zn deposits) and porphyry Mo deposit(s). If these deposits are exposed to the oxygenated weathering environment, they may produce acidic waters that are rich in heavy metals such as Zn, Cd, Pb, and other elements. The alteration halos surrounding the mineralized areas also can be weathered to mobilize heavy metals in the environment. Acidic, metal-rich waters typical of these environments are found around Mount Emmons, some of which are natural and some of which are of anthropogenic origin.

Hydrologic and geophysical data from high-elevation boreholes in Redwell Basin near Crested Butte, Colorado - Lyndsay B Ball (other, 2021)
Four boreholes (MW1, MW1UZ, MW2, MW2.1) were drilled in the fall of 2017 and summer of 2018 in upper Redwell Basin, a headwater catchment underlain by hydrothermally altered sedimentary rock in the Elk Mountains near the town of Crested Butte, Colorado. The boreholes were continuously cored using a wireline HQ-sized coring system and sample a combination of Quaternary-aged surficial colluvium and the Cretaceous-aged Mesaverde Formation. In-situ injection-based hydraulic tests were performed in MW1 and MW2 during drilling while advancing using a single-packer apparatus in tandem with an in-line flow meter and interval pressure monitoring. Borehole geophysical logging was performed in MW1, MW1UZ, and MW2.1 in the open holes. The boreholes were completed as vertically discrete nested monitoring wells. Pressure transducers have been deployed in selected wells to monitor groundwater level and fluid temperature over time. This data release includes borehole location and well completion information as well as related hydrologic and geophysical data. The borehole geophysical data directory contains borehole geophysical logs. The hydraulic test data directory contains in-situ packer test data and laboratory permeability/porosity results from selected core samples. The hydrologic monitoring data directory contains groundwater level and temperature data for selected wells.

Hydrogeochemical data for the characterization of stream, groundwater, and beaver-induced floodplain exchange in the East River Science Focus Area, Crested Butte, CO - Martin Briggs (other, 2021)
The U.S. Geological Survey, along with scientists from Rutgers University, collected water chemistry, electromagnetic, redox-potential, dissolved oxygen, water flow rate, and water temperature data along stream and river corridors in multiple sub-watersheds of the East River Science Focus Area (SFA) near Crested Butte, CO. The concept of ‘river corridor’ science recognizes that the quality of flowing surface waters is intrinsically linked to their contributing catchments through hydrologic connectivity, including lower terrestrial hillslopes, floodplains, and riparian zones. Bidirectional river-floodplain exchange in particular can be critical to basin water storage and nutrient transformation dynamics, yet floodplain hydrologic exchange flows are often driven primarily by episodic high-flow events or relatively slow-exchanging, long hyporheic flowpaths. Beaver (Castor canadensis) disrupt these abiotic floodplain exchange drivers by actively diverting large quantities of channel water laterally using an engineered series of dams, impacting both wet and dry season floodplain connection. As beaver ponds and seepage zones accompanying beaver activity often exhibit suboxic to hypoxic conditions, there is the potential to mobilize reduced metals from alluvial sediments to streams and rivers. The data contained in this release can be used to assess beaver-induced physical and chemical river-floodplain exchange.

SnowEx20 Grand Mesa IOP BSU 1 GHz Multi-polarization GPR CMP Snow Water Equivalent, Version 1 (other, 2021)

A composite high resolution canopy height map for the Upper East River domain - Ian K Breckheimer (s3, 2021)
This dataset represents a 1/3 m resolution vegetation canopy height model for the upper East River Watershed in Western Colorado. Source datasets include August 2015 and August 2019 discrete-return LiDAR point clouds collected by Quantum Geospatial for terrain mapping purposes on behalf of the Colorado Hazard Mapping Program and the Colorado Water Conservation Board. Both datasets adhere to the USGS QL2 quality standard. The point cloud data were processed using the R package lidR to generate a canopy height model representing maximum vegetation height above the ground surface, using a pit-free algorithm. The file "UER_canopy_ht_33cm_v2.tif" contains gridded canopy height data, with canopy height measured in meters. This dataset is distinct from, but covers overlapping geographic areas as, LiDAR datasets collected as part of the 2018 NEON Aerial Observation Platform campaign in the Upper East River (Goulden T ; Hass B ; Brodie E ; Chadwick K D ; Falco N ; Maher K ; Wainwright H ; Williams K (2020): NEON AOP Survey of Upper East River CO Watersheds: LAZ Files, LiDAR Surface Elevation, Terrain Elevation, and Canopy Height Rasters. Watershed Function SFA. doi:10.15485/1617203), and the 2015 LiDAR scan contracted by the Department of Energy for the East River and Washington Gulch (Wainwright H ; Williams K (2017): LiDAR collection in August 2015 over the East River Watershed, Colorado, USA. Watershed Function SFA. doi:10.21952/WTR/1412542). The current dataset has a higher point density (9.4 points / square meter) than the 2018 NEON AOP data, and covers a larger geographic area than the 2015 DOE data. The original point cloud data, processing scripts, and other supporting documents can be found in the ESS-DIVE repository (following the DOI link).

Digital Data from Mineral Investigation of Sangre de Cristo Wilderness Study Area, Alamosa, Custer, Fremont, Huerfano, and Saguache Counties, Colorado, USA (other, 2021)
This Data Release provides tabular and geospatial data digitized by the U.S. Geological Survey (USGS) from a U.S. Bureau of Mines (USBoM) report titled Mineral Investigation of Sangre de Cristo Wilderness Study Area, Alamosa, Custer, Fremont, Huerfano, and Saguache Counties, Colorado. The original preliminary paper report, numbered Mineral Land Assessment 65-83 (MLA 65-83; Ellis and others, 1983), presented the results of a mineral resource potential survey of areas in and around the Sangre de Cristo Range flanking the northeastern extent of San Luis Valley in south-central Colorado. Included in this Data Release are georeferenced scans of the regional plate maps, digitized sample site locations, analytical chemistry, and structural [...]

SnowEx20 Grand Mesa IOP BSU 1 GHz Multi-polarization GPR CMP Snow Water Equivalent, Version 1 (other, 2021)

Unsaturated and Saturated Hydraulic Parameters of Soils at the East River Watershed, Colorado Calculated using the Pedotransfer Function Method (ess_dive, 2021)
The purpose of the data package is to present the results of calculations of the following unsaturated-saturated hydraulic parameters of soils of the East River Watershed, Colorado: fully saturated water content (Qs), residual saturation (Qr), van genuchten parameters alpha and n, field capacity (FC), and saturated hydraulic conductivity (Ks). Calculations were conducted for the following soil texture types: sandy_loam, loam, silty_clay_loam, clay_loam, silt loam; the particle size distribution included the percentage of sand, silt, clay, and the bulk density (BD) of soils. Calculations were conducted for the following areas - Lower_Subalpine (6 samples), - Lower_Montane_lower_hillslope (7 samples), - Floodplain_at_base_of_lower_montane_hillslope, (11 samples), - PLM-0 (10 samples), - PLM-1 (10 samples), and - PLM-3 (13 samples) Calculations were conducted using the Pedotransfer Function Method developed by Tóth et al. (2014) with the application of the code ”euptf” in Rstudio. The data are being summarized in the Excel file ”Unsaturated_Saturated_Hydraulic_Parameters_PTF_calculated_EASt_EIver.xls" including two worksheets: “full_data_EAST_RIVER” which includes (a) the input data used for calculations, the soil texture triangle, and the plots of the water retention curves and unsaturated hydraulic conductivity for several types of soil texture, and (b) the summary table with the averaged parameters for each area. The the texture triangle was plotted using the Rstudio "soiltexture." Microsoft Excel software is required to open the Excel file. The metadata and a list of references to the Rstudio libraries used for calculations and data visualization are giving in the Word Readme file.

Data release for Surficial Geology of the Northern San Luis Valley, Saguache, Fremont, Custer, Alamosa, Rio Grande, Conejos, and Costilla Counties, Colorado (other, 2021)
The San Luis Valley and associated underlying basin of south-central Colorado and north-central New Mexico is the largest structural and hydrologic basin of the Rio Grande Rift and fluvial system. The surrounding San Juan and Sangre de Cristo Mountains reveal evidence of widespread volcanism and transtensional tectonism beginning in the Oligocene and continuing to the present, as seen in fault displacement of Pleistocene to Holocene deposits along the eastern basin-bounding Sangre de Cristo fault system and fault zones along the western margin of the basin. The San Luis basin can generally be subdivided into northern and southern basins at the structural and physiographic high terrain of the San Luis Hills in the center of the basin, proximal to the Colorado-New Mexico stateline. The northern San Luis Valley can be subdivided into two subbasins at approximately the latitude of the Great Sand Dunes and San Luis Lakes, where the endorheic northern subbasin surface and subsurface flow currently accumulate in a series of playa lakes. To the south of this playa region, the Rio Grande has captured basin hydrology into a through-going fluvial system cutting through the San Luis Hills, carving the Rio Grande gorge, and ultimately flowing into the Gulf of Mexico. This surficial geologic map of the northern San Luis Valley, paired with the Alamosa, CO 1:100,000-scale geologic map (U.S. Geological Survey Scientific Investigations Map 3342) provides new and compiled geologic mapping that characterizes basin deposits and locates the traces of active faults, with the goal to provide geospatial data for future investigations related to western North American neotectonics, Pleistocene paleoclimate, and related geomorphic processes. In addition, present natural and anthropogenic water bodies have been located and updated for hydrologic modeling and water-usage investigations.

3 m Resolution 20th Percentile Canopy Height Estimates for the Upper Gunnison Basin derived from 2015 and 2019 LiDAR Data - Ian K Breckheimer (s3, 2021)
This is a map of 20th percentile canopy height above the ground for the Upper Gunnison River Basin based on 2015 and 2019 LiDAR data. Height is measured in meters. This dataset was generated from the terrain-normalized point clouds using functions in the R package lidR. The ground-classified points were first used to generate a bare-earth surface, which was subtracted from the point cloud elevation to generate a terrain-normalized point cloud. 80th percentile heights were calculated for the LiDAR returns in each pixel using a kernel density method implemented using the quantile() R function. Artifacts from steep topography and structures have not been removed from this dataset.

met.b1 (2021)
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Chemical and geophysical data collected along Oh-be-joyful Creek, Gunnison National Forest, Colorado - Martin Briggs (other, 2021)
As part of their Watershed Function Scientific Focus Area (SFA), Berkeley Lab and its collaborating institutions (e.g., USGS) have established a "Community Watershed" in the headwaters of the East River near Crested Butte, Colorado (USA), designed to quantify processes impacting the ability of mountainous systems to retain and release water, nutrients, carbon, and metals. The ongoing research spans a range of scales from hillslope to catchment to basin, with surface water and groundwater linking multiple geomorphic compartments. A major goal of this SFA research is to generate a transferable understanding of mountain hillslope to river dissolved nutrient, carbon, and metals transport, integrating extensive and novel field observations with fully coupled numerical models. The mountain headwater Oh-Be-Joyful Creek is part of the East River SFA located approximately 6 km northwest of the town of Crested Butte and is a key tributary of the Slate River. The creek is generally incised into bedrock (predominantly Mancos Shale) and many steeper sections have little to no bed sediment. Banks range from bedrock walls to avalanche and rock slide deposits. At an elevation of approximately 2900 m A.S.L., the regional Peeler fault intersects Oh-Be-Joyful Creek from the south creating a preferential groundwater discharge zone. This data release presents various water quality data collected along the Oh-be-joyful Creek from the main channel, groundwater discharge points, and small tributaries, including data collected during a constant rate dye injection near the Peeler fault zone.

East River Surface and Pore Water FTICR-MS Data Associated with “Implications of sample treatment on characterization of the riverine environmental metabolome” (ess_dive, 2021)
Surface and pore water samples were collected from distributed locations around Meander A in East River (Crested Butte, CO, USA) during the summer of 2018. This dataset consists of the characterization of dissolved organic matter using 12 Tesla Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS; in .xml format) analyzed through the Environmental Molecular Sciences Laboratory (EMSL; https://www.pnnl.gov/environmental-molecular-sciences-laboratory) using two different sample pre-treatment methods (solid phase extraction, no solid phase extraction) and two electrospray ionization methods (ESI-positive, ESI-negative) to identify the impacts of these choices on the final dataset. This study aimed to understand how the different sample processing methods influence the resulting FTICR-MS dataset. Any published work that utilizes data presented in this dataset should cite the dataset using the DOI number. If using the dataset, please acknowledge the U.S. Department of Energy (DOE) Office of Science (BER) Subsurface Biogeochemical Research (SBR) program, the Environmental Molecular Sciences Laboratory (EMSL), and Worldwide Hydrobiogeochemical Observation Network for Dynamic River Systems (WHONDRS). The publication DOI will be added to this abstract when available.

Styled 2018 snow depth basemap of the Upper East River domain - Ian K Breckheimer (s3, 2021)
This is a styled basemap showing snow depth on March 31st, 2018 derived from repeat LiDAR data collection by the Airborne Snow Observatory. This dataset is derived directly from: Painter, T. 2018. ASO L4 Lidar Snow Depth 3m UTM Grid, Version 1. Boulder, Colorado USA. NASA National Snow and Ice Data Center Distributed Active Archive Center. doi: https://doi.org/10.5067/KIE9QNVG7HP0. Small areas outside of the UER region, but within the extent of this map had missing data. These gaps were filled with linear regression relating 2018 and 2019 ASO snow depths (where one map was available), or regressions related snow depth to elevation (where neither 2018 nor 2019 data was available). Peak snow depths in 2018 were near the 20th percentile of the long-term average estimated from the Butte SNOTEL station. The color scale ranges from <20 cm (gray), through red (20 - 100 cm), yellow (100 - 200 cm), green (200 - 300 cm), and blue (300 - 400+ cm).

Biomass Inventories at Harvard Forest EMS Tower since 1993 - William Munger; Steven Wofsy (other, 2021)
In 1993, we installed 40 circular, 10 m radius biometric plots in the footprint of the EMS tower on Prospect Hill. We randomly placed the plots within 100 m increments along ten 500 m transects that extend from the tower in the northwest and southwest directions. In 2001, we removed three plots (G3, H3, H4) from the datasets and ceased measurements there due to their inundation by a beaver pond. In 1999, we installed 6 additional circular, 10 m radius biometric plots on the Simes Lot, adjacent to Prospect Hill to study the effects of a selective harvest that occurred there in the winter of 2000-01. In the summer of 2001, we expanded the harvested plots in size to 15 m radius and ceased measurements at one plot (X4) because it was unaffected by the harvest. The harvest also affected three of the original tower plots (A4, A5, B5), which were expanded in size as a part of the harvest plot group. Consequently, there are 34 tower plots and 8 harvest plots. We have taken the following ecological measurements at each site: tree growth, woody debris, litter, leaf area increment (LAI), leaf chemistry, and soil respiration and moisture.

Styled hillshade basemap for the Upper Gunnison domain - Ian K Breckheimer (s3, 2021)
This dataset is a styled basemap depicting topography the Upper Gunnison domain as a hillshade with contour lines, optimized for fast display on web maps and mobile devices. The underlying datasets are available as part of Release 3 of the RMBL Spatial Data Platform. Hillshade topography mimics the look of the landscape as if the surface topography was a homogeneous gray color and illuminated from the southwest. The contour intervals depicting topography are at 20 m spacing for light lines, and 100 m spacing for dark lines.

End-Member Mixing Analysis Data Package for the East River Watershed, CO USA. (ess_dive, 2021)
The data package consolidates water year 2016 stream, rain, snow and groundwater data used by Carroll et al. (2018) for end-member mixing analysis to isolate seasonal stream source within the East River, CO. Stream concentration and daily discharge are provided for the 11 sub-basins of the East River. The Inouye well defines deep groundwater. Weekly rain is collected at Bradley, Forest, LMWL and 403. Snow pits and snow melt chemistry are defined at multiple sites across the East River. Solutes provided include Mg, Ca, Sr, U, Cl, SO4, DIC, d2H and d18O. Carroll, R., Bearup, L., Brown, W., Dong, W., Bill, M., and K.H. Williams. 2018. Factors controlling groundwater and solute flux from snow-dominated basins. Hydrological Processes. Special Issue Water in the Critical Zone. 1-6. DOI:10.1002/hyp.13151.

NOAA/WDS Paleoclimatology - Woodhouse - Cochetopa Dome - PIPO - ITRDB CO594 (other, 2021)
This archived Paleoclimatology Study is available from the NOAA National Centers for Environmental Information (NCEI), under the World Data Service (WDS) for Paleoclimatology. The associated NCEI study type is Tree Ring. The data include parameters of tree ring with a geographic location of Colorado, United States Of America. The time period coverage is from 513 to -52 in calendar years before present (BP). See metadata information for parameter and study location details. Please cite this study when using the data.

East River Surface and Pore Water FTICR-MS Data Associated with “Implications of sample treatment on characterization of the riverine environmental metabolome” (ess_dive, 2021)
Surface and pore water samples were collected from distributed locations around Meander A in East River (Crested Butte, CO, USA) during the summer of 2018. This dataset consists of the characterization of dissolved organic matter using 12 Tesla Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS; in .xml format) analyzed through the Environmental Molecular Sciences Laboratory (EMSL; https://www.pnnl.gov/environmental-molecular-sciences-laboratory) using two different sample pre-treatment methods (solid phase extraction, no solid phase extraction) and two electrospray ionization methods (ESI-positive, ESI-negative) to identify the impacts of these choices on the final dataset. This study aimed to understand how the different sample processing methods influence the resulting FTICR-MS dataset. Any published work that utilizes data presented in this dataset should cite the dataset using the DOI number. If using the dataset, please acknowledge the U.S. Department of Energy (DOE) Office of Science (BER) Subsurface Biogeochemical Research (SBR) program, the Environmental Molecular Sciences Laboratory (EMSL), and Worldwide Hydrobiogeochemical Observation Network for Dynamic River Systems (WHONDRS). The publication DOI will be added to this abstract when available.

Qinayan/Soil-thickness: Soil thickness estimation - Qina (other, 2021)
This release includes Python codes and associated field sampling and remote sensing data for the estimation of the spatial distribution of soil thickness in two hillslopes in the Pump House area in the East River Watershed in the CO., the U.S.

1 m Resolution Multiscale Height-above-stream Wetness Index for the Upper Gunnison Domain - Hodnett L. A.; Cuartas A. D.; Rodrigues C. D.; Nobre; S. R. Saleska; Rennó; Silveira G. (s3, 2021)
This map is a soil moisture proxy derived from analysis of the UG 1m hydrologically corrected digital elevation model. The intuition behind this map is that areas that have flat topography and are near the elevation of local streams are likely to have high soil moisture. This index builds on the work of Nobre, A. D., Cuartas, L. A., Hodnett, M., Rennó, C. D., Rodrigues, G., Silveira, A., & Saleska, S. (2011). Height Above the Nearest Drainage–a hydrologically relevant new terrain model. Journal of Hydrology, 404(1-2), 13-29. The map was generated with a multi-step procedure. First, a binary map of streams was generated from the 1m DEM using the GRASS GIS r.waterhsed module with a multi-flow-direction algorithm. Then the SAGA GIS module "Height Above Stream Network" was used to interpolate stream elevations and subtract from terrain elevations, producing a map of the vertical distance above the nearest stream. This procedure was repeated 4 times with different flow accumulation thresholds for defining the stream network (8k, 32k, 128k, and 512k squre meters), and the resulting height above stream maps were averaged to get a multiscale height above stream measure. This map was then combined with an estimate of local slope to get the toographic index I, defined as: ln(1/(H + 5) + 1.1) /  (S + 50) where H is the height above local streams and S is the local slope. The resulting map was scaled to the range 0 to 1.

Geochemical exports to river from the intrameander hyporheic zone under transient hydrologic conditions, Water Resources Research: Dataset. (ess_dive, 2021)
To understand how redox processes influence carbon, nitrogen, and iron cycling within the intrameander hyporheic zone, we developed a biotic and abiotic reaction network and incorporated it into the reactive transport simulator PFLOTRAN. Two dimensional reactive flow and transport simulations were performed (1) to evaluate how transient hydrological conditions control the lateral redox zonation within an intrameander region of the East River in Colorado and (2) to quantify the impact of a single meander on subsurface exports of carbon and other geochemical species to the river. This data package includes simulated hydrologic and geochemical data from 23 Oct 2015 to 22 Oct 2016.