Genome-resolved metagenomics and metatranscriptomics of microbial communities in three meander-bound floodplain soils along the East River, Colorado. (ess_dive, 2021)
This dataset comprises paired environmental and genomic data for soil samples collected across meander-bound floodplains G (ERMG), L (ERML) and Z (ERMZ). A total of 96 soil samples (32 per floodplain) from the ~ 10-25 cm layer were collected in September 2015, during base flow conditions. An additional 32 soil samples were collected from ERML in September 2016, including three samples from a depth just above the water table. A subset of samples (14) collected in 2016 were used for metatranscriptomics as well as metagenomics. The data package includes: 1) A spread sheet with sample names, location and depth by meander-bound floodplain. 2) Total organic carbon (TOC), total inorganic carbon (TIC), total carbon (TC = TOC + TIC), total nitrogen (TN), and the TOC to TN ratio (TOC:N) from 2015 subsamples. 3) Soil chemistry for 2016 subsamples. 4) A spread sheet with elevation, Easting, Northing, and topographic position index (TPI) for each site sampled in 2015. 5) A kml file, which can be viewed in Google Earth, with the locations of the 96 soil sampling sites along the East River Watershed Floodplain in Colorado. Metagenomics and metatranscriptomics data, as well as reconstructed genomes, are available elsewhere (see data package methods and bioRxiv preprint for links to the data). 6) Two sets of reconstructed genomes with overlapping members (see bioRxiv preprint for description and associated data). Metagenomes and metatranscriptomes are available elsewhere (see data package methods and bioRxiv preprint). To view tar.gz files, the following software can be used: https://www.gnu.org/software/tar/, https://www.7-zip.org/.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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 [...]

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.

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.

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).

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.

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.

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 [...]

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.

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.

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.

SnowEx20 Grand Mesa In Situ Dielectric 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.

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.

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.

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”

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

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.

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 [...]

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.

Effects of Plant Removal on Mineralization Rates at the Rocky Mountain Biological Laboratory, Gunnison County, Colorado: 2018 (2021)
The loss of aboveground plant diversity alters belowground ecosystem function; yet, the mechanisms underpinning this relationship and the degree to which plant community structure and climate mediate the effects of plant species loss remain unclear. Here, we explored how plant species loss through experimental removal shaped belowground function in ecosystems characterized by different climatic regimes and edaphic properties. We measured plant community composition as well as potential carbon (C) and nitrogen (N) mineralization through laboratory soil incubations and microbial extracellular enzyme activity in soils collected from four unique plant removal experiments located along an elevational gradient in Colorado, USA, during the summer of 2018. We found that regardless of the identity of the removed species or the climate at each site plant removal decreased the absolute variation in potential N-mineralization rates and marginally reduced the magnitude of N-mineralization rates. While plant species removal also marginally reduced C-mineralization rates, C-mineralization, unlike N-mineralization, displayed sensitivity to the climatic and edaphic differences among sites, where C-mineralization was greatest at the high elevation site that receives the most precipitation annually and contains the largest soil total C pools. Plant removal had little impact on soil enzyme activity. Removal effects were not contingent on the amount of biomass removed annually, and shifts in mineralization rates occurred despite only marginal shifts in plant community structure following plant species removal. Our results present a surprisingly simple and consistent pattern of belowground response to the loss of dominant plant species across an elevational gradient with different climatic and edaphic properties, suggesting a common response of belowground ecosystem function to plant species loss regardless of which plant species are lost or the broader climatic context.

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.

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 - 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 [...]

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.

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>

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)
Supplemental Data Files for a submission to Geosciences, "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)" Funding for this work was provided through the U.S. Department of Energy Office of Legacy Management.

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 [...]

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).

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

Early snowmelt and warming experiments to study plant phenology - Diana K Jerome; William K. Petry; Amy M. Iler; K. A. Mooney (other, 2021)
Phenology - the timing of life events - determines how a species’ life cycle aligns with the abiotic and biotic environment, however, climate change has altered the environmental cues organisms use to track climate leading to shifts in phenology. In high latitude environments, phenological shifts in plants are associated with both temperature and the timing of snowmelt, but the mechanism underlying the effect of snowmelt on phenology remains unclear. Here we aim to disentangle the effects of experimental warming and earlier snowmelt on the phenology of three long lived perennial wildflowers. In the summer of 2019, we factorially crossed passive warming with early snowmelt timing within a subalpine plant community in the Colorado Rocky Mountains at the Rocky Mountain Biological Laboratory to understand the individual effects of these aspects of climate change.

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.

Waterlevel, geochemical, and borehole data from Rifle, Colorado from 2006-2016 - Li Yang; Mark J. Robbins; Pe Long; Chad Hobson; M. Conrad; Benjamin Potter; Mark J. Robbins; M. 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.

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 - Heidi Steltzer; Chelsea Wilmer; Heidi Steltzer; Chelsea Wilmer; Chelsea Wilmer; Chelsea Wilmer; Heidi Steltzer; Heidi Steltzer; Chelsea Wilmer; A. N. Henderson; Heidi Steltzer; A. N. Henderson; et al. (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”.

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.

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.

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 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.

East River Surface and Pore Water FTICR-MS Data Associated with “Implications of sample treatment on characterization of the riverine environmental metabolome” - Jacqueline Wells; Michael J. Wilkins; Nikola Tolic; Lupita Renteria; C. M. Saup; Jacqueline Wells; A. S. Nelson; Jason G. Toyoda; Michael J. Wilkins; Vanessa A. Garayburu-Caruso; A. S. Nelson; Robert E. Danczak; et al. (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.

Multi-year census of arthropod abundance on the plant Ligusticum porteri near Crested Butte, CO - M. L. Mullins; James H Den Uyl; E. 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.

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.

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.

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

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.

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.

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).

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.

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.

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.

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.

Data for Context-dependent biotic interactions control plant abundance across altitudinal environmental gradients, 2014, 2016, Colorado, USA. - Stephanie N. Kivlin; Melanie R Kazenel; J. S. Lynn; Jennifer A. Rudgers (other, 2021)
Many biotic interactions influence community structure, yet most distribution models for plants have focused on plant competition or used only abiotic variables to predict plant abundance. Furthermore, biotic interactions are commonly context-dependent across abiotic gradients. For example, plant-plant interactions can grade from competition to facilitation over temperature gradients. We used a hierarchical Bayesian framework to predict the abundances of 12 plant species across a mountain landscape and test hypotheses on the context-dependency of biotic interactions over abiotic gradients. We combined field-based estimates of six biotic interactions (foliar herbivory and pathogen damage, fungal root colonization, fossorial mammal disturbance, plant cover, and plant diversity) with abiotic data on climate and soil depth, nutrients, and moisture. All biotic interactions were significantly context-dependent along temperature gradients. Results supported the stress gradient hypothesis: As abiotic stress increased, the strength or direction of the relationship between biotic variables and plant abundance generally switched from negative (suggesting suppressed plant abundance) to positive (suggesting facilitation/mutualism). For half of the species, plant cover was the best predictor of abundance, suggesting that the prior focus on plant-plant interactions is well-justified. Explicitly incorporating the context-dependency of biotic interactions generated novel hypotheses about drivers of plant abundance across abiotic gradients and may improve the accuracy of niche models.

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”

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.

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.

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).

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.

Hydraulic test data - Lyndsay B Ball (other, 2020)
Boreholes were drilled in 2017 and 2018 in Redwell Basin, a headwater catchment underlain by mineralized and hydrothermally altered sedimentary rock in the Elk Mountains near the town of Crested Butte, Colorado. Site locations and well construction are documented under the main page of this data release. Hydraulic data were acquired during drilling and on core samples to estimate the hydraulic properties of selected geologic materials. While advancing the drill stem, long-interval packer tests were conducted in MW1 and MW2 boreholes to measure in-situ formation permeability. The open borehole interval targeted for each hydraulic test was exposed by raising the drill stem about 10 m above the bottom of the hole. A single-bladder packer [...]

Hybrid predictive modeling approach simulated evapotranspiration and ecosystem respiration data (ess_dive, 2020)
This dataset includes measured data used for developing hybrid-predictive-modeling (HPM) approach and simulated evapotranspiration and ecosystem respiration data across several Fluxnet sites, Snow Telemetry (SNOTEL) sites and East River Watershed in Colorado locations. Fluxnet sites considered in this study include: Saskatchewan-Aspen (CA-OAS), Saskatchewan-Black Spruce (CA-OBS), Niwot Ridge (US-NR1), Tonzi Ranch (US-TON), Vaira Ranch-lone (US-VAR), Santa Rita Mesquite (US-SRM), Walnut Gulch Lucky Hills Shrub (US-WHS), and Walnut Gulch Kendall Grasslands (US-WKG). Snotel sites include: Butte (ER-BT), Porphyry Creek (ER-PK) and Schofield Pass (ER-SP). The 16 East River Watershed locations with different vegetation types are denoted by: evergreen forests (EF), deciduous forests (DF), riparian shrublands (RS) and meadow grassland (MS). This data package includes: 1) A summary spread sheet of the sites and acronyms for data variables. 2) Processed Fluxnet datasets that are obtained from Fluxnet.fluxdata.org with HPM estimated evapotranspiration (ET) and ecosystem respiration (RECO) and the trained parameter metrics and models for Fluxnet sites; 3) Processed SNOTEL datasets obtained from www.nrcs.usda.gov/snow/ and HPM estimated ET and RECO; 4) Weather data at east river locations obtained from DAYMET (daymet.ornl.gov) as well as HPM estimated ET and RECO. Normalized difference vegetation index (NDVI) datasets are obtained from Landsat 5, 7 and 8 on Google Earth Engine platform. Detailed QA/QC and sampling methods of measured data are available at the original data source.

Digital subsurface data of Paleozoic rocks in the Upper Colorado River Basin in Wyoming, Utah, Colorado, Arizona, and New Mexico from USGS Regional Aquifer System Analysis (other, 2020)
The Upper Colorado River Basin has a drainage area of about 113,500 square miles in western Colorado, eastern Utah, southwestern Wyoming, northeastern Arizona, and northwestern New Mexico. In the 1980’s and 1990’s, the Upper Colorado River Basin was a study area under of the U.S. Geological Survey's Regional Aquifer-System Analysis (RASA) program (Sun and Johnston, 1994; Sun and Weeks, 1991). The objectives of the RASA program for the Upper Colorado River Basin were to provide regional assessments of major aquifer systems by providing quantitative assessments of the occurrence, movement, and availability of water stored in rock formations that underlie the basin/watershed. These assessments included: (1) the classification of stratigraphic [...]

Database for the Geologic Map of the Bonanza Caldera Area, Northeastern San Juan Mountains, Colorado (other, 2020)
The San Juan Mountains in southwestern Colorado have long been recognized as a site of exceptionally voluminous mid-Tertiary volcanism, including at least 24 major ignimbrite sheets (each 150-5,000 km3) and associated caldera structures active at 33-23 Ma. More recent volcanologic and petrologic studies in the San Juan region have focused mainly on several ignimbrite-caldera systems: the southeastern area (Platoro complex), western calderas (Uncompahgre-Silverton-Lake City), the central cluster (La Garita-Creede calderas). The northeast San Juan region that was far less studied until recently occupies a transition between earlier volcanism in central Colorado and the larger-volume younger ignimbrite-caldera foci farther south and west. [...]

The State of Open Data 2020 - Digital Science; Mariette van Selm; Nature Research; Mark Hahnel; Greg Goodey; Kathleen Shearer; Alan Hyndman; Leslie D. McIntosh; Brian Nosek; Grace Baynes; Merce Crosas (other, 2020)
We’re proud to release our fifth State of Open Data report and feel inspired and encouraged that most open data trends are heading in the right direction. The report outlines the impact of the COVID-19 pandemic on research and how this has influenced researchers' data sharing behaviour. Alongside survey results from 4,500 participants, the report includes a collection of articles from global industry experts.

Differential concentration discharge for the upper and lower reaches of the East River Watershed, Colorado (ess_dive, 2020)
This dataset captures the difference in concentration over the difference in discharge across upper and lower reaches of the East River watershed for 2015 and 2016 water years. The East River is part of the Watershed Function Scientific Focus Area (WFSFA) located in the Upper Colorado River Basin, United States. Herein, the upper reach is defined as the segment between EAQ (East Above Quigley) and EBC (East Below Copper), and the lower reach is defined as the segment between EBC and PH (Pump House). The overall purpose of the dataset is to provide a better accounting of the gains, losses or fractional solute turnover between sampling stations. Compiled data for the two segments (EAQ to EBC and EBC to PH) are provided in two Excel files, and the same data are provided in csv format in the corresponding zip files.

Turbulence dissipation rate estimated from Doppler Lidar measurements during LAPSE-RATE (other, 2020)
This dataset includes turbulence dissipation rate estimated from the University of Colorado Windcube v1 lidars and the University of Oklahoma Halo Streamline scanning Doppler Lidar during the 2018 LAPSE-RATE (Lower Atmospheric Profiling Studies at Elevation - a Remotely-piloted Aircraft Team Experiment) field campaign.This campaign took place in the San Luis Valley of Colorado between 14-21 July, 2018. On 14 July, both Windcube lidars were co-located at the Saguache site for intercomparison. WC49 (here named DPLR2) was moved to the Moffat School site late in the day on the 14th, where the Halo Streamline was deployed. Bad or missing data is set to -9999.9 for variable fields.

LAPSE-RATE ground-based Doppler lidar datasets from Univ Colorado Boulder (other, 2020)
This dataset includes measurements obtained using the University of Colorado Windcube v1 lidars during the 2018 LAPSE-RATE (Lower Atmospheric Profiling Studies at Elevation - a Remotely-piloted Aircraft Team Experiment) field campaign. This campaign took place in the San Luis Valley of Colorado between 14-21 July, 2018. On 14 July, both lidars were co-located at the Saguache site for intercomparison. WC49 (here named DPLR2) was moved to the Moffat School site late in the day on the 14th. Moffat School data starts on the 15th. Bad or missing data is set to -9999.0 for all fields. The a1 and the a2 datafiles are identical except that the a2 files include beam information (0, 90, 180, or 270) that was omitted from the a1 files.

Snowmelt Timing Maps Derived from MODIS for North America, Version 2, 2001-2018 - R. A. Matthews; M. Medler; Dorothy K. Hall; A. Flower; D. O'Leary III (other, 2020)
This data set provides snowmelt timing maps (STMs), cloud interference maps, and a map with the count of calculated snowmelt timing values for North America. The STMs are based on the Moderate Resolution Imaging Spectroradiometer (MODIS) standard 8-day composite snow-cover product MOD10A2 collection 6 for the period 2001-01-01 to 2018-12-31. The STMs were created by conducting a time-series analysis of the MOD10A2 snow maps to identify the DOY of snowmelt on a per-pixel basis. Snowmelt timing (no-snow) was defined as a snow-free reading following two consecutive snow-present readings for a given 500-m pixel. The count of STM values is also reported, which represents the number of years on record in the STMs from 2001-2018.

WHONDRS Summer 2019 Sampling Campaign: Global River Corridor Sediment FTICR-MS, Dissolved Organic Carbon, Aerobic Respiration, Elemental Composition, Grain Size, Total Nitrogen and Organic Carbon Content, Bacterial Abundance, and Stable Isotopes (v9) (2020)
The WHONDRS Summer 2019 Sampling (S19S) Campaign collected samples in 97 globally distributed river corridor systems between July and September 2019. Surficial streambed sediments were collected at three locations within each site (upstream, midstream, and downstream). Surface water was collected at the downstream site. This dataset includes a portion of the data types produced from the sediment samples and does not include any results from the surface water. Surface water data can be found at https://data.ess-dive.lbl.gov/view/doi:10.15485/1603775. The S19S campaign was designed with the science community to ask questions associated with links among core/transient metabolomes, microbial metabolism, biogeochemical function, and physical properties of watershed and river corridor systems. This data package was originally published in December 2020. It was updated in April 2021 (v2; modified files), May 2022 (v3; new and modified files), November 2022 (v4; new and modified files), January 2023 (v5 and v6; new and modified files), February 2023 (v7; new and modified files), August 2023 (v8; new and modified files), and July 2025 (new and modified files). See the change history section in the readme for details. This dataset contains (1) high resolution characterization of dissolved organic matter from sediment via 12 Tesla Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) through the Environmental Molecular Sciences Laboratory (EMSL; https://www.pnnl.gov/environmental-molecular-sciences-laboratory); (2) dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC); (3) respiration rates and normalized respiration rates calculated from laboratory sediment incubations; (4) X-ray fluorescence (XRF) elemental composition; (5) grain size distribution from the < 2 millimeter fraction of sediment; (6) total organic carbon and total nitrogen content; (7) bacterial abundance flow cytometry data; (8) sediment stable isotopes (C and N); (9) site photos; (10) field and laboratory methods metadata, including international generic sample number (IGSN) mapping file; (11) file-level metadata (flmd); (12) data dictionary (dd); and (13) water and sediment mass and volume used in incubations. The FTICR-MS files are .xml, and the data package includes instructions for using Formularity (https://omics.pnl.gov/software/formularity) and an R script to process the data based on the user’s specific needs. The XRF data includes .msa, .txt, and .spx files. All other data files are .csv, .pdf, .txt, .jpg, or .jpeg. CORRECTION: Carbon and nitrogen content are reported as percentages. The current column headers "01395_C_percent_per_mg" and "01397_N_percent_per_mg" are incorrect. These should read "01395_C_percent" and "01397_N_percent" and will be corrected in the next version of this data package.

Hybrid predictive modeling approach simulated evapotranspiration and ecosystem respiration data (ess_dive, 2020)
This dataset includes measured data used for developing hybrid-predictive-modeling (HPM) approach and simulated evapotranspiration and ecosystem respiration data across several Fluxnet sites, SNOTEL sites and East River locations (Chen et al., 2020 in review). Fluxnet sites considered in this study include: CA-OAS, CA-OBS, US-NR1, US-TON, US-VAR, US-SRM, US-WHS, US-WKG. Snotel sites Butte (ER-BT), Porphyry Creek (ER-PK) and Schofield Pass (ER-SP) are included as well 16 east river locations with different vegetation types denoted by evergreen forests (EF), deciduous forests (DF), riparian shrublands (RS) and meadow grassland (MS). This data package includes: 1) A summary spread sheet of the sites and acronyms for data variables. 2) Processed Fluxnet datasets that are obtained from Fluxnet.fluxdata.org with HPM estimated evapotranspiration (ET) and ecosystem respiration (RECO). Trained models and metrics for parameters for the Fluxnet sites were added in an update on November 2, 2020; 3) Processed SNOTEL datasets obtained from www.nrcs.usda.gov/snow/ and HPM estimated ET and RECO; 4) Weather data at east river locations obtained from DAYMET (daymet.ornl.gov) as well as HPM estimated ET and RECO. NDVI datasets are obtained from Landsat 5, 7 and 8 on Google Earth Engine platform. Detailed QA/QC and sampling methods of measured data are available at the original data source.

Differential concentration discharge for the upper and lower reaches of the East River Watershed, Colorado - Madison Burrus; Madison Burrus; S. S. Hubbard; Madison Burrus; Madison Burrus; Michelle Newcomer; Michelle Newcomer; S. S. Hubbard; Michelle Newcomer; Bhavna Arora; Michelle Newcomer; S. S. Hubbard; et al. (ess_dive, 2020)
This dataset captures the difference in concentration over the difference in discharge across upper and lower reaches of the East River watershed for 2015 and 2016 water years. The East River is part of the Watershed Function Scientific Focus Area (WFSFA) located in the Upper Colorado River Basin, United States. Herein, the upper reach is defined as the segment between EAQ (East Above Quigley) and EBC (East Below Copper), and the lower reach is defined as the segment between EBC and PH (Pump House). The overall purpose of the dataset is to provide a better accounting of the gains, losses or fractional solute turnover between sampling stations. Compiled data for the two segments (EAQ to EBC and EBC to PH) are provided in two Excel files, and the same data are provided in csv format in the corresponding zip files.

Post survey report for AOP Assignable Asset collection of Crested Butte, CO (ess_dive, 2020)
This report contains details of the National Ecological Observatory Network Airborne Observation Platform (NEON AOP) assignable asset (AA) flight over Crested Butte, Colorado (CO). The report is being prepared for Lawrence Berkeley National Lab (LBNL), the primary clients for the flights who contracted the NEON AOP for flights during June 2018. The report includes a summary of the acquired flight lines over the planned area, results of calibration surveys, and quality assurance (QA) results of the acquired data. Detailed reports on the acquired data and processing results were also delivered with the data. LBNL contracted the AA NEON AOP flights to observe watersheds of interest at Crested Butte with remotely sensed data including high resolution LiDAR, imaging spectroscopy, and high-resolution camera imagery. The remote sensing imagery acquired by the AOP intendeds to support LBNL on an interdisciplinary project on hydrology, biogeochemistry, and ecosystem functioning in the area surrounding the Rocky Mountain Biological Laboratory (RMBL), one of the most prominent ecological study sites in the United States.

Long-term flowering phenology and abundance data at Gothic, Colorado - Underwood B. D.; Irwin D. W.; Inouye N.; R. M. Dalton; Inouye (other, 2020)
Prof. David Inouye has been collecting data on the abundance and timing of flowers that fall within permanent plots at the Rocky Mountain Biological Laboratory (RMBL), in Gothic, Colorado, USA, from 1973 to present. During the growing season, flowers of each species are counted approximately every other day, though in some years the start and/or end of flowering were missed, and data were not collected in 1978 and 1990. A core set of 23 2 x 2 m plots have been followed 1974-present (excluding 1978 and 1990), and additional plots have been added through the years (two in 1985, three in 1998, and two in 2004). Data are now collected in a total of 30 plots and up to 135 plant species have been recorded in the plots. A companion dataset on the long-term abundance and phenology of bees at the RMBL is also available on the Open Science Framework (https://osf.io/kmxyn). The project is now managed by David's son Brian Inouye with collaborators Nora Underwood and Rebecca Irwin.

Post survey report for AOP Assignable Asset collection of Crested Butte, CO (ess_dive, 2020)
This report contains details of the National Ecological Observatory Network Airborne Observation Platform (NEON AOP) assignable asset (AA) flight over Crested Butte, Colorado (CO). The report is being prepared for Lawrence Berkeley National Lab (LBNL), the primary clients for the flights who contracted the NEON AOP for flights during June 2018. The report includes a summary of the acquired flight lines over the planned area, results of calibration surveys, and quality assurance (QA) results of the acquired data. Detailed reports on the acquired data and processing results were also delivered with the data. LBNL contracted the AA NEON AOP flights to observe watersheds of interest at Crested Butte with remotely sensed data including high resolution LiDAR, imaging spectroscopy, and high-resolution camera imagery. The remote sensing imagery acquired by the AOP intendeds to support LBNL on an interdisciplinary project on hydrology, biogeochemistry, and ecosystem functioning in the area surrounding the Rocky Mountain Biological Laboratory (RMBL), one of the most prominent ecological study sites in the United States.

Conifer water use patterns in the East River Watershed, Colorado US, based on stable water isotopes and cellulose isotopes (ess_dive, 2020)
This data package contains a series of datasets aimed at understanding the seasonal origins of water used by the dominant conifer species, Abies lasiocarpa and Picea engelmannii, in the East River Watershed. There is a distinct difference in the stable isotopic ratio of summer rain and snowpack and thus by tracking the isotopic ratio of the xylem water in trees, it is possible to separate when a tree is using snow vs. summer rain. Following typical protocols, we sampled and extracted water from soils in the "Research Meadow" near Gothic, CO within the East River Watershed through the 2016 growing season. The stable isotopic ratio of these waters were then measured. Using values of the isotopic ratio of precipitation and snowpack from that season, we develop a mixing model to show how the trees transitioned from use of snowpack to summer in late July. We extended the information on the seasonal origins of water from 2016 back until 1980 by using measurements of the isotopic ratio of cellulose from trees in the Research Meadow. The isotopic ratio of tree ring cellulose records a signal both of the Vapor Pressure Deficit at the leaf-atmosphere boundary and also the source water for the trees. We concluded from this extended analysis that the trees underwent transitions between periods where snow was the dominant water source and summer rain was the dominant water source. More details on this analysis can be found in the publication: Persistence and Plasticity in Conifer Water Use Strategies. JGR Biogeoscience. DOI 10.1029/2018JG004845. The dataset specifically includes stable isotope measurements of xylem and soil water for Spruce and Fir trees at the Rocky Mountain Biological Lab's Research Meadow as well as snowpack and precipitation stable isotopes from nearby National Atmospheric Deposition Program sites. Associated meteorological data is included, which is needed to understand the source water for the trees based on the cellulose measurements. The dataset also includes intra-ring measurements of the d18O and d13C of cellulose these same species of trees at the Ziegler Reservoir site in Snowmass, CO. This site was chosen because it is a location where subfossil wood from the last interglacial period (116,000 to 130,000 years ago) were discovered. We measured the d18O and d13C of the subfossil trees following the same protocol as the modern samples. We found that the trees utilized more summer rain during the interglacial period. This analysis and detailed methods are provided in the following manuscript: Wetter summers mitigated temperature stress on Rocky Mountain forests during the last interglacial warm period which is in revision at GRL but is available as a preprint here: 10.1002/essoar.10506740.2

Hybrid predictive modeling approach simulated evapotranspiration and ecosystem respiration data (ess_dive, 2020)
This dataset includes measured data used for developing hybrid-predictive-modeling (HPM) approach and simulated evapotranspiration and ecosystem respiration data across several Fluxnet sites, Snow Telemetry (SNOTEL) sites and East River Watershed in Colorado locations. Fluxnet sites considered in this study include: Saskatchewan-Aspen (CA-OAS), Saskatchewan-Black Spruce (CA-OBS), Niwot Ridge (US-NR1), Tonzi Ranch (US-TON), Vaira Ranch-lone (US-VAR), Santa Rita Mesquite (US-SRM), Walnut Gulch Lucky Hills Shrub (US-WHS), and Walnut Gulch Kendall Grasslands (US-WKG). Snotel sites include: Butte (ER-BT), Porphyry Creek (ER-PK) and Schofield Pass (ER-SP). The 16 East River Watershed locations with different vegetation types are denoted by: evergreen forests (EF), deciduous forests (DF), riparian shrublands (RS) and meadow grassland (MS). This data package includes: 1) A summary spread sheet of the sites and acronyms for data variables. 2) Processed fluxnet datasets that are obtained from Fluxnet.fluxdata.org with HPM estimated evapotranspiration (ET) and ecosystem respiration (RECO); 3) Processed SNOTEL datasets obtained from www.nrcs.usda.gov/snow/ and HPM estimated ET and RECO; 4) Weather data at east river locations obtained from DAYMET (daymet.ornl.gov) as well as HPM estimated ET and RECO. Normalized difference vegetation index (NDVI) datasets are obtained from Landsat 5, 7 and 8 on Google Earth Engine platform. Detailed QA/QC and sampling methods of measured data are available at the original data source.

LAPSE-RATE ground-based Doppler lidar datasets from Univ Colorado Boulder (other, 2020)
This dataset includes measurements obtained using the University of Colorado Windcube v1 lidars during the 2018 LAPSE-RATE (Lower Atmospheric Profiling Studies at Elevation - a Remotely-piloted Aircraft Team Experiment) field campaign. This campaign took place in the San Luis Valley of Colorado between 14-21 July, 2018. On 14 July, both lidars were co-located at the Saguache site for intercomparison. WC49 (here named DPLR2) was moved to the Moffat School site late in the day on the 14th. Moffat School data starts on the 15th. Bad or missing data is set to -9999.0 for all fields. The a1 and the a2 datafiles are identical except that the a2 files include beam information (0, 90, 180, or 270) that was omitted from the a1 files.

Ute Ulay Dam - oc534 (other, 2020)
The Ute Ulay Mining Complex is located along the Alpine Loop Scenic Byway just south of Lake City, Colorado. The Ute Ulay mining claims were discovered in 1871 and were one of the biggest producers of gold and silver in the San Juan Mountains. The Bureau of Land Management Gunnison Field Office has partnered with Hinsdale County to promote heritage tourism and has stabilized and preserved several structures within the mining complex. Ute Ulay was listed on the National Register of Historic Places in 2017. The Ute Ulay Dam was constructed in 1926 to provide hydropower to the mill that processed the gold and silver ores. The poured concrete dam measures 160 feet across and is reinforced with woven rebar. Water was forced into the hydropower plant from a flume originating from the dam. The hydropower plant produced power using three turbine water wheels. The power plant was used until 1951, when the flume collapsed. Source: Objaverse 1.0 / Sketchfab

Contiguous U.S. annual snow persistence and trends from 2001-2020 - John C Hammond (other, 2020)
Snow persistence (SP) or the snow cover index (SCI), is the fraction of time that snow is present on the ground for a defined period. Cloud covered index (CCI) is the fraction of time that there is no data, cloud, or sensor saturation for the same period. SP and CCI were calculated on a pixel by pixel basis using MODIS/Terra Snow Cover 8-Day L3 Global 500m Grid, Collection 6 obtained from the National Snow and Ice Data Center (NSIDC). January 1 - July 3 SP was calculated for each year as the fraction of 8-day MODIS images with snow present. The selected period brackets the temporal extent of peak snow accumulation to complete snow ablation in most parts of the western United States. The July 3 date is used because the 8-day MODIS image does not fall on the first of the month in this case. This data release contains gridded 500 m MODIS snow persistence for years 2001 to 2020 along with accompanying pixel by pixel trends for the entire contiguous U.S.

Migration Stopovers (WGFD) of Mule Deer in the Platte Valley Herd in Wyoming - Wyoming Game and Fish Department (other, 2020)
The Platte Valley Herd Corridor was designated by the Wyoming Game and Fish Department in 2018 (fig. 30). The Platte Valley herd contains approximately 11,000 mule deer. The corridor is based on two wintering populations, including a south segment from Saratoga, Wyoming, to the Colorado State line, and a north segment from Saratoga to the Dana Ridge area north of I-80. Winter ranges in the Platte Valley are more dispersed than winter ranges in other parts of the state, so deer migrate in many different directions. Many deer in the southern segment follow the Platte River south to summer ranges in Colorado. Most deer migrations in the north radiate south and east from winter ranges along I-80. The WGFD collared 45 additional mule deer [...]

Migration Corridors (WGFD Designated) of Mule Deer in the Platte Valley Herd in Wyoming - Wyoming Game and Fish Department (other, 2020)
The Platte Valley Herd Corridor was designated by the Wyoming Game and Fish Department in 2018 (fig. 30). The Platte Valley herd contains approximately 11,000 mule deer. The corridor is based on two wintering populations, including a south segment from Saratoga, Wyoming, to the Colorado State line, and a north segment from Saratoga to the Dana Ridge area north of I-80. Winter ranges in the Platte Valley are more dispersed than winter ranges in other parts of the state, so deer migrate in many different directions. Many deer in the southern segment follow the Platte River south to summer ranges in Colorado. Most deer migrations in the north radiate south and east from winter ranges along I-80. The WGFD collared 45 additional mule deer [...]

Turbulence dissipation rate estimated from Doppler Lidar measurements during LAPSE-RATE (other, 2020)
This dataset includes turbulence dissipation rate estimated from the University of Colorado Windcube v1 lidars and the University of Oklahoma Halo Streamline scanning Doppler Lidar during the 2018 LAPSE-RATE (Lower Atmospheric Profiling Studies at Elevation - a Remotely-piloted Aircraft Team Experiment) field campaign.This campaign took place in the San Luis Valley of Colorado between 14-21 July, 2018. On 14 July, both Windcube lidars were co-located at the Saguache site for intercomparison. WC49 (here named DPLR2) was moved to the Moffat School site late in the day on the 14th, where the Halo Streamline was deployed. Bad or missing data is set to -9999.9 for variable fields.

Conifer water use patterns in the East River Watershed, Colorado US, based on stable water isotopes and cellulose isotopes (ess_dive, 2020)
This data package contains a series of datasets aimed at understanding the seasonal origins of water used by the dominant conifer species, Abies lasiocarpa and Picea engelmannii, in the East River Watershed. There is a distinct difference in the stable isotopic ratio of summer rain and snowpack and thus by tracking the isotopic ratio of the xylem water in trees, it is possible to separate when a tree is using snow vs. summer rain. Following typical protocols, we sampled and extracted water from soils in the "Research Meadow" near Gothic, CO within the East River Watershed through the 2016 growing season. The stable isotopic ratio of these waters were then measured. Using values of the isotopic ratio of precipitation and snowpack from that season, we develop a mixing model to show how the trees transitioned from use of snowpack to summer in late July. We extended the information on the seasonal origins of water from 2016 back until 1980 by using measurements of the isotopic ratio of cellulose from trees in the Research Meadow. The isotopic ratio of tree ring cellulose records a signal both of the Vapor Pressure Deficit at the leaf-atmosphere boundary and also the source water for the trees. We concluded from this extended analysis that the trees underwent transitions between periods where snow was the dominant water source and summer rain was the dominant water source. More details on this analysis can be found in the publication: Persistence and Plasticity in Conifer Water Use Strategies. JGR Biogeoscience. DOI 10.1029/2018JG004845. The dataset specifically includes stable isotope measurements of xylem and soil water for Spruce and Fir trees at the Rocky Mountain Biological Lab's Research Meadow as well as snowpack and precipitation stable isotopes from nearby National Atmospheric Deposition Program sites. The dataset also includes intra-ring measurements of the d18O of cellulose from these trees at this site as well as at the Ziegler Reservoir site in Snowmass, CO. Associated meteorological data is included, which is needed to understand the source water for the trees based on the cellulose measurements.

Hybrid predictive modeling approach simulated evapotranspiration and ecosystem respiration data (ess_dive, 2020)
This dataset includes measured data used for developing hybrid-predictive-modeling (HPM) approach and simulated evapotranspiration and ecosystem respiration data across several Fluxnet sites, SNOTEL sites and East River locations (Chen et al., 2020 in review). Fluxnet sites considered in this study include: CA-OAS, CA-OBS, US-NR1, US-TON, US-VAR, US-SRM, US-WHS, US-WKG. Snotel sites Butte (ER-BT), Porphyry Creek (ER-PK) and Schofield Pass (ER-SP) are included as well 16 east river locations with different vegetation types denoted by evergreen forests (EF), deciduous forests (DF), riparian shrublands (RS) and meadow grassland (MS). This data package includes: 1) A summary spread sheet of the sites and acronyms for data variables. 2) Processed Fluxnet datasets that are obtained from Fluxnet.fluxdata.org with HPM estimated evapotranspiration (ET) and ecosystem respiration (RECO). Trained models and metrics for parameters for the Fluxnet sites were added in an update on November 2, 2020; 3) Processed SNOTEL datasets obtained from www.nrcs.usda.gov/snow/ and HPM estimated ET and RECO; 4) Weather data at east river locations obtained from DAYMET (daymet.ornl.gov) as well as HPM estimated ET and RECO. NDVI datasets are obtained from Landsat 5, 7 and 8 on Google Earth Engine platform. Detailed QA/QC and sampling methods of measured data are available at the original data source.

Digital subsurface data of Paleozoic rocks in the Upper Colorado River Basin in Wyoming, Utah, Colorado, Arizona, and New Mexico from USGS Regional Aquifer System Analysis (other, 2020)
The Upper Colorado River Basin has a drainage area of about 113,500 square miles in western Colorado, eastern Utah, southwestern Wyoming, northeastern Arizona, and northwestern New Mexico. In the 1980’s and 1990’s, the Upper Colorado River Basin was a study area under of the U.S. Geological Survey's Regional Aquifer-System Analysis (RASA) program (Sun and Johnston, 1994; Sun and Weeks, 1991). The objectives of the RASA program for the Upper Colorado River Basin were to provide regional assessments of major aquifer systems by providing quantitative assessments of the occurrence, movement, and availability of water stored in rock formations that underlie the basin/watershed. These assessments included: (1) the classification of stratigraphic [...]

Database for the Geologic Map of the Bonanza Caldera Area, Northeastern San Juan Mountains, Colorado (other, 2020)
The San Juan Mountains in southwestern Colorado have long been recognized as a site of exceptionally voluminous mid-Tertiary volcanism, including at least 24 major ignimbrite sheets (each 150-5,000 km3) and associated caldera structures active at 33-23 Ma. More recent volcanologic and petrologic studies in the San Juan region have focused mainly on several ignimbrite-caldera systems: the southeastern area (Platoro complex), western calderas (Uncompahgre-Silverton-Lake City), the central cluster (La Garita-Creede calderas). The northeast San Juan region that was far less studied until recently occupies a transition between earlier volcanism in central Colorado and the larger-volume younger ignimbrite-caldera foci farther south and west. [...]

RMBL USFS & BLM Lands - Shannon Sprott (other, 2020)
These are the parcel lands within Gunnison County that are either managed or owned by the US forest Service or the Bureau of Land Management. This layer was created by RMBL GIS, and is a subset of data from the original Exempt shapefile downloaded from the Gunnison County website. The data download link goes to the shapefile data format, though this data is available for download off the ArcGIS Online site as a KML, File Geodatabase, and GeoJson file types.

Natural abundance nitrate isotopes from Rifle and the East River Watershed, Colorado - Taylor Maavara; Taylor Maavara; Taylor Maavara; Patrick O. Sorensen; M. Conrad; Taylor Maavara; Patrick O. Sorensen; M. Conrad; Patrick O. Sorensen; M. Conrad; Nicholas J. Bouskill; Patrick O. Sorensen; et al. (ess_dive, 2020)
This data package provides data on the natural abundance isotopes of nitrate from various sources, including porewater, stream, and precipitation. The overall purpose of this data package is to complement additional data streams for nitrogen cycling metrics (e.g., riverine inorganic and organic nitrogen measurements) with specific data gleaned from the interpretation of terrestrial and riverine isotope measurements and collectively understand on how nitrogen is cycled around this system. The Rifle and East River are part of the Watershed Function Scientific Focus Area (WFSFA) located in the Upper Colorado River Basin, United States. Collection locations include: Pumphouse (multiple sampling dates), River (upstream/ downstream meander C), Shallow soil lysimeters (hillslope, toeslope, floodplain), Hillslope-floodplain borehole wells (i.e., Pumphouse Lower Montane (PLM) wells), and Potassium chloride(KCL)-extracted soil samples. Copper Creek sampling includes 8x river sample points and two tributaries sampled on Sept. Oct. 2017, July 2018. East River below the Rocky Mountain Biological Laboratory sampling includes 1 access point sampled on July, Sept. Oct. 2017. Rifle floodplain sampling includes well TT03 across multiple collection times over 2014. Data is provided in 5 individual files by location in csv format, or all compiled in Excel format.

Database for the Geologic Map of the Bonanza Caldera Area, Northeastern San Juan Mountains, Colorado (other, 2020)
The San Juan Mountains in southwestern Colorado have long been recognized as a site of exceptionally voluminous mid-Tertiary volcanism, including at least 24 major ignimbrite sheets (each 150-5,000 km3) and associated caldera structures active at 33-23 Ma. More recent volcanologic and petrologic studies in the San Juan region have focused mainly on several ignimbrite-caldera systems: the southeastern area (Platoro complex), western calderas (Uncompahgre-Silverton-Lake City), the central cluster (La Garita-Creede calderas). The northeast San Juan region that was far less studied until recently occupies a transition between earlier volcanism in central Colorado and the larger-volume younger ignimbrite-caldera foci farther south and west. The present study of the Bonanza area evaluates eruptive and magmatic processes of silicic Cordilleran volcanism in this northeast region, based on new geologic mapping (mainly summers of 2007-12) and concurrent petrologic and geochronologic analysis. The resulting map is based on new field mapping of volcanic rocks in thirteen 7.5-minute quadrangles in northeastern parts of the volcanic field, petrologic studies involving several hundred new chemical analyses, and high-resolution age determinations for about 130 sites. The Bonanza center contains exceptionally complete and diverse features of an ignimbrite caldera cycle, including voluminous andesite erupted before and after ignimbrite eruptions, complex compositional zonation within both the outflow ignimbrite sheet and the tuff concurrently ponded within the caldera, extensive portions of the ring-fault system that accommodated subsidence, thick compositionally diverse lavas that filled the caldera after subsidence, remnants of the original topographic caldera rim, widespread erosional exposure of caldera-floor features, and postcaldera granitic intrusions that generated a notably steep resurgent dome within the caldera. This geologic map database is accompanied by a report, which includes the formatted geologic map and explanatory pamphlet, available at https://doi.org/10.3133/sim3394. The authors ask that users of the geologic map database cite both the database and the report: Report: Lipman, P.W., 2020, Geologic map of the Bonanza Caldera Area, northeastern San Juan Mountains, Colorado: U.S. Geological Survey Scientific Investigations Map 3394, pamphlet 73 p., 2 sheets, scale 1:50,000, https://doi.org/10.3133/sim3394. Database: Joel E. Robinson, and Peter W. Lipman, 2020, Database for the Geologic Map of the Bonanza Caldera Area, Northeastern San Juan Mountains, Colorado: U.S. Geological Survey, https://doi.org/10.5066/P911OL4Q.

Natural abundance nitrate isotopes from Rifle and the East River Watershed, Colorado (ess_dive, 2020)
This data package provides data on the natural abundance isotopes of nitrate from various sources, including porewater, stream, and precipitation. The overall purpose of this data package is to complement additional data streams for nitrogen cycling metrics (e.g., riverine inorganic and organic nitrogen measurements) with specific data gleaned from the interpretation of terrestrial and riverine isotope measurements and collectively understand on how nitrogen is cycled around this system. The Rifle and East River are part of the Watershed Function Scientific Focus Area (WFSFA) located in the Upper Colorado River Basin, United States. Collection locations include: Pumphouse (multiple sampling dates), River (upstream/ downstream meander C), Shallow soil lysimeters (hillslope, toeslope, floodplain), Hillslope-floodplain borehole wells (i.e., Pumphouse Lower Montane (PLM) wells), and Potassium chloride(KCL)-extracted soil samples. Copper Creek sampling includes 8x river sample points and two tributaries sampled on Sept. Oct. 2017, July 2018. East River below the Rocky Mountain Biological Laboratory sampling includes 1 access point sampled on July, Sept. Oct. 2017. Rifle floodplain sampling includes well TT03 across multiple collection times over 2014. Data is provided in 5 individual files by location in csv format, or all compiled in Excel format.

Data release for Geologic Map of the Homestake Reservoir 7.5' quadrangle, Lake, Pitkin, and Eagle Counties, Colorado - Chester A Ruleman (other, 2020)
The Homestake Reservoir 7.5' quadrangle lies at the northwestern end of the Upper Arkansas Valley, and headwaters of the Arkansas River, and the Roaring Fork, Fryingpan, and Eagle Rivers of the Colorado River system. The quadrangle lies within tectonic provinces of the 1.4 Ga Picuris Orogeny, the late Paleozoic Ancestral Rockies, Late Cretaceous-Paleocene Laramide orogeny, Oligocene to Miocene, and Pliocene?, volcanism, and Miocene to the present Rio Grande rift extensional tectonics. In the eastern half of the quadrangle, high-angle, east-dipping, Neogene normal faults displace Proterozoic rocks, and locally Mio-Pliocene? volcanic rocks. Many quartz veins and hydrothermally altered zones are exposed along the eastern flank of the [...]

ASO L4 Lidar Point Cloud Digital Terrain Model 3m UTM Grid, Version 1 - Kat Bormann; Thomas Painter (other, 2020)

Daymet: Daily Surface Weather Data on a 1-km Grid for North America, Version 4 - R. Shrestha; Y. Wei; M.M. Thornton; P.E. Thornton; S-C. Kao (other, 2020)
This dataset provides Daymet Version 4 data as gridded estimates of daily weather parameters for North America, Hawaii, and Puerto Rico. Daymet variables include the following parameters: minimum temperature, maximum temperature, precipitation, shortwave radiation, vapor pressure, snow water equivalent, and day length. The dataset covers the period from January 1, 1980, to December 31 (or December 30 in leap years) of the most recent full calendar year for the Continental North America and Hawaii spatial regions. Data for Puerto Rico is available starting in 1950. Each subsequent year is processed individually at the close of a calendar year. Daymet variables are provided as individual files, by variable and year, at a 1 km x 1 km spatial resolution and a daily temporal resolution. Areas of Hawaii and Puerto Rico are available as files separate from the continental North America. Data are in a North America Lambert Conformal Conic projection and are distributed in a standardized Climate and Forecast (CF)-compliant netCDF file format.

Turbulence dissipation rate estimated from Doppler Lidar measurements during LAPSE-RATE (other, 2020)
This dataset includes turbulence dissipation rate estimated from the University of Colorado Windcube v1 lidars and the University of Oklahoma Halo Streamline scanning Doppler Lidar during the 2018 LAPSE-RATE (Lower Atmospheric Profiling Studies at Elevation - a Remotely-piloted Aircraft Team Experiment) field campaign.This campaign took place in the San Luis Valley of Colorado between 14-21 July, 2018. On 14 July, both Windcube lidars were co-located at the Saguache site for intercomparison. WC49 (here named DPLR2) was moved to the Moffat School site late in the day on the 14th, where the Halo Streamline was deployed. Bad or missing data is set to -9999.9 for variable fields.

Water Level Data from Wells PLM1 and PLM6 for the East River Watershed, Colorado (ess_dive, 2020)
This data set contains water level data for the PLM1 and PLM6 wells. PLM1 and PLM6 are location identifiers used by the Watershed Function SFA project for two groundwater monitoring wells along an elevation gradient located along the lower montane life zone of a hillslope near the Pumphouse location. These wells used to monitor subsurface water and carbon inventories and fluxes at the East River Watershed, Colorado, USA. Complete metadata information on the PLM1 and PLM6 wells are available in the related data package reference Varadharajan C, et al (2020). https://doi.org/10.15485/1660962. Data are reported in .csv files per well. The latitude and longitude of each location are given in a file called locations.csv. These data are used for determining the seasonally dependent flow of groundwater under the PLM hillslope. The downslope flow of groundwater in combination with data on groundwater chemistry can be used to estimate rates of solute export from the hillslope to the floodplain and river. These data products are part of the Watershed Function Scientific Focus Area collection effort to further scientific understanding of biogeochemical dynamics from genome to watershed scales.

Turbulence dissipation rate estimated from Doppler Lidar measurements during LAPSE-RATE (other, 2020)
This dataset includes turbulence dissipation rate estimated from the University of Colorado Windcube v1 lidars and the University of Oklahoma Halo Streamline scanning Doppler Lidar during the 2018 LAPSE-RATE (Lower Atmospheric Profiling Studies at Elevation - a Remotely-piloted Aircraft Team Experiment) field campaign.This campaign took place in the San Luis Valley of Colorado between 14-21 July, 2018. On 14 July, both Windcube lidars were co-located at the Saguache site for intercomparison. WC49 (here named DPLR2) was moved to the Moffat School site late in the day on the 14th, where the Halo Streamline was deployed. Bad or missing data is set to -9999.9 for variable fields.

Natural abundance nitrate isotopes from Rifle and the East River Watershed, Colorado (ess_dive, 2020)
This data package provides data on the natural abundance isotopes of nitrate from various sources, including porewater, stream, and precipitation. The overall purpose of this data package is to complement additional data streams for nitrogen cycling metrics (e.g., riverine inorganic and organic nitrogen measurements) with specific data gleaned from the interpretation of terrestrial and riverine isotope measurements and collectively understand on how nitrogen is cycled around this system. The Rifle and East River are part of the Watershed Function Scientific Focus Area (WFSFA) located in the Upper Colorado River Basin, United States. Collection locations include: Pumphouse (multiple sampling dates), River (upstream/ downstream meander C), Shallow soil lysimeters (hillslope, toeslope, floodplain), Hillslope-floodplain borehole wells (i.e., Pumphouse Lower Montane (PLM) wells), and Potassium chloride(KCL)-extracted soil samples. Copper Creek sampling includes 8x river sample points and two tributaries sampled on Sept. Oct. 2017, July 2018. East River below the Rocky Mountain Biological Laboratory sampling includes 1 access point sampled on July, Sept. Oct. 2017. Rifle floodplain sampling includes well TT03 across multiple collection times over 2014. Data is provided in 5 individual files by location in csv format, or all compiled in Excel format.

Post survey report for AOP Assignable Asset collection of Crested Butte, CO (ess_dive, 2020)
This report contains details of the National Ecological Observatory Network Airborne Observation Platform (NEON AOP) assignable asset (AA) flight over Crested Butte, Colorado (CO). The report is being prepared for Lawrence Berkeley National Lab (LBNL), the primary clients for the flights who contracted the NEON AOP for flights during June 2018. The report includes a summary of the acquired flight lines over the planned area, results of calibration surveys, and quality assurance (QA) results of the acquired data. Detailed reports on the acquired data and processing results were also delivered with the data. LBNL contracted the AA NEON AOP flights to observe watersheds of interest at Crested Butte with remotely sensed data including high resolution LiDAR, imaging spectroscopy, and high-resolution camera imagery. The remote sensing imagery acquired by the AOP intendeds to support LBNL on an interdisciplinary project on hydrology, biogeochemistry, and ecosystem functioning in the area surrounding the Rocky Mountain Biological Laboratory (RMBL), one of the most prominent ecological study sites in the United States.

Data supplementing Lichtenberg et al. (2020) Competition for nectar resources does not affect bee foraging tactic constancy. Ecological Entomology - R. E. Irwin (other, 2020)
This dataset contains data and scripts that supplement the publication Lichtenberg et al. (2020) Competition for nectar resources does not affect bee foraging tactic constancy. Ecological Entomology. DOI: 10.1111/een.12866 Please cite the above article if you use any of the included data or code.

Digital subsurface data of Paleozoic rocks in the Upper Colorado River Basin in Wyoming, Utah, Colorado, Arizona, and New Mexico from USGS Regional Aquifer System Analysis (other, 2020)
The Upper Colorado River Basin has a drainage area of about 113,500 square miles in western Colorado, eastern Utah, southwestern Wyoming, northeastern Arizona, and northwestern New Mexico. In the 1980?s and 1990?s, the Upper Colorado River Basin was a study area under of the U.S. Geological Survey's Regional Aquifer-System Analysis (RASA) program (Sun and Johnston, 1994; Sun and Weeks, 1991). The objectives of the RASA program for the Upper Colorado River Basin were to provide regional assessments of major aquifer systems by providing quantitative assessments of the occurrence, movement, and availability of water stored in rock formations that underlie the basin/watershed. These assessments included: (1) the classification of stratigraphic sequences into those intervals that constitute aquifers and those that constitute confining beds; and (2) the generation of maps that portrayed the areal extent of aquifers, aquifer thickness, and overburden thickness. These studies generated a large body of subsurface geologic information as part of the regional aquifer analyses, some of which are captured in this digital data release. Aquifer systems in consolidated rocks in the Upper Colorado River Basin have been grouped into three major subdivisions of sedimentary rocks; in descending order: (1) Tertiary-rock aquifers, (2) Mesozoic-rock aquifers, and (3) Paleozoic-rock aquifers (Taylor and others, 1983; 1986). Within each aquifer group, rocks are further divided into aquifers and confining units on the basis of lithology, depositional environment, and hydrologic characteristics (Glover and others, 1998; Freethy and Cordy, 1991; Geldon, 2003). In a report describing consolidated-rock aquifers of Paleozoic age, 7 hydrostratigraphic units were defined, four aquifers and three confining units (Geldon, 2003). The hydrostratigraphic units of Paleozoic age are locally exposed around the margins of uplifts and in deeply-incised canyon; they occur widely in the subsurface of the Upper Colorado River Basin study area, except in parts of the Uinta, Wind River, and Uncompahgre uplifts where they have been removed by erosion. These hydrostratigraphic units are part of the stratigraphic sequence of Paleozoic rocks that has a total thickness of more than 5,000 ft. This digital dataset contains spatial datasets corresponding to the contoured subsurface maps of Paleozoic rock units produced by the U.S. Geological Survey's Regional Aquifer-System Analysis (RASA) of the Upper Colorado River Basin (Geldon, 2003). The data define the thickness, extent, nomenclature, and facies characteristics of principal hydrostratigraphic units of Paleozoic age in the basin. The digital data describe the following hydrostratigraphic units: the Flathead aquifer, the Gros Ventre confining unit, the Bighorn aquifer, the Elbert-Parting confining unit, the Madison aquifer (consisting of two zones, the Redwall-Leadville zone, and the Darwin-Humbug zone), the Four Corners confining unit (consisting of the Belden-Molas subunit and the Paradox-Eagle Valley subunit), and the Canyonlands aquifer (consisting of three zones, the Cutler-Maroon zone, the Weber-de Chelly zone, and the Park City-State Bridge zone). Contoured thickness and lithology data for each unit are contained in line features classes within a geodatabase; unit extents, facies extents, and formation nomenclatural extents are represented as polygon feature classes. Both types of data are also saved as individual shapefiles. Nonspatial tables define the data sources used, terminology, and the stacking hierarchy and component geologic formations of each the of hydrostratigraphic units.

Water Level Data from Wells PLM1 and PLM6 for the East River Watershed, Colorado (ess_dive, 2020)
This data set contains water level data for the PLM1 and PLM6 wells. PLM1 and PLM6 are location identifiers used by the Watershed Function SFA project for two groundwater monitoring wells along an elevation gradient located along the lower montane life zone of a hillslope near the Pumphouse location. These wells used to monitor subsurface water and carbon inventories and fluxes at the East River Watershed, Colorado, USA. Complete metadata information on the PLM1 and PLM6 wells are available in the related data package reference Varadharajan C, et al (2020). https://doi.org/10.15485/1660962. Data are reported in .csv files per well. The latitude and longitude of each location are given in a file called locations.csv. These data are used for determining the seasonally dependent flow of groundwater under the PLM hillslope. The downslope flow of groundwater in combination with data on groundwater chemistry can be used to estimate rates of solute export from the hillslope to the floodplain and river. These data products are part of the Watershed Function Scientific Focus Area collection effort to further scientific understanding of biogeochemical dynamics from genome to watershed scales.

Hybrid predictive modeling approach simulated evapotranspiration and ecosystem respiration data (ess_dive, 2020)
This dataset includes measured data used for developing hybrid-predictive-modeling (HPM) approach and simulated evapotranspiration and ecosystem respiration data across several Fluxnet sites, SNOTEL sites and East River locations (Chen et al., 2020 in review). Fluxnet sites considered in this study include: CA-OAS, CA-OBS, US-NR1, US-TON, US-VAR, US-SRM, US-WHS, US-WKG. Snotel sites Butte (ER-BT), Porphyry Creek (ER-PK) and Schofield Pass (ER-SP) are included as well 16 east river locations with different vegetation types denoted by evergreen forests (EF), deciduous forests (DF), riparian shrublands (RS) and meadow grassland (MS). This data package includes: 1) A summary spread sheet of the sites and acronyms for data variables. 2) Processed Fluxnet datasets that are obtained from Fluxnet.fluxdata.org with HPM estimated evapotranspiration (ET) and ecosystem respiration (RECO). Trained models and metrics for parameters for the Fluxnet sites were added in an update on November 2, 2020; 3) Processed SNOTEL datasets obtained from www.nrcs.usda.gov/snow/ and HPM estimated ET and RECO; 4) Weather data at east river locations obtained from DAYMET (daymet.ornl.gov) as well as HPM estimated ET and RECO. NDVI datasets are obtained from Landsat 5, 7 and 8 on Google Earth Engine platform. Detailed QA/QC and sampling methods of measured data are available at the original data source.

Hydrologic monitoring data - Lyndsay B Ball (other, 2020)
Boreholes were drilled in 2017 and 2018 in Redwell Basin, a headwater catchment underlain by hydrothermally altered sedimentary rock in the Elk Mountains near the town of Crested Butte, Colorado. Two boreholes were completed as vertically discrete nested monitoring wells (MW1 as MW1A-MW1D and MW2.1 as MW2.1A-MW2.1C) and one borehole was completed as a single monitoring well (MW2 as RP8). Site locations and well construction are documented under the main page of this data release. Absolute (non-vented) pressure and temperature data loggers (PTDs) were deployed in these wells to monitor groundwater levels and fluid temperature over time. The period of record covers August 2018-September 2019 for all wells; the period of record for MW1D [...]

MuSLI Multi-Source Land Surface Phenology Yearly North America 30 m V001 - Mark Friedl (other, 2020)

RMBL Digitized Herbarium Records - C. F. Williams (other, 2020)
Vascular Plants curated within the Rocky Mountain Biological Laboratory Herbarium. Specimens date to 1929 and are primarily from the East River and upper Gunnison basin.

Changing climate drives divergent and nonlinear shifts in flowering phenology across elevations - Nicole E. Rafferty (other, 2020)

Data from: Foraging efficiency and size matching in a plant – pollinator community: the importance of sugar content and tongue length - M. Stang; Saskia G.T. Klumpers; Peter G.L. Klinkhamer (other, 2020)
A longstanding question in ecology is how species interactions are structured within communities. Although evolutionary theory predicts close size matching between floral nectar tube depth and pollinator proboscis length of interacting species, such size matching has seldom been shown and explained in multispecies assemblages. Here, we investigated the degree of size matching among Asteraceae and their pollinators and its relationship with foraging efficiency. The majority of pollinators, especially Hymenoptera, choose plant species on which they had high foraging efficiencies. When proboscides were shorter than nectar tubes, foraging efficiency rapidly decreased because of increased handling time. When proboscides were longer than nectar tubes, a decreased nectar reward rather than an increased handling time made shallow flowers more inefficient to visit. Altogether, this led to close size matching. Overall, our results show the importance of nectar reward and handling time as drivers of plant – pollinator network structure.

NEON AOP Survey of Upper East River CO Watersheds: LAZ Files, LiDAR Surface Elevation, Terrain Elevation, and Canopy Height Rasters (2020)
Lawrence Berkeley National Laboratory (LBNL) contracted the National Ecological Observatory Network Airborne Observation Platform (NEON AOP) to observe watersheds of interest surrounding Crested Butte, CO with remotely sensed data, including LiDAR. The flight box design encompassed the watersheds, surveying a total area of 334 km2 across 72 lines. The instrument used was an Optech Gemini, with a pulse density of 2-9 pulses m-2 across the study area (see final report document for detailed information). These LiDAR data are the primary data that were provided by NEON including LAZ files of a classified point cloud, and geotifs of a digital surface elevation model, digital terrain elevation model, and a canopy height model at 1 m resolution with a height threshold of > 2 m. Raster files can also be found on Google Earth Engine: https://code.earthengine.google.com/5c96bbc96ffd50e3c8b1433b34a0bb86.

Coronavirus testing indicates transmission risk increases along wildlife supply chains for human consumption in Viet Nam, 2013-2014 (2020)
Outbreaks of emerging coronaviruses in the past two decades and the current pandemic of a novel coronavirus (SARS-CoV-2) that emerged in China highlight the importance of this viral family as a zoonotic public health threat. To gain a better understanding of coronavirus presence and diversity in wildlife at wildlife-human interfaces in three southern provinces in Viet Nam 2013-2014, we used consensus Polymerase Chain Reactions to detect coronavirus sequences. In comparison to previous studies, we observed high proportions of positive samples among field rats (34.0%, 239/702) destined for human consumption and insectivorous bats in guano farms (74.8%, 234/313) adjacent to human dwellings. Most notably among field rats, the odds of coronavirus RNA detection significantly increased along the supply chain from field rats sold by traders (reference group; 20.7% positivity, 39/188) by a factor of 2.2 for field rats sold in large markets (32.0%, 116/363) and 10.0 for field rats sold and served in restaurants (55.6%, 84/151). Coronaviruses were also detected in rodents on the majority of wildlife farms sampled (60.7%, 17/28). These coronaviruses were found in the Malayan porcupines (6.0%, 20/331) and bamboo rats (6.3%, 6/96) that are raised on wildlife farms for human consumption as food. We identified six known coronaviruses in bats and rodents, clustered in three Coronaviridae genera, including the Alpha-, Beta-, and Gammacoronaviruses. Our analysis also suggested either mixing of animal excreta in the environment or interspecies transmission of coronaviruses, as both bat and avian coronaviruses were detected in rodent feces on wildlife farms. The mixing of multiple coronaviruses, and their apparent amplification along the wildlife supply chain into restaurants, suggests maximal risk for end consumers and likely underpins the mechanisms of zoonotic spillover to people. PREDICT data associated with event, sample, specimen, test, and sequence result finding were collected on paper field forms, project-standardized excel templates, or online forms and uploaded in the EIDITH database. EIDITH helped clean and curate this data and provided an extract on 23 March, 2020 of the dataset with fields used in this publication. Column name    Field description Country    Country SiteName    The name of the site where the samples were collected District    District within Vietnam StateProv    Province within Vietnam SiteLatitude    Site latitude rounded up to 2 decimal places  SiteLongitude    Site longitude rounded up to 2 decimal places  EventName    Generated as sitename + event date DomesticAnimals    List of domestic and other animals observed at a site (if observed if not blank) AnimalID    Country defined animal ID TaxaGroup    Taxonomic description of the animal sampled 4 categories (Bats, Carnivores, Non-human Primates, Rodents & Shrews) SpeciesScientificName    The scientific name of the animal sampled. If complete genus species is unknown, this will be the next known level of taxonomic classification (i.e. genus, subfamily, family) CommonName    The english common name of the animal sampled. If the complete geenus species is unknown, the english name will be set to Unidentified long-fingered bat in the Miniopterus genus, as an example for Miniopterus sp.. CommonNameFieldMorphology    When an animal is barcoded this is set to the species_scientific_name as defined in the field before the species_scientific_name is updated with the barcoding results. If the barcoding test did not result in a species identification or the animal was not barcoded, this field will be left blank. IDCertainty    If the animal was barcoded, the certainty corresponds to the barcoding results and indicates the percent of sequence match. For animals not barcoded, the certainty is based on the field team's confidence in the species identification. Order    Taxonomic order Family     Taxonomic family (if known) Genus Taxonomic genus (if known) SampleDate    The date the animal was sampled in the field MM/DD/YY SpecimenID    The text value of the ID of the specimen, which matches the label on the physical specimen. SpecimenType    The type of specimen collected TestType    The type of PCR that the PCR was performed for TestRequested    The viral family that the PCR was performed for TestRequestedProtocol    The testing assay used to perform the PCR test ConfirmationResult    The confirmation test result (Negative or Positive) Sequence    The genetic sequence (if positive otherwise NULL) GenbankAccessionNumber    The Genbank accession number (if positive otherwise NULL) Virus    Which viruses were associated with each specimen x test combination (if positive otherwise NULL) - long version VirusGroup    Which viruses were associated with each specimen x test combination (if positive otherwise NULL) - short version

Kinetics Data of Iron(II), Manganese(II), Dissolved Organic Carbon and Nitrate from Batch Incubation Experiments Using Hyporheic Sediments from the East River Watershed, Colorado. (ess_dive, 2020)
Hyporheic zones act as critical ecological links between terrestrial and aquatic systems where redox-sensitive metals of iron (Fe) and manganese (Mn) significantly impact nutrient cycling and water quality. In order to understand the production, release and speciation of Fe(II) and Mn(II) in groundwater, we conducted batch incubation experiments using sediment samples from a hyporheic zone of the East River floodplain in Colorado. The East River is part of the Watershed Function Scientific Focus Area (WFSFA) located in the Upper Colorado River Basin, United States. Collection and processing of the data is described in the Methods, along with details of data file contents. There are 6 data files provided in two formats: 1 zip-folder of .csv (open source) files, and 1 zip-folder of .xlsx (Excel) files. The data tables provided in the two formats are the exact same.

Kinetics Data of Iron(II), Manganese(II), Dissolved Organic Carbon and Nitrate from Batch Incubation Experiments Using Hyporheic Sediments from the East River Watershed, Colorado. - Amrita Bhattacharyya; Amrita Bhattacharyya; Amrita Bhattacharyya; Wenming Dong; P. M. Fox; Wenming Dong; P. M. Fox; P. Nico; P. Nico; P. M. Fox; Wenming Dong; Markus Bill; et al. (ess_dive, 2020)
Hyporheic zones act as critical ecological links between terrestrial and aquatic systems where redox-sensitive metals of iron (Fe) and manganese (Mn) significantly impact nutrient cycling and water quality. In order to understand the production, release and speciation of Fe(II) and Mn(II) in groundwater, we conducted batch incubation experiments using sediment samples from a hyporheic zone of the East River floodplain in Colorado. The East River is part of the Watershed Function Scientific Focus Area (WFSFA) located in the Upper Colorado River Basin, United States. Collection and processing of the data is described in the Methods, along with details of data file contents. There are 6 data files provided in two formats: 1 zip-folder of .csv (open source) files, and 1 zip-folder of .xlsx (Excel) files. The data tables provided in the two formats are the exact same.

Plant composition data from 67 grassland sites of the Upper Gunnison Basin, CO, USA, 2014 - Melanie R Kazenel; Stephanie N. Kivlin; Jennifer A. Rudgers; J. S. Lynn (other, 2020)
Here, we deposit data from a vegetation survey conducted in 2014. The data was collected to document current vegetation patterns in the region, parameterize species distribution models, and assess community turnover in flower color. The survey was conducted in the Upper Gunnison Basin and the environs around the Rocky Mountain Biological Laboratory, CO, USA, spanning an elevation gradient from 2700-4000m above sea level. Data were acquired through visual estimates of percent cover of species within replicate quadrats in a site. We include information scraped from the USDA Plants Database (https://plants.sc.egov.usda.gov/java/) on species lifeform, life history, and invasive status.

The Importance of Interflow to Groundwater Recharge in a Snowmelt-Dominated, Alpine Watershed, Geophysical Research Letters: Modeling and Data Package (ess_dive, 2020)
This data package contains hydrologic modeling input and output files for the East River (ER_PRMS.zip) and Copper Creek (CC_GSFLOW.zip) for water years 1987 to 2018. These data were used to generate simulated results published in Geophysical Research Letters (Carroll et al., 2019) describing the importance of interflow in generating groundwater recharge in the upper subalpine. The East River and Copper Creek are part of the Watershed Function Scientific Focus Area (WFSFA) located in the Upper Colorado River Basin, United States. The hydrologic model uses the U.S. Geological Survey coupled groundwater and surface water flow model (GSFLOW). Input and output files are askii format, while the model executable (gsflow.exe), source code, example problems and documentation describing model files is provided at the following U.S. Geological Survey website. https://www.usgs.gov/software/coupled-ground-water-and-surface-water-flow-model-gsflow. GSFLOW executables are compiled for either Microsoft Windows or Linux operating systems.

The Importance of Interflow to Groundwater Recharge in a Snowmelt-Dominated, Alpine Watershed, Geophysical Research Letters: Modeling and Data Package (ess_dive, 2020)
This data package contains hydrologic modeling input and output files for the East River (ER_PRMS.zip) and Copper Creek (CC_GSFLOW.zip) for water years 1987 to 2018. These data were used to generate simulated results published in Geophysical Research Letters (Carroll et al., 2019) describing the importance of interflow in generating groundwater recharge in the upper subalpine. The East River and Copper Creek are part of the Watershed Function Scientific Focus Area (WFSFA) located in the Upper Colorado River Basin, United States. The hydrologic model uses the U.S. Geological Survey coupled groundwater and surface water flow model (GSFLOW). Input and output files are askii format, while the model executable (gsflow.exe), source code, example problems and documentation describing model files is provided at the following U.S. Geological Survey website. https://www.usgs.gov/software/coupled-ground-water-and-surface-water-flow-model-gsflow. GSFLOW executables are compiled for either Microsoft Windows or Linux operating systems.

Differential concentration discharge for the upper and lower reaches of the East River Watershed, Colorado (ess_dive, 2020)
This dataset captures the difference in concentration over the difference in discharge across upper and lower reaches of the East River watershed for 2015 and 2016 water years. The East River is part of the Watershed Function Scientific Focus Area (WFSFA) located in the Upper Colorado River Basin, United States. Herein, the upper reach is defined as the segment between EAQ (East Above Quigley) and EBC (East Below Copper), and the lower reach is defined as the segment between EBC and PH (Pump House). The overall purpose of the dataset is to provide a better accounting of the gains, losses or fractional solute turnover between sampling stations. Compiled data for the two segments (EAQ to EBC and EBC to PH) are provided in two Excel files, and the same data are provided in csv format in the corresponding zip files.

Life histories of the perennial geophyte Erythronium grandiflorum (Liliaceae) in Colorado subalpine transplant garden from annual measurements, 1991 onward - J. D. Thomson (other, 2020)
In an outdoor garden at Irwin, Colorado, we established glacier lily plants in open-bottomed PVC pots that protected them from gopher attack. The initial cohorts were excavated from field sites as mature corms of unknown age. Later cohorts were grown from seed, so their ages are known. Each spring since 1991, we have noted fruit and flower production. In August, after the aboveground parts have died back, we exhume the plants, wash off the soil, weigh the corms, characterize their morphology, photograph them, and replant them. If a corm splits, we replant the pieces in separate pots. The study is ongoing, with 264 plants in 2019. Main findings through 2020: plants produce 0-4 flowers per year, depending on size; most plants flower each year; death is rare, with many plants having survived the entire study; setting a fruit reduces corm substantially (cost of reproduction); plants appear to regulate weight by adjusting flower production, and by splitting; genotypes vary in splitting propensity. Oddly, mortality is higher in very large corms than in mid-sized ones. Evidence for senescence is scant.

Differential concentration discharge for the upper and lower reaches of the East River Watershed, Colorado (ess_dive, 2020)
This dataset captures the difference in concentration over the difference in discharge across upper and lower reaches of the East River watershed for 2015 and 2016 water years. The East River is part of the Watershed Function Scientific Focus Area (WFSFA) located in the Upper Colorado River Basin, United States. Herein, the upper reach is defined as the segment between EAQ (East Above Quigley) and EBC (East Below Copper), and the lower reach is defined as the segment between EBC and PH (Pump House). The overall purpose of the dataset is to provide a better accounting of the gains, losses or fractional solute turnover between sampling stations. Compiled data for the two segments (EAQ to EBC and EBC to PH) are provided in two Excel files, and the same data are provided in csv format in the corresponding zip files.

Conifer water use patterns in the East River Watershed, Colorado US, based on stable water isotopes and cellulose isotopes (ess_dive, 2020)
This data package contains a series of datasets aimed at understanding the seasonal origins of water used by the dominant conifer species, Abies lasiocarpa and Picea engelmannii, in the East River Watershed. There is a distinct difference in the stable isotopic ratio of summer rain and snowpack and thus by tracking the isotopic ratio of the xylem water in trees, it is possible to separate when a tree is using snow vs. summer rain. Following typical protocols, we sampled and extracted water from soils in the "Research Meadow" near Gothic, CO within the East River Watershed through the 2016 growing season. The stable isotopic ratio of these waters were then measured. Using values of the isotopic ratio of precipitation and snowpack from that season, we develop a mixing model to show how the trees transitioned from use of snowpack to summer in late July. We extended the information on the seasonal origins of water from 2016 back until 1980 by using measurements of the isotopic ratio of cellulose from trees in the Research Meadow. The isotopic ratio of tree ring cellulose records a signal both of the Vapor Pressure Deficit at the leaf-atmosphere boundary and also the source water for the trees. We concluded from this extended analysis that the trees underwent transitions between periods where snow was the dominant water source and summer rain was the dominant water source. More details on this analysis can be found in the publication: Persistence and Plasticity in Conifer Water Use Strategies. JGR Biogeoscience. DOI 10.1029/2018JG004845. The dataset specifically includes stable isotope measurements of xylem and soil water for Spruce and Fir trees at the Rocky Mountain Biological Lab's Research Meadow as well as snowpack and precipitation stable isotopes from nearby National Atmospheric Deposition Program sites. Associated meteorological data is included, which is needed to understand the source water for the trees based on the cellulose measurements. This dataset was updated in June 2021 also include intra-ring measurements of the d18O and d13C of cellulose these same species of trees at the Ziegler Reservoir site in Snowmass, CO. These are listed as files: "Interglaciald18OCellulose.csv", "Interglaciald13OCellulose.csv" and "Modernd13CCellulose.csv". The intent of these measurements was to assess whether common conifers (abies and picea) had undergone ecophysiological or ecohydrological changes during the last period in Earth's history was warmer than today, i.e. the last Interglacial (116,000 to 130,000 years ago). This site was chosen because it is a location where subfossil wood from this critical warm period was discovered. We measured the d18O and d13C of the subfossil trees following the same protocol as the modern samples which included chemical extraction of cellulose and isotope ratio mass spectrometry. We found that the trees showed little difference in water use efficiency but utilized more summer rain during the interglacial period. This analysis and detailed methods are provided in the following manuscript: Wetter summers mitigated temperature stress on Rocky Mountain forests during the last interglacial warm period which is in revision at GRL but is available as a preprint here: 10.1002/essoar.10506740.2

Data from: Lifetime fitness, sex-specific life history, and the maintenance of a polyphenism - Christopher Eden; Nicole Gerlanc; Michael P. Moore; Morgan Geile; A. C. R. Lackey; J. Doyle; Ashley Hagan; H. H. Whiteman (other, 2020)
Polyphenisms, alternative morphs produced through plasticity, can reveal the evolutionary and ecological processes that initiate and maintain diversity within populations. We examined lifetime fitness consequences of two morphs in a polyphenic population of Arizona Tiger Salamanders using a 27-year data set with 1,317 adults and 6,862 captures across eight generations. Larval salamanders develop into either an aquatic paedomorph that retains larval traits and stays in its natal pond or a terrestrial metamorph that undergoes metamorphosis. To evaluate the adaptive significance of this polyphenism, we compared lifetime reproductive success of each morph and assessed how life history strategies and spatiotemporal variation explained fitness. We found sex-specific differences in lifetime fitness between morphs. For males, paedomorphs had more reproductive opportunities than metamorphs when we accounted for the potential mating advantage of larger males. For females, in contrast, metamorphs had higher estimated egg production than paedomorphs. Life history strategies differed between morphs largely because the morphs maximize different ends of the trade-off between age at first reproduction and longevity. Spatiotemporal variation affected larval more than adult life history traits with little to no effect on lifetime fitness. Thus, environmental variation likely explains differences in morph production across time and space but contributes little to lifetime fitness differences between morphs and sexes. Our long-term study and measures of lifetime fitness provide unique insight into the complex selective regimes potentially acting on each morph and sex. Our findings motivate future work to examine how sex-specific selection may contribute to the maintenance of polyphenism.

Hydrologic Model Files (PRMS) for Historical Conditions in the East River Watershed, Colorado between 1987-2019 (ess_dive, 2020)
The data package contains model input and output file for the East River watershed (85 km2) located in the headwaters of the Colorado River. The model is the U.S. Geological Survey (USGS) Precipitation-Modeling Runoff System (PRMS) for the historical, or baseline, condition (1987-2019) to assess the efficiency of summer monsoon rains to generate streamflow. The finite difference grid resolution is 100 m with elevations resampled from the USGS National Elevation Dataset. LANDFIRE raster data is used to derive parameters of dominant cover type, summer and winter cover density, canopy interception characteristics for snow and rain and transmission coefficient for shortwave radiation. Climate forcing uses minimum and maximum daily temperature lapse rates defined by the two Snow Telemetry (SNOTEL) stations located in the vicinity of the East River adjusted for aspect. Schofield SNOTEL snowfall is spatially distributed using LiDAR derived snow depth observations from the Airborne Snow Observatory (ASO) flown 4 April 2016. Snow depths are converted to snow water equivalent based on ground surveys and density modeling. Rainfall is spatially distributed using the monthly Parameter-elevation Relationships on Independent Slopes Model 30-year monthly averages. Simulated solar radiation is calibrated to match weather station observations. Model verification of snow water equivalent (SWE) accumulation and ablation relies on the 2018 and 2019 ASO maps and weather station snow depth. The data package contains model input files in text format, model documentation in pfd and a readme.txt file to help users understand the file structure to run the program.

Conifer water use patterns in the East River Watershed, Colorado US, based on stable water isotopes and cellulose isotopes (ess_dive, 2020)
This data package contains a series of datasets aimed at understanding the seasonal origins of water used by the dominant conifer species, Abies lasiocarpa and Picea engelmannii, in the East River Watershed. There is a distinct difference in the stable isotopic ratio of summer rain and snowpack and thus by tracking the isotopic ratio of the xylem water in trees, it is possible to separate when a tree is using snow vs. summer rain. Following typical protocols, we sampled and extracted water from soils in the "Research Meadow" near Gothic, CO within the East River Watershed through the 2016 growing season. The stable isotopic ratio of these waters were then measured. Using values of the isotopic ratio of precipitation and snowpack from that season, we develop a mixing model to show how the trees transitioned from use of snowpack to summer in late July. We extended the information on the seasonal origins of water from 2016 back until 1980 by using measurements of the isotopic ratio of cellulose from trees in the Research Meadow. The isotopic ratio of tree ring cellulose records a signal both of the Vapor Pressure Deficit at the leaf-atmosphere boundary and also the source water for the trees. We concluded from this extended analysis that the trees underwent transitions between periods where snow was the dominant water source and summer rain was the dominant water source. More details on this analysis can be found in the publication: Persistence and Plasticity in Conifer Water Use Strategies. JGR Biogeoscience. DOI 10.1029/2018JG004845. The dataset specifically includes stable isotope measurements of xylem and soil water for Spruce and Fir trees at the Rocky Mountain Biological Lab's Research Meadow as well as snowpack and precipitation stable isotopes from nearby National Atmospheric Deposition Program sites. Associated meteorological data is included, which is needed to understand the source water for the trees based on the cellulose measurements. This dataset was updated in June 2021 also include intra-ring measurements of the d18O and d13C of cellulose these same species of trees at the Ziegler Reservoir site in Snowmass, CO. These are listed as files: "Interglaciald18OCellulose.csv", "Interglaciald13OCellulose.csv" and "Modernd13CCellulose.csv". The intent of these measurements was to assess whether common conifers (abies and picea) had undergone ecophysiological or ecohydrological changes during the last period in Earth's history was warmer than today, i.e. the last Interglacial (116,000 to 130,000 years ago). This site was chosen because it is a location where subfossil wood from this critical warm period was discovered. We measured the d18O and d13C of the subfossil trees following the same protocol as the modern samples which included chemical extraction of cellulose and isotope ratio mass spectrometry. We found that the trees showed little difference in water use efficiency but utilized more summer rain during the interglacial period. This analysis and detailed methods are provided in the following manuscript: Wetter summers mitigated temperature stress on Rocky Mountain forests during the last interglacial warm period which is in revision at GRL but is available as a preprint here: 10.1002/essoar.10506740.2

Hydrologic Model Files (PRMS) for Historical Conditions in the East River Watershed, Colorado between 1987-2019 (ess_dive, 2020)
The data package contains model input and output file for the East River watershed (85 km2) located in the headwaters of the Colorado River. The model is the U.S. Geological Survey (USGS) Precipitation-Modeling Runoff System (PRMS) for the historical, or baseline, condition (1987-2019) to assess the efficiency of summer monsoon rains to generate streamflow. The finite difference grid resolution is 100 m with elevations resampled from the USGS National Elevation Dataset. LANDFIRE raster data is used to derive parameters of dominant cover type, summer and winter cover density, canopy interception characteristics for snow and rain and transmission coefficient for shortwave radiation. Climate forcing uses minimum and maximum daily temperature lapse rates defined by the two Snow Telemetry (SNOTEL) stations located in the vicinity of the East River adjusted for aspect. Schofield SNOTEL snowfall is spatially distributed using LiDAR derived snow depth observations from the Airborne Snow Observatory (ASO) flown 4 April 2016. Snow depths are converted to snow water equivalent based on ground surveys and density modeling. Rainfall is spatially distributed using the monthly Parameter-elevation Relationships on Independent Slopes Model 30-year monthly averages. Simulated solar radiation is calibrated to match weather station observations. Model verification of snow water equivalent (SWE) accumulation and ablation relies on the 2018 and 2019 ASO maps and weather station snow depth. The data package contains model input files in text format, model documentation in pfd and a readme.txt file to help users understand the file structure to run the program.

Hydrologic Model Files (PRMS) for Historical Conditions in the East River Watershed, Colorado between 1987-2019 (ess_dive, 2020)
The data package contains model input and output file for the East River watershed (85 km2) located in the headwaters of the Colorado River. The model is the U.S. Geological Survey (USGS) Precipitation-Modeling Runoff System (PRMS) for the historical, or baseline, condition (1987-2019) to assess the efficiency of summer monsoon rains to generate streamflow. The finite difference grid resolution is 100 m with elevations resampled from the USGS National Elevation Dataset. LANDFIRE raster data is used to derive parameters of dominant cover type, summer and winter cover density, canopy interception characteristics for snow and rain and transmission coefficient for shortwave radiation. Climate forcing uses minimum and maximum daily temperature lapse rates defined by the two Snow Telemetry (SNOTEL) stations located in the vicinity of the East River adjusted for aspect. Schofield SNOTEL snowfall is spatially distributed using LiDAR derived snow depth observations from the Airborne Snow Observatory (ASO) flown 4 April 2016. Snow depths are converted to snow water equivalent based on ground surveys and density modeling. Rainfall is spatially distributed using the monthly Parameter-elevation Relationships on Independent Slopes Model 30-year monthly averages. Simulated solar radiation is calibrated to match weather station observations. Model verification of snow water equivalent (SWE) accumulation and ablation relies on the 2018 and 2019 ASO maps and weather station snow depth. The data package contains model input files in text format, model documentation in pfd and a readme.txt file to help users understand the file structure to run the program.

Water Level Data from Wells PLM1 and PLM6 for the East River Watershed, Colorado (ess_dive, 2020)
This data set contains water level data for the PLM1 and PLM6 wells. PLM1 and PLM6 are location identifiers used by the Watershed Function SFA project for two groundwater monitoring wells along an elevation gradient located along the lower montane life zone of a hillslope near the Pumphouse location. These wells used to monitor subsurface water and carbon inventories and fluxes at the East River Watershed, Colorado, USA. Complete metadata information on the PLM1 and PLM6 wells are available in the related data package reference Varadharajan C, et al (2020). https://doi.org/10.15485/1660962. Data are reported in .csv files per well. The latitude and longitude of each location are given in a file called locations.csv. These data are used for determining the seasonally dependent flow of groundwater under the PLM hillslope. The downslope flow of groundwater in combination with data on groundwater chemistry can be used to estimate rates of solute export from the hillslope to the floodplain and river. These data products are part of the Watershed Function Scientific Focus Area collection effort to further scientific understanding of biogeochemical dynamics from genome to watershed scales.

Data for: The impacts of bioenergy pine plantation management practices on bee communities - Jamieson Botsch; Holly Ober; E. K. Dobbs; Andriana Miljanic; Lora Smith; Robert Fletcher; Isabel Gottlieb; Brice Lawley; David Gruenewald (other, 2020)
1. Cultivation of bioenergy feedstocks is a growing land-use worldwide, yet we have a poor understanding of how bioenergy crop management practices affect biodiversity. This knowledge gap is particularly acute for candidate cellulosic bioenergy feedstocks, such as tree plantations, and for organisms that provide important ecosystem services, such as pollinators. 2. We examined bee communities in 83 sites across three states in the southeastern USA—Alabama, Florida and Georgia. We compared bee abundance and diversity in 66 pine plantation sites that reflect management with and without potential bioenergy feedstock production. At least three bioenergy feedstock production methods have been proposed for this region: 1) converting conventional timber stands to short-rotation bioenergy plantations; 2) harvesting feedstock by thinning conventional plantations; and 3) harvesting of woody debris residues after plantations have been clear-cut. 3. We found that bioenergy-associated management practices including younger plantations (relative to older) and woody debris removal (relative to debris unremoved) in clear-cut plantations were associated with reduced bee diversity. Removing ground debris in clear-cut plantations also drastically increased bee abundance, though this effect was largely driven by strong dominance of just two bee species. Clear-cut plantations had lower beta diversity than standing plantations. 4. Synthesis and applications. Management practices associated with bioenergy feedstock production can have negative effects on bee community diversity. In particular, harvesting of debris in clear-cut plantations dramatically reduces bee diversity. Large-scale bioenergy feedstock production that increases the prevalence of young and clear-cut stands may cause landscape-level beta diversity to decline. Nevertheless, bioenergy pine plantations likely support higher bee diversity than corn fields, an alternative bioenergy feedstock.

bblonder/flir_thermal_control: Initial release - B. Blonder (other, 2020)
Initial release

Post survey report for AOP Assignable Asset collection of Crested Butte, CO (ess_dive, 2020)
This report contains details of the National Ecological Observatory Network Airborne Observation Platform (NEON AOP) assignable asset (AA) flight over Crested Butte, Colorado (CO). The report is being prepared for Lawrence Berkeley National Lab (LBNL), the primary clients for the flights who contracted the NEON AOP for flights during June 2018. The report includes a summary of the acquired flight lines over the planned area, results of calibration surveys, and quality assurance (QA) results of the acquired data. Detailed reports on the acquired data and processing results were also delivered with the data. LBNL contracted the AA NEON AOP flights to observe watersheds of interest at Crested Butte with remotely sensed data including high resolution LiDAR, imaging spectroscopy, and high-resolution camera imagery. The remote sensing imagery acquired by the AOP intendeds to support LBNL on an interdisciplinary project on hydrology, biogeochemistry, and ecosystem functioning in the area surrounding the Rocky Mountain Biological Laboratory (RMBL), one of the most prominent ecological study sites in the United States.

bblonder/thermal_analysis: Initial release - B. Blonder (other, 2020)
Initial release

Quality-controlled Vegetation Canopy Height Model for the Upper East River Domain - Ian K Breckheimer (s3, 2020)
This is a vegetation canopy height map from the 2018 NEON AOP dataset. It was derived from the NEON Lidar-based digital surface model and the re-processed SDP NEON DEM. Pixels with low NDVI or inside building footprints were set to a value of zero.

Conifer water use patterns in the East River Watershed, Colorado US, based on stable water isotopes and cellulose isotopes. Space and Time Dynamics of Transpiration in the East River Watershed: Biotic and Abiotic Controls (ess_dive, 2020)
This data package contains a series of datasets aimed at understanding the seasonal origins of water used by the dominant conifer species, Abies lasiocarpa and Picea engelmannii, in the East River Watershed. There is a distinct difference in the stable isotopic ratio of summer rain and snowpack and thus by tracking the isotopic ratio of the xylem water in trees, it is possible to separate when a tree is using snow vs. summer rain. Following typical protocols, we sampled and extracted water from soils in the "Research Meadow" near Gothic, CO within the East River Watershed through the 2016 growing season. The stable isotopic ratio of these waters were then measured. Using values of the isotopic ratio of precipitation and snowpack from that season, we develop a mixing model to show how the trees transitioned from use of snowpack to summer in late July. We extended the information on the seasonal origins of water from 2016 back until 1980 by using measurements of the isotopic ratio of cellulose from trees in the Research Meadow. The isotopic ratio of tree ring cellulose records a signal both of the Vapor Pressure Deficit at the leaf-atmosphere boundary and also the source water for the trees. We concluded from this extended analysis that the trees underwent transitions between periods where snow was the dominant water source and summer rain was the dominant water source. More details on this analysis can be found in the publication: Persistence and Plasticity in Conifer Water Use Strategies. JGR Biogeoscience. DOI 10.1029/2018JG004845. The dataset specifically includes stable isotope measurements of xylem and soil water for Spruce and Fir trees at the Rocky Mountain Biological Lab's Research Meadow as well as snowpack and precipitation stable isotopes from nearby National Atmospheric Deposition Program sites. The dataset also includes intra-ring measurements of the d18O of cellulose from these trees at this site as well as at the Ziegler Reservoir site in Snowmass, CO. Associated meteorological data is included, which is needed to understand the source water for the trees based on the cellulose measurements.

Social Behavior and Population Dynamics of Yellow-bellied Marmots 1965 and Continuing after 2001. - Daniel T. Blumstein (other, 2020)
These data continue and expand upon data collected by Kenneth B. Armitage titled, " Social Behavior and Population Dynamics of Yellow-bellied Marmots", that goes from 1965 - 2001. A record includes the subject's age, sex, body mass, locality, and reproductive status. Starting in 2002, additional columns are added that include: the subject's reaction to being trapped and tagged, and a list of samples that were collected (blood, feces, hair, alarm call recordings).   To access data from 2002, please contact Daniel Blumstein (marmots@ucla.edu).

Sub-Basin Delineation for the Upper East River, Colorado, United States (ess_dive, 2020)
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).

A global database of plant production and carbon exchange from global change manipulative experiments - Jian Song; Shiqiang Wan (other, 2020)
1. Database used in the article entitled "A meta-analysis of 1,119 manipulative experiments on terrestrial carbon-cycling responses to global change", which is published in Nature Ecology & Evolution. 2. A updated version of the original dataset used in our Nature Ecology & Evolution paper.

LiDAR collection in August 2015 over the East River Watershed, Colorado, USA - Haruko M. Wainwright; K. H. Williams (ess_dive, 2020)
Airborne LiDAR data were acquired over the East River Watershed on June 8, 2015 to August 10, 2015. The area covered was approximately 4933 square kilometers with an average point density of 10-12 points per square meter to comply with USGS's QL1 standard. Additional products include the LiDAR point cloud and derived products (including the digital elevation map, top-of-canopy elevation). The attached LIDAR acquisition report accompanies the delivered LiDAR data and documents contract specifications, data acquisition procedures, acquisition parameters (e.g., flight line trajectories, coverage maps), processing methods, and analysis of the final dataset including LiDAR accuracy and density. The metadata can be accessed by using GIS software (QGIS, ArcGIS) or remote sensing software (ENVI).

Data for Context-dependent biotic interactions control plant abundance across altitudinal environmental gradients, 2014, 2016, Colorado, USA - Melanie R Kazenel; Jennifer A. Rudgers; Stephanie N. Kivlin; J. S. Lynn (other, 2020)
Many biotic interactions influence community structure, yet most distribution models for plants have focused on plant competition or used only abiotic variables to predict plant abundance. Furthermore, biotic interactions are commonly context-dependent across abiotic gradients. For example, plant-plant interactions can grade from competition to facilitation over temperature gradients. We used a hierarchical Bayesian framework to predict the abundances of 12 plant species across a mountain landscape and test hypotheses on the context-dependency of biotic interactions over abiotic gradients. We combined field-based estimates of six biotic interactions (foliar herbivory and pathogen damage, fungal root colonization, fossorial mammal disturbance, plant cover, and plant diversity) with abiotic data on climate and soil depth, nutrients, and moisture. All biotic interactions were significantly context-dependent along temperature gradients. Results supported the stress gradient hypothesis: As abiotic stress increased, the strength or direction of the relationship between biotic variables and plant abundance generally switched from negative (suggesting suppressed plant abundance) to positive (suggesting facilitation/mutualism). For half of the species, plant cover was the best predictor of abundance, suggesting that the prior focus on plant-plant interactions is well-justified. Explicitly incorporating the context-dependency of biotic interactions generated novel hypotheses about drivers of plant abundance across abiotic gradients and may improve the accuracy of niche models.

Conifer water use patterns in the East River Watershed, Colorado US, based on stable water isotopes and cellulose isotopes - Ioana Stefanescu; Francois Ritter; Nadja Insel; L. Anderson; C. Still; Ioana Stefanescu; Francois Ritter; Max Berkelhammer; L. Anderson; C. Still; Nadja Insel; M. J. Winnick; et al. (ess_dive, 2020)
This data package contains a series of datasets aimed at understanding the seasonal origins of water used by the dominant conifer species, Abies lasiocarpa and Picea engelmannii, in the East River Watershed. There is a distinct difference in the stable isotopic ratio of summer rain and snowpack and thus by tracking the isotopic ratio of the xylem water in trees, it is possible to separate when a tree is using snow vs. summer rain. Following typical protocols, we sampled and extracted water from soils in the "Research Meadow" near Gothic, CO within the East River Watershed through the 2016 growing season. The stable isotopic ratio of these waters were then measured. Using values of the isotopic ratio of precipitation and snowpack from that season, we develop a mixing model to show how the trees transitioned from use of snowpack to summer in late July. We extended the information on the seasonal origins of water from 2016 back until 1980 by using measurements of the isotopic ratio of cellulose from trees in the Research Meadow. The isotopic ratio of tree ring cellulose records a signal both of the Vapor Pressure Deficit at the leaf-atmosphere boundary and also the source water for the trees. We concluded from this extended analysis that the trees underwent transitions between periods where snow was the dominant water source and summer rain was the dominant water source. More details on this analysis can be found in the publication: Persistence and Plasticity in Conifer Water Use Strategies. JGR Biogeoscience. DOI 10.1029/2018JG004845. The dataset specifically includes stable isotope measurements of xylem and soil water for Spruce and Fir trees at the Rocky Mountain Biological Lab's Research Meadow as well as snowpack and precipitation stable isotopes from nearby National Atmospheric Deposition Program sites. The dataset also includes intra-ring measurements of the d18O of cellulose from these trees at this site as well as at the Ziegler Reservoir site in Snowmass, CO. Associated meteorological data is included, which is needed to understand the source water for the trees based on the cellulose measurements.

Hydrologic Model Files (PRMS) for Historical Conditions in the East River Watershed, Colorado between 1987-2019 - David Gochis; David Gochis; David Gochis; David Gochis; K. H. Williams; K. H. Williams; K. H. Williams; K. H. Williams (ess_dive, 2020)
The data package contains model input and output file for the East River watershed (85 km2) located in the headwaters of the Colorado River. The model is the U.S. Geological Survey (USGS) Precipitation-Modeling Runoff System (PRMS) for the historical, or baseline, condition (1987-2019) to assess the efficiency of summer monsoon rains to generate streamflow. The finite difference grid resolution is 100 m with elevations resampled from the USGS National Elevation Dataset. LANDFIRE raster data is used to derive parameters of dominant cover type, summer and winter cover density, canopy interception characteristics for snow and rain and transmission coefficient for shortwave radiation. Climate forcing uses minimum and maximum daily temperature lapse rates defined by the two Snow Telemetry (SNOTEL) stations located in the vicinity of the East River adjusted for aspect. Schofield SNOTEL snowfall is spatially distributed using LiDAR derived snow depth observations from the Airborne Snow Observatory (ASO) flown 4 April 2016. Snow depths are converted to snow water equivalent based on ground surveys and density modeling. Rainfall is spatially distributed using the monthly Parameter-elevation Relationships on Independent Slopes Model 30-year monthly averages. Simulated solar radiation is calibrated to match weather station observations. Model verification of snow water equivalent (SWE) accumulation and ablation relies on the 2018 and 2019 ASO maps and weather station snow depth. The data package contains model input files in text format, model documentation in pfd and a readme.txt file to help users understand the file structure to run the program.

Plant census and microenvironment dataset from Mt. Baldy, Colorado, USA, 2014-2017 - Bente J. Graae; R. M. Dalton; B. Blonder; Jacob M. Heiling (other, 2020)
The data comprise a long-term study of alpine plant community dynamics in the Gunnison National Forest of Colorado. The data comprise annual census data for all plants (including seedlings) in each of 50 2x2m plots, including information on size, reproduction, life stage, and mortality, with all plants identified and geo-located. These data are also made available transformed to provide individual-level estimates of growth, survival, fecundity, and recruitment. The dataset covers several thousand individuals of approximately twenty species, and highlights an apparent pattern of demographic decline. The data also include information on microenvironment / microedaphic variation at 2 m resolution covering the entire research site, including information on temperatures, topography, soil chemistry, soil texture, and other variables. The data also include information on the functional traits of many of the species present at the site, including information on biomass allocation, leaf traits, root traits, seed traits, and floral traits.

Estimating densities of larval Salmonflies (Pteronarcys californica) through multiple pass removal of post-emergent exuvia in Colorado rivers - Dan Kowalski (other, 2020)
Traditional methods of collecting, sorting, and identifying benthic macroinvertebrate samples are useful for stream biomonitoring and ecological studies, however, these methods are time consuming, expensive, and require taxonomic expertise. Estimating larval densities through collection of post-emergent exuvia can be a practical and time efficient alternative. We evaluated the use of multiple pass depletion techniques of the post-emergent exuvia of Pteronarcys californica to estimate larval densities at ten sites in three Colorado rivers. Exuvia density was highly correlated with both final-instar larval density (R2 = 0.90) and total larval density (R2 = 0.88) and the multiple pass removal technique performed well. Exuvia surveys found P. californica at three low density sites where benthic sampling failed to detect it. At moderate and high density sites the exuvia surveys always produced lower density estimates than benthic surveys. Multiple pass depletion estimates of exuvia proved to be an accurate and efficient technique at estimating larval densities and provided an effective alternative for traditional benthic sampling when objectives are detecting and monitoring P. californica, especially at low density sites.

Cross-Section Geometry and Sediment-Size Data from Muddy Creek and North Fork Gunnison River below Paonia Reservoir, western Colorado, 2019 - Rodney J Richards; Mark F Henneberg (other, 2020)
This dataset contains cross-section geometry and sediment-size data collected in the fall of 2019 from Muddy Creek and North Fork Gunnison River below Paonia Reservoir, western Colorado. Six cross sections were surveyed using Real-Time Kinematic Global Navigation Satellite System (RTK-GNSS) methods to document channel geometry below Paonia Reservoir. One cross section was surveyed on Muddy Creek below Paonia Reservoir, and five cross sections were surveyed from North Fork Gunnison River below Paonia Reservoir. All six cross sections are incorporated in this data release within one shapefile. Pebble counts were performed at each of the six cross sections to document sediment-size distributions downstream from the reservoir. Four transects were completed at each cross section, where sediment size was measured and recorded. Sediment-size data are presented in .CSV files, with one file for each cross-section location, incorporating all of the data for each of the four transects at that location.

Multi-direction Stream Flowlines for the Upper East River Domain - Ian K Breckheimer (s3, 2020)
This map represents estimated stream flowlines from a hydrologically corrected digital elevation model. The lines were derived in the GRASS GIS module r.watershed using a multi-flow direction algorithm that allows channel braiding. Each stream segment is identified by a unique integer.

Multi-direction Flow Accumulation for the Upper East River Domain - Ian K Breckheimer (s3, 2020)
This dataset represents estimated flow accumulation from a hydrologically corrected digital elevation model. The map was derived in GRASS GIS using a multi-flow direction algorithm that allows channel braiding. Values represent the area (in square meters) of land that contributes flow to a given cell.

The Importance of Interflow to Groundwater Recharge in a Snowmelt-Dominated, Alpine Watershed, Geophysical Research Letters: Modeling and Data Package (ess_dive, 2020)
This data package contains hydrologic modeling input and output files for the East River (ER_PRMS.zip) and Copper Creek (CC_GSFLOW.zip) for water years 1987 to 2018. These data were used to generate simulated results published in Geophysical Research Letters (Carroll et al., 2019) describing the importance of interflow in generating groundwater recharge in the upper subalpine. The East River and Copper Creek are part of the Watershed Function Scientific Focus Area (WFSFA) located in the Upper Colorado River Basin, United States. The hydrologic model uses the U.S. Geological Survey coupled groundwater and surface water flow model (GSFLOW). Input and output files are askii format, while the model executable (gsflow.exe), source code, example problems and documentation describing model files is provided at the following U.S. Geological Survey website. https://www.usgs.gov/software/coupled-ground-water-and-surface-water-flow-model-gsflow. GSFLOW executables are compiled for either Microsoft Windows or Linux operating systems.

Basic High-resolution Landcover Map for the Upper East River Domain - Ian K Breckheimer (s3, 2020)
This is a landcover map derived from the 2018 NEON AOP dataset for the upper east river. 1=needle-leaf trees and shrubs 2=deciduous trees and shrubs 3=deciduous meadow and subshrub (<0.5m) 4=bare rock, soil, gravel and asphalt 5=water 6=snow 7=buildings Source data includes NEON LiDAR and imaging spectrometry products described in: 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 Chadwick K D ; Brodrick P ; Grant K ; Henderson A ; Bill M ; Breckheimer I ; Williams C F R ; Goulden T ; Falco N ; McCormick M ; Musinsky J ; Pierce S ; Hastings Porro M ; Scott A ; Brodie E ; Hancher M ; Steltzer H ; Wainwright H ; Maher K W; undefined K M (2020): NEON AOP foliar trait maps, maps of model uncertainty estimates, and conifer map. A Multiscale Approach to Modeling Carbon and Nitrogen Cycling within a High Elevation Watershed. DOI: 10.15485/1618133

Large Sub-watersheds of the Upper East River Domain - Ian K Breckheimer (s3, 2020)
This map represents estimated watersheds for stream segments derived from a hydrologically corrected digital elevation model. The flow lines were derived in GRASS GIS using a single direction algorithm that does not allow channel braiding. Each watershed is identified by a unique integer that matches the stream segment. Stream segments were delineated to drain at least 512000 square meters. Users should also cite the original elevation datasets and documentation: 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

Single-direction Major Streams for the Upper East River Domain - Ian K Breckheimer (s3, 2020)
This map represents estimated stream flowlines from a hydrologically corrected digital elevation model. The lines were derived in GRASS GIS using a single flow-direction (D8) algorithm that does not allow channel braiding. Each stream segment is identified by a unique integer. Stream lines were delineated for drainage areas greater than 512000 square meters. Users should also cite the original elevation datasets and documentation: 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

Single-direction Flow Accumulation Map for the Upper East River Domain - Ian K Breckheimer (s3, 2020)
This map represents estimated flow accumulation from a hydrologically corrected digital elevation model. The map was derived in GRASS GIS using a single flow-direction (D8) algorithm that does not allow channel braiding. Values represent the area (in square meters) of land that contributes flow to a given cell. This dataset was generated with the r.watershed module of GRASS GIS 7.8.2. Users should also cite the original source datasets and documentation: 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 Chadwick K D ; Brodrick P ; Grant K ; Henderson A ; Bill M ; Breckheimer I ; Williams C F R ; Goulden T ; Falco N ; McCormick M ; Musinsky J ; Pierce S ; Hastings Porro M ; Scott A ; Brodie E ; Hancher M ; Steltzer H ; Wainwright H ; Maher K W; undefined K M (2020): NEON AOP foliar trait maps, maps of model uncertainty estimates, and conifer map. A Multiscale Approach to Modeling Carbon and Nitrogen Cycling within a High Elevation Watershed. DOI: 10.15485/1618133

Surface Water Map at 1m Resolution for the Upper East River Domain - Ian K Breckheimer (s3, 2020)
This map represents the estimated binary presence of surface water during the NEON Airborne Observation Platform campaign in July 2018. Values of 1 represent open water, values of 0 represent no water present. Surface water was mapped using imaging spectrometer data from the AOP, and combined with a flow accumulation map to provide continuous water bodies for streams with drainage areas larger than 3x10^6 square meters.

Hydrologically Corrected (cut) 1m Digital Elevation Model for the Upper East River Domain - Ian K Breckheimer (s3, 2020)
This is a hydrologically corrected digital elevation model derived from the 2018 NEON AOP dataset. It represents the height above sea level for impervious objects attached to the ground, such as buildings, but not vegetation. Bridges and culverts have been "cut" to allow realistic surface flow for hydrologic applications. Users should also cite the original source datasets and documentation: 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 Chadwick K D ; Brodrick P ; Grant K ; Henderson A ; Bill M ; Breckheimer I ; Williams C F R ; Goulden T ; Falco N ; McCormick M ; Musinsky J ; Pierce S ; Hastings Porro M ; Scott A ; Brodie E ; Hancher M ; Steltzer H ; Wainwright H ; Maher K W; undefined K M (2020): NEON AOP foliar trait maps, maps of model uncertainty estimates, and conifer map. A Multiscale Approach to Modeling Carbon and Nitrogen Cycling within a High Elevation Watershed. DOI: 10.15485/1618133

Leaf-off 1m Digital Surface Model of the Upper East River Domain - Ian K Breckheimer (s3, 2020)
This is a digital surface model from the 2018 NEON AOP dataset. It represents the height above sea level for objects attached to the ground, such as buildings. This version of the data includes the elevation of buildings and other non-vegetation objects such as bridges. Areas of deciduous vegetation reflect bare-earth elevations. Areas of evergreen vegetation represent elevations of vegetation tops. Users should also cite the original source datasets and documentation: 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 Chadwick K D ; Brodrick P ; Grant K ; Henderson A ; Bill M ; Breckheimer I ; Williams C F R ; Goulden T ; Falco N ; McCormick M ; Musinsky J ; Pierce S ; Hastings Porro M ; Scott A ; Brodie E ; Hancher M ; Steltzer H ; Wainwright H ; Maher K W; undefined K M (2020): NEON AOP foliar trait maps, maps of model uncertainty estimates, and conifer map. A Multiscale Approach to Modeling Carbon and Nitrogen Cycling within a High Elevation Watershed. DOI: 10.15485/1618133

1m Digital Elevation Model with Buildings Derived from the 2018 NEON AOP Dataset - Ian K Breckheimer (s3, 2020)
This is a digital surface model from the 2018 NEON AOP dataset. It represents the height above sea level for objects attached to the ground, such as buildings. This version of the data includes the elevation of buildings and other non-vegetation objects such as bridges, but areas of vegetation reflect bare-earth elevations. 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 Chadwick K D ; Brodrick P ; Grant K ; Henderson A ; Bill M ; Breckheimer I ; Williams C F R ; Goulden T ; Falco N ; McCormick M ; Musinsky J ; Pierce S ; Hastings Porro M ; Scott A ; Brodie E ; Hancher M ; Steltzer H ; Wainwright H ; Maher K W; undefined K M (2020): NEON AOP foliar trait maps, maps of model uncertainty estimates, and conifer map. A Multiscale Approach to Modeling Carbon and Nitrogen Cycling within a High Elevation Watershed. DOI: 10.15485/1618133

Quality-controlled and Gap-filled 1m Digital Elevation Model for the Upper East River Domain - Ian K Breckheimer (s3, 2020)
This is a bare-earth digital elevation model from the 2018 NEON AOP dataset. Areas outside the boundaries of the Upper East River domain were filled with data interpolated from the 3m 2018 Airborne Snow Observatory DEM. The ASO DEM was harmonized with the NEON DEM and filtered to remove small pits and peaks.

Multi-direction Major Streams for the Upper East River Domain - Ian K Breckheimer (s3, 2020)
This map represents estimated stream flowlines from a hydrologically corrected digital elevation model. The lines were derived in GRASS GIS using a multi-direction algorithm that allows channel braiding. Each stream segment is identified by a unique integer. Stream lines were delineated for drainage areas greater than 512000 square meters. Users should also cite the original elevation datasets and documentation: 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 Chadwick K D ; Brodrick P ; Grant K ; Henderson A ; Bill M ; Breckheimer I ; Williams C F R ; Goulden T ; Falco N ; McCormick M ; Musinsky J ; Pierce S ; Hastings Porro M ; Scott A ; Brodie E ; Hancher M ; Steltzer H ; Wainwright H ; Maher K W; undefined K M (2020): NEON AOP foliar trait maps, maps of model uncertainty estimates, and conifer map. A Multiscale Approach to Modeling Carbon and Nitrogen Cycling within a High Elevation Watershed. DOI: 10.15485/1618133

Ute Ulay Mining Complex and Henson Ghost Town - oc534 (other, 2020)
The Ute Ulay Mining Complex is located along the Alpine Loop Scenic Byway just south of Lake City, Colorado. The Ute Ulay mining claims were discovered in 1871 and were one of the biggest producers of gold and silver in the San Juan Mountains. The Bureau of Land Management Gunnison Field Office has partnered with Hinsdale County to promote heritage tourism and has stabilized and preserved several structures within the mining complex. Ute Ulay was listed on the National Register of Historic Places in 2017. The mining town of Henson sprung up in 1880 and provided basic necessities to support the 300 miners and their families working at the booming Ute Ulay Mining Complex. By 1883, the town had a schoolhouse, post office, several supply stores, and its dirt roads were lined with one room log cabins. Many of these structures are still standing today and an interpreted historic walking tour through the ghost town is available. Source: Objaverse 1.0 / Sketchfab

Ute Ulay Water Tank - oc534 (other, 2020)
The Ute Ulay Mining Complex is located along the Alpine Loop Scenic Byway just south of Lake City, Colorado. The Ute Ulay mining claims were discovered in 1871 and were one of the biggest producers of gold and silver in the San Juan Mountains. The Bureau of Land Management Gunnison Field Office has partnered with Hinsdale County to promote heritage tourism and has stabilized and preserved several structures within the mining complex. Ute Ulay was listed on the National Register of Historic Places in 2017. The wooden water tank was filled by the flume from the Ute Ulay Dam. The water tank supplied water to the hydropower plant through three vertical pipes to three Leffel turbine water wheels that powered the electrical generating equipment in the power plant. The water tank was constructed in 1926 along with the dam, flume, and hydropower plant. Source: Objaverse 1.0 / Sketchfab

RMBL NHD Lakes - Shannon Sprott (other, 2020)
The National Hydrography Dataset (NHD) represents the water drainage network of the United States with features such as rivers, streams, canals, lakes, ponds, coastline, dams, and stream gages. This data was downloaded directly from the usgs.gov National Map downloader site. The data was then clipped to Gunnison County boundary by RMBL GIS. The most current version of the National Hydrography Dataset, the NHD High Resolution, is mapped at a scale of 1:24,000 scale or better (1:63,360 or better in Alaska). The download link goes to the shapefile data format, though this data is available for download off the ArcGIS Online site as a KML, File Geodatabase, and GeoJson file types.

RMBL County Town Boundaries - Shannon Sprott (other, 2020)
These are the platted and recorded designated city and town boundaries within Gunnison County. This  dataset was downloaded directly from the Gunnison County GIS website and was updated on 09/10/2019. The data download link goes to the shapefile data format, though this data is available for download off the ArcGIS Online site as a KML, File Geodatabase, and GeoJson file types.

The Importance of Interflow to Groundwater Recharge in a Snowmelt-Dominated, Alpine Watershed, Geophysical Research Letters: Modeling and Data Package (ess_dive, 2020)
This data package contains hydrologic modeling input and output files for the East River (ER_PRMS.zip) and Copper Creek (CC_GSFLOW.zip) for water years 1987 to 2018. These data were used to generate simulated results published in Geophysical Research Letters (Carroll et al., 2019) describing the importance of interflow in generating groundwater recharge in the upper subalpine. The East River and Copper Creek are part of the Watershed Function Scientific Focus Area (WFSFA) located in the Upper Colorado River Basin, United States. The hydrologic model uses the U.S. Geological Survey coupled groundwater and surface water flow model (GSFLOW). Input and output files are askii format, while the model executable (gsflow.exe), source code, example problems and documentation describing model files is provided at the following U.S. Geological Survey website. https://www.usgs.gov/software/coupled-ground-water-and-surface-water-flow-model-gsflow. GSFLOW executables are compiled for either Microsoft Windows or Linux operating systems.

Post survey report for AOP Assignable Asset collection of Crested Butte, CO (ess_dive, 2020)
This report contains details of the National Ecological Observatory Network Airborne Observation Platform (NEON AOP) assignable asset (AA) flight over Crested Butte, Colorado (CO). The report is being prepared for Lawrence Berkeley National Lab (LBNL), the primary clients for the flights who contracted the NEON AOP for flights during June 2018. The report includes a summary of the acquired flight lines over the planned area, results of calibration surveys, and quality assurance (QA) results of the acquired data. Detailed reports on the acquired data and processing results were also delivered with the data. LBNL contracted the AA NEON AOP flights to observe watersheds of interest at Crested Butte with remotely sensed data including high resolution LiDAR, imaging spectroscopy, and high-resolution camera imagery. The remote sensing imagery acquired by the AOP intendeds to support LBNL on an interdisciplinary project on hydrology, biogeochemistry, and ecosystem functioning in the area surrounding the Rocky Mountain Biological Laboratory (RMBL), one of the most prominent ecological study sites in the United States.

Hydrologic Model Files (PRMS) for Historical Conditions in the East River Watershed, Colorado between 1987-2019 (ess_dive, 2020)
The data package contains model input and output file for the East River watershed (85 km2) located in the headwaters of the Colorado River. The model is the U.S. Geological Survey (USGS) Precipitation-Modeling Runoff System (PRMS) for the historical, or baseline, condition (1987-2019) to assess the efficiency of summer monsoon rains to generate streamflow. The finite difference grid resolution is 100 m with elevations resampled from the USGS National Elevation Dataset. LANDFIRE raster data is used to derive parameters of dominant cover type, summer and winter cover density, canopy interception characteristics for snow and rain and transmission coefficient for shortwave radiation. Climate forcing uses minimum and maximum daily temperature lapse rates defined by the two Snow Telemetry (SNOTEL) stations located in the vicinity of the East River adjusted for aspect. Schofield SNOTEL snowfall is spatially distributed using LiDAR derived snow depth observations from the Airborne Snow Observatory (ASO) flown 4 April 2016. Snow depths are converted to snow water equivalent based on ground surveys and density modeling. Rainfall is spatially distributed using the monthly Parameter-elevation Relationships on Independent Slopes Model 30-year monthly averages. Simulated solar radiation is calibrated to match weather station observations. Model verification of snow water equivalent (SWE) accumulation and ablation relies on the 2018 and 2019 ASO maps and weather station snow depth. The data package contains model input files in text format, model documentation in pfd and a readme.txt file to help users understand the file structure to run the program.

Hybrid predictive modeling approach simulated evapotranspiration and ecosystem respiration data (ess_dive, 2020)
This dataset includes measured data used for developing hybrid-predictive-modeling (HPM) approach and simulated evapotranspiration and ecosystem respiration data across several Fluxnet sites, SNOTEL sites and East River locations (Chen et al., 2020 in review). Fluxnet sites considered in this study include: CA-OAS, CA-OBS, US-NR1, US-TON, US-VAR, US-SRM, US-WHS, US-WKG. Snotel sites Butte (ER-BT), Porphyry Creek (ER-PK) and Schofield Pass (ER-SP) are included as well 16 east river locations with different vegetation types denoted by evergreen forests (EF), deciduous forests (DF), riparian shrublands (RS) and meadow grassland (MS). This data package includes: 1) A summary spread sheet of the sites and acronyms for data variables. 2) Processed Fluxnet datasets that are obtained from Fluxnet.fluxdata.org with HPM estimated evapotranspiration (ET) and ecosystem respiration (RECO). Trained models and metrics for parameters for the Fluxnet sites were added in an update on November 2, 2020; 3) Processed SNOTEL datasets obtained from www.nrcs.usda.gov/snow/ and HPM estimated ET and RECO; 4) Weather data at east river locations obtained from DAYMET (daymet.ornl.gov) as well as HPM estimated ET and RECO. NDVI datasets are obtained from Landsat 5, 7 and 8 on Google Earth Engine platform. Detailed QA/QC and sampling methods of measured data are available at the original data source.

Post survey report for AOP Assignable Asset collection of Crested Butte, CO - John Musinsky; John Musinsky; John Musinsky; John Musinsky; Tristan Goulden; John Musinsky; Tristan Goulden; John Musinsky; Tristan Goulden; Tristan Goulden; Tristan Goulden; Tristan Goulden (ess_dive, 2020)
This report contains details of the National Ecological Observatory Network Airborne Observation Platform (NEON AOP) assignable asset (AA) flight over Crested Butte, Colorado (CO). The report is being prepared for Lawrence Berkeley National Lab (LBNL), the primary clients for the flights who contracted the NEON AOP for flights during June 2018. The report includes a summary of the acquired flight lines over the planned area, results of calibration surveys, and quality assurance (QA) results of the acquired data. Detailed reports on the acquired data and processing results were also delivered with the data. LBNL contracted the AA NEON AOP flights to observe watersheds of interest at Crested Butte with remotely sensed data including high resolution LiDAR, imaging spectroscopy, and high-resolution camera imagery. The remote sensing imagery acquired by the AOP intendeds to support LBNL on an interdisciplinary project on hydrology, biogeochemistry, and ecosystem functioning in the area surrounding the Rocky Mountain Biological Laboratory (RMBL), one of the most prominent ecological study sites in the United States.

Conifer water use patterns in the East River Watershed, Colorado US, based on stable water isotopes and cellulose isotopes (ess_dive, 2020)
This data package contains a series of datasets aimed at understanding the seasonal origins of water used by the dominant conifer species, Abies lasiocarpa and Picea engelmannii, in the East River Watershed. There is a distinct difference in the stable isotopic ratio of summer rain and snowpack and thus by tracking the isotopic ratio of the xylem water in trees, it is possible to separate when a tree is using snow vs. summer rain. Following typical protocols, we sampled and extracted water from soils in the "Research Meadow" near Gothic, CO within the East River Watershed through the 2016 growing season. The stable isotopic ratio of these waters were then measured. Using values of the isotopic ratio of precipitation and snowpack from that season, we develop a mixing model to show how the trees transitioned from use of snowpack to summer in late July. We extended the information on the seasonal origins of water from 2016 back until 1980 by using measurements of the isotopic ratio of cellulose from trees in the Research Meadow. The isotopic ratio of tree ring cellulose records a signal both of the Vapor Pressure Deficit at the leaf-atmosphere boundary and also the source water for the trees. We concluded from this extended analysis that the trees underwent transitions between periods where snow was the dominant water source and summer rain was the dominant water source. More details on this analysis can be found in the publication: Persistence and Plasticity in Conifer Water Use Strategies. JGR Biogeoscience. DOI 10.1029/2018JG004845. The dataset specifically includes stable isotope measurements of xylem and soil water for Spruce and Fir trees at the Rocky Mountain Biological Lab's Research Meadow as well as snowpack and precipitation stable isotopes from nearby National Atmospheric Deposition Program sites. The dataset also includes intra-ring measurements of the d18O of cellulose from these trees at this site as well as at the Ziegler Reservoir site in Snowmass, CO. Associated meteorological data is included, which is needed to understand the source water for the trees based on the cellulose measurements.

Ice Nucleating Particles (INP) (2020)
Ice Nucleating Particles (INP)

RMBL NHD Streams - Shannon Sprott (other, 2020)
The National Hydrography Dataset (NHD) represents the water drainage network of the United States with features such as rivers, streams, canals, lakes, ponds, coastline, dams, and stream gages. This data was downloaded directly from the usgs.gov National Map downloader site. The data was then clipped to Gunnison County boundary by RMBL GIS. The most current version of the National Hydrography Dataset, the NHD High Resolution, is mapped at a scale of 1:24,000 scale or better (1:63,360 or better in Alaska). The download link goes to the shapefile data format, though this data is available for download off the ArcGIS Online site as a KML, File Geodatabase, and GeoJson file types.

RMBL Gothic RNA - Shannon Sprott (other, 2020)
This is the designated Gothic Research Natural Area boundary that was acquired from the USFS in 2015. The data download link goes to the shapefile data format, though this data is available for download off the ArcGIS Online site as a KML, File Geodatabase, and GeoJson file types.

Database for the Geologic Map of the Bonanza Caldera Area, Northeastern San Juan Mountains, Colorado (other, 2020)
The San Juan Mountains in southwestern Colorado have long been recognized as a site of exceptionally voluminous mid-Tertiary volcanism, including at least 24 major ignimbrite sheets (each 150-5,000 km3) and associated caldera structures active at 33-23 Ma. More recent volcanologic and petrologic studies in the San Juan region have focused mainly on several ignimbrite-caldera systems: the southeastern area (Platoro complex), western calderas (Uncompahgre-Silverton-Lake City), the central cluster (La Garita-Creede calderas). The northeast San Juan region that was far less studied until recently occupies a transition between earlier volcanism in central Colorado and the larger-volume younger ignimbrite-caldera foci farther south and west. The present study of the Bonanza area evaluates eruptive and magmatic processes of silicic Cordilleran volcanism in this northeast region, based on new geologic mapping (mainly summers of 2007-12) and concurrent petrologic and geochronologic analysis. The resulting map is based on new field mapping of volcanic rocks in thirteen 7.5-minute quadrangles in northeastern parts of the volcanic field, petrologic studies involving several hundred new chemical analyses, and high-resolution age determinations for about 130 sites. The Bonanza center contains exceptionally complete and diverse features of an ignimbrite caldera cycle, including voluminous andesite erupted before and after ignimbrite eruptions, complex compositional zonation within both the outflow ignimbrite sheet and the tuff concurrently ponded within the caldera, extensive portions of the ring-fault system that accommodated subsidence, thick compositionally diverse lavas that filled the caldera after subsidence, remnants of the original topographic caldera rim, widespread erosional exposure of caldera-floor features, and postcaldera granitic intrusions that generated a notably steep resurgent dome within the caldera. This geologic map database is accompanied by a report, which includes the formatted geologic map and explanatory pamphlet, available at https://doi.org/10.3133/sim3394. The authors ask that users of the geologic map database cite both the database and the report: Report: Lipman, P.W., 2020, Geologic map of the Bonanza Caldera Area, northeastern San Juan Mountains, Colorado: U.S. Geological Survey Scientific Investigations Map 3394, pamphlet 73 p., 2 sheets, scale 1:50,000, https://doi.org/10.3133/sim3394. Database: Joel E. Robinson, and Peter W. Lipman, 2020, Database for the Geologic Map of the Bonanza Caldera Area, Northeastern San Juan Mountains, Colorado: U.S. Geological Survey, https://doi.org/10.5066/P911OL4Q.

Leaf mass per area and leaf water content measurements from field survey in association with NEON AOP survey, East River, CO 2018. A Multiscale Approach to Modeling Carbon and Nitrogen Cycling within a High Elevation Watershed. (ess_dive, 2020)
Leaf area, wet, and dry weights for leaf samples from 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 leaf area and wet and dry weights for leaves from tree and shrub sampling sites, as well as samples for meadow species present within a given sampling area. Associated data packages contain species composition information at the plot level (DOI: 10.15485/1618130), as well as additional biogeochemical, microbial, and geophysical data as they become available. For full documentation, please see associated reference. This package contains zipped folders of all scans that were used for area calculations for both sampling sites (tree/shrub, site_scans.zip) as well as representative samples from a daily sampling area of meadow species that were found in the 1 m plots (meadow_area_scans.zip). It also contains the macro code that was used in ImageJ for processing of the area calculations. Finally, it includes excel files with the area (cm2), wet weight (g), dry weight (g), leaf mass per area (LMA, g/m2), and leaf water content (%) for each set of scans. Related References Chadwick et al., Integrating airborne remote sensing and field campaigns for ecology and Earth system science, In review Chadwick K D ; Grant K ; Henderson A ; Breckheimer I ; Williams C F R ; Falco N ; Chen J ; Henry H ; Khurram A ; Lamb J ; McCormick M ; McOmber H ; Pierce S ; Polussa A ; Hastings Porro M ; Scott A ; Wu Singh H ; Whitney B ; Brodie E ; Carroll R ; Dewey C ; Kueppers L ; Maavara T ; Steltzer H ; Williams K ; Maher K (2020): Locations, metadata, and species cover from field sampling survey associated with NEON AOP survey, East River, CO 2018. Watershed Function SFA. DOI: 10.15485/1618130

Leaf-on 1m Digital Surface Model for the Upper East River Domain - Ian K Breckheimer (s3, 2020)
This is a digital surface model from the 2018 NEON AOP dataset. It represents the height above sea level for objects attached to the ground, such as buildings and trees. This version of the data includes the elevation of the tops of deciduous vegetation, consistent with the data collection interval of July 2018. Users should also cite the source datasets and documentation: 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 Chadwick K D ; Brodrick P ; Grant K ; Henderson A ; Bill M ; Breckheimer I ; Williams C F R ; Goulden T ; Falco N ; McCormick M ; Musinsky J ; Pierce S ; Hastings Porro M ; Scott A ; Brodie E ; Hancher M ; Steltzer H ; Wainwright H ; Maher K W; undefined K M (2020): NEON AOP foliar trait maps, maps of model uncertainty estimates, and conifer map. A Multiscale Approach to Modeling Carbon and Nitrogen Cycling within a High Elevation Watershed. DOI: 10.15485/1618133

RMBL Wilderness Areas - Shannon Sprott (other, 2020)
This data set contains all of the wilderness area boundaries within Gunnison County. The original dataset was downloaded off the Gunnison County GIS website. The data download link goes to the shapefile data format, though this data is available for download off the ArcGIS Online site as a KML, File Geodatabase, and GeoJson file types.

Quality-controlled 1m Digital Elevation Model for the Upper East River Domain - Ian K Breckheimer (s3, 2020)
1m Resolution bare-earth Digital Elevation Model for the Upper East River Derived from 2018 NEON AOP Data. This version has been re-processed to remove artifacts associated with sharp ridges and dense vegetation, and was based on original data from NEON:  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

RMBL County Roads 2019 - Shannon Sprott (other, 2020)
All E911 highways, public and private roads within Gunnison and some of Hinsdale Counties. This data was downloaded directly from the Gunnison County GIS website, and was last updated 09/10/2019. The data download link goes to the shapefile data format, though this data is available for download off the ArcGIS Online site as a KML, File Geodatabase, and GeoJson file types

RMBL County Trails - Shannon Sprott (other, 2020)
This data set includes all trails, bikeways and public paths within Gunnison County. It was created by RMBL GIS and is a compilation of trail data from multiple sources such as the Crested Butte Mountain Bike Association, US Forest Service and Gunnison County. The data download link goes to the shapefile data format, though this data is available for download off the ArcGIS Online site as a KML, File Geodatabase, and GeoJson file types.

Small Sub-watersheds of the Upper East River Domain - Ian K Breckheimer (s3, 2020)
This map represents estimated watersheds for stream segments derived from a hydrologically corrected digital elevation model. The flow lines were derived in GRASS GIS using a single direction algorithm that does not allow channel braiding. Each watershed is identified by a unique integer that matches the stream segment. Stream segments were delineated to drain at least 32000 square meters. Users should also cite the original elevation datasets and documentation: 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

Hydrologically Corrected (cut and burned) 1m Digital Elevation Model for the Upper East River Domain - Ian K Breckheimer (s3, 2020)
This is a hydrologically corrected digital elevation model derived from the 2018 NEON AOP dataset. It represents the height above sea level for impervious objects attached to the ground, such as buildings, but not vegetation. Bridges and culverts have been "cut" to allow flow, and areas of suface water are "burned" into the DEM, and are represented by the minimum elevation of that area of contiguous surface water.

Single-direction Stream Flowlines for the Upper East River Domain - Ian K Breckheimer (s3, 2020)
This map represents estimated stream flowlines from a hydrologically corrected digital elevation model. The lines were derived in GRASS GIS using a single-flow direction algorithm that does not allow channel braiding. Each stream segment is identified by a unique integer.Stream lines were delineated for drainage areas greater than 32000 square meters. Users should also cite the original source datasets and documentation: 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 Chadwick K D ; Brodrick P ; Grant K ; Henderson A ; Bill M ; Breckheimer I ; Williams C F R ; Goulden T ; Falco N ; McCormick M ; Musinsky J ; Pierce S ; Hastings Porro M ; Scott A ; Brodie E ; Hancher M ; Steltzer H ; Wainwright H ; Maher K W; undefined K M (2020): NEON AOP foliar trait maps, maps of model uncertainty estimates, and conifer map. A Multiscale Approach to Modeling Carbon and Nitrogen Cycling within a High Elevation Watershed. DOI: 10.15485/1618133

Data for Lynn et al. “Soil microbes that may accompany climate warming increase alpine plant production” - D. A. Duarte; Jennifer A. Rudgers; J. S. Lynn (other, 2020)
Climate change is causing species with non-overlapping ranges to come in contact, and a key challenge is to predict the consequences of such species re-shuffling. Experiments on plants have focused largely on novel competitive interactions; other species interactions, such as plant-microbe symbioses, while less studied, may also influence plant responses to climate change. In this greenhouse study, we evaluated interactions between soil microbes and alpine-restricted plant species, simulating a warming scenario in which low elevation microbes migrate upslope into the distribution of alpine plants. We examined three alpine grasses from the Rocky Mountains, CO, USA (Poa alpina, Festuca brachyphylla, Elymus scribneri). We used soil inocula from within (resident) or below (novel) the plants' current elevation range and examined responses in plant biomass, plant traits, and fungal colonization of roots. Resident soil inocula from the species' home range decreased biomass to a greater extent than novel soil inocula. The depressed growth in resident soils suggested these soils harbor more carbon-demanding microbes, as plant biomass generally declined with greater fungal colonization of roots, especially in resident soil inocula. Although plant traits did not respond to the provenance of soil inocula, specific leaf area declined and root:shoot ratio increased when soil inocula were sterilized, indicating microbial mediation of plant trait expression. Contrary to current predictions, our findings suggest that if upwardly migrating microbes were to displace current soil microbes, alpine plants may benefit from this warming-induced microbial re-shuffling.

RMBL County Parcels 2019 - Shannon Sprott (other, 2020)
This dataset contains the parcel boundaries with the tax parcel information included from the Gunnison County Assessors and GIS office. It was downloaded directly off the Gunnison County GIS department website. The data download link goes to the shapefile data format, though this data is available for download off the ArcGIS Online site as a KML, File Geodatabase, and GeoJson file types.

RMBL USFS Districts - Shannon Sprott (other, 2020)
These are the US Forest Service designated districts for the Gunnison County area. This dataset was created in 2015 by Rocky Mountain Biological Lab GIS off documents and legal boundaries from the USFS. These districts are broken into 4 different districts: West Zone/Aspen Ranger District (White River National Forest), West Zone/Sopris Ranger District (White River National Forest), Paonia Ranger District (Gunnison National Forest), Gunnison Ranger District (Gunnison-Uncompahgre National Forest). The data download link goes to the shapefile data format, though this data is available for download off the ArcGIS Online site as a KML, File Geodatabase, and GeoJson file types.

Sample collection information and SNP data for Gunnison Sage-grouse across the species range generated in the Molecular Ecology Lab during 2015-2018 - Kevin Oh (other, 2020)
This dataset contains sample collection information and SNP genotypes for populations of Gunnison Sage-grouse across the species' range. This data was collected in order to examine patterns of adaptive genetic variation in Gunnison Sage-grouse. The data is archived in GenBank at the following URL https://www.ncbi.nlm.nih.gov/bioproject/517770.

Sample collection information and whole genome data for Greater and Gunnison Sage-grouse range generated in the Molecular Ecology Lab during 2015-2018 - Kevin Oh (other, 2020)
This dataset contains sample collection information for whole genome sequences of Gunnison and Greater Sage-grouse. These data were collected in order to examine patterns of adaptive genetic variation in Greater and Gunnison Sage-grouse. The data is archived in GenBank at the following URL https://www.ncbi.nlm.nih.gov/bioproject/531321.

RMBL 2020 Current Research sites - Shannon Sprott (other, 2020)
This data set is created and updated yearly based on scientist, researcher, and student GPS mapping throughout the year. All of the current research sites from each summer are combined as polygons in one feature layer. This dataset is for public use and does not contain any private researcher name or project specific information. The data download link goes to the shapefile data format, though this data is available for download off the ArcGIS Online site as a KML, File Geodatabase, and GeoJson file types.

Long-term bee phenology and abundance data at the RMBL, Gothic, Colorado - Inouye B. D.; Inouye; N. Underwood; R. E. Irwin (other, 2020)
Prof. Rebecca (Becky) Irwin has been collecting data on the abundance and timing of bees in permanent sites near the Rocky Mountain Biological Lab (RMBL), Gothic, Colorado, USA, from 2009 to present. During the flight season, we use pan traps and netting every two weeks to estimate bee abundance by catch rate. All solitary bees are collected, pinned, and identified to the lowest taxonomic level possible (>75% of specimens to species). Bumble bees that are netted are identified in the field, marked and released. The dataset consists of >190 bee species from at least 36 genera. The pan trap and netting data are in two separate files. We also collect flowering data at the time of bee collection every two weeks. More detailed flowering data can be found in the Long-term flowering phenology and abundance project at the Open Science Framework (https://osf.io/jt4n5), and long-term weather records are available from the region as well from the RMBL (www.rmbl.org).

Turbulence dissipation rate estimated from Doppler Lidar measurements during LAPSE-RATE (other, 2020)
This dataset includes turbulence dissipation rate estimated from the University of Colorado Windcube v1 lidars and the University of Oklahoma Halo Streamline scanning Doppler Lidar during the 2018 LAPSE-RATE (Lower Atmospheric Profiling Studies at Elevation - a Remotely-piloted Aircraft Team Experiment) field campaign.This campaign took place in the San Luis Valley of Colorado between 14-21 July, 2018. On 14 July, both Windcube lidars were co-located at the Saguache site for intercomparison. WC49 (here named DPLR2) was moved to the Moffat School site late in the day on the 14th, where the Halo Streamline was deployed. Bad or missing data is set to -9999.9 for variable fields.

SnowEx20 Grand Mesa IOP BSU 1 GHz Multi-polarization GPR Raw, Version 1 (other, 2020)

LAPSE-RATE ground-based Doppler lidar datasets from Univ Colorado Boulder (other, 2020)
This dataset includes measurements obtained using the University of Colorado Windcube v1 lidars during the 2018 LAPSE-RATE (Lower Atmospheric Profiling Studies at Elevation - a Remotely-piloted Aircraft Team Experiment) field campaign. This campaign took place in the San Luis Valley of Colorado between 14-21 July, 2018. On 14 July, both lidars were co-located at the Saguache site for intercomparison. WC49 (here named DPLR2) was moved to the Moffat School site late in the day on the 14th. Moffat School data starts on the 15th. Bad or missing data is set to -9999.0 for all fields. The a1 and the a2 datafiles are identical except that the a2 files include beam information (0, 90, 180, or 270) that was omitted from the a1 files.

LAPSE-RATE ground-based Doppler lidar datasets from Univ Colorado Boulder (other, 2020)
This dataset includes measurements obtained using the University of Colorado Windcube v1 lidars during the 2018 LAPSE-RATE (Lower Atmospheric Profiling Studies at Elevation - a Remotely-piloted Aircraft Team Experiment) field campaign. This campaign took place in the San Luis Valley of Colorado between 14-21 July, 2018. On 14 July, both lidars were co-located at the Saguache site for intercomparison. WC49 (here named DPLR2) was moved to the Moffat School site late in the day on the 14th. Moffat School data starts on the 15th. Bad or missing data is set to -9999.0 for all fields. The a1 and the a2 datafiles are identical except that the a2 files include beam information (0, 90, 180, or 270) that was omitted from the a1 files.

LAPSE-RATE ground-based Doppler lidar datasets from Univ Colorado Boulder (other, 2020)
This dataset includes measurements obtained using the University of Colorado Windcube v1 lidars during the 2018 LAPSE-RATE (Lower Atmospheric Profiling Studies at Elevation - a Remotely-piloted Aircraft Team Experiment) field campaign. This campaign took place in the San Luis Valley of Colorado between 14-21 July, 2018. On 14 July, both lidars were co-located at the Saguache site for intercomparison. WC49 (here named DPLR2) was moved to the Moffat School site late in the day on the 14th. Moffat School data starts on the 15th. Bad or missing data is set to -9999.0 for all fields.