Raw soil carbon dioxide, moisture, temperature and micrometeorological data in the East River Watershed, Colorado June 2021-October 2022. (DE-SC0021139)
Abstract
This dataset contains raw data from four tripod stations along an elevation gradient on Snodgrass Mountain in the East River Watershed, CO, USA. Each station contains a datalogger connected to 3 soil Carbon Dioxide CO2 gas probes, 3 soil temperature/moisture sensors and a micrometeorological station. Sensors are scanned every minute, and the 30 minute average is reported. The file snodgrass_soil_ESS.csv contains raw data and a row of column descriptors and units of measurements. No data processing or QA/QC was done on the raw data sets. This research was performed to investigate the ecohydrological linkages of belowground carbon processes in the East River watershed forested communities to better understand how these ecosystems will respond to a changing cold-season moisture input.
- Authors:
-
- Northern Arizona University Center for Ecosystem Science and Communication
- Contributors:
Related Person:
- Northern Arizona University Center for Ecosystem Science and Communication
- Publication Date:
- Research Org.:
- Environmental System Science Data Infrastructure for a Virtual Ecosystem (ESS-DIVE) (United States); Ecohydrological controls on root and microbial respiration in the East River watershed of Colorado
- Sponsoring Org.:
- U.S. DOE > Office of Science > Biological and Environmental Research (BER); Rocky Mountain Biological Laboratory
- Subject:
- 54 ENVIRONMENTAL SCIENCES
- Keywords:
- Soil CO2; Soil Moisture; Soil Temperature; Aspen; Mixed-Conifer; Soil Respiration; EARTH SCIENCE > LAND SURFACE > SOILS; Air temperature; soil temperature; precipitation; Soil CO2 concentration; soil water content; EARTH SCIENCE > LAND SURFACE > SOILS > SOIL MOISTURE/WATER CONTENT; EARTH SCIENCE > LAND SURFACE > SOILS > SOIL TEMPERATURE
- Geolocation:
- 38.94781,-106.9633|38.92084,-106.9633|38.92084,-106.9865|38.94781,-106.9865|38.94781,-106.9633
- OSTI Identifier:
- 1909712
- DOI:
- https://doi.org/10.15485/1909712
- Project Location:
-
Citation Formats
Simonpietri, Austin, Carbone, Mariah, and Richardson, Andrew. Raw soil carbon dioxide, moisture, temperature and micrometeorological data in the East River Watershed, Colorado June 2021-October 2022. (DE-SC0021139). United States: N. p., 2023.
Web. doi:10.15485/1909712.
Simonpietri, Austin, Carbone, Mariah, & Richardson, Andrew. Raw soil carbon dioxide, moisture, temperature and micrometeorological data in the East River Watershed, Colorado June 2021-October 2022. (DE-SC0021139). United States. doi:https://doi.org/10.15485/1909712
Simonpietri, Austin, Carbone, Mariah, and Richardson, Andrew. 2023.
"Raw soil carbon dioxide, moisture, temperature and micrometeorological data in the East River Watershed, Colorado June 2021-October 2022. (DE-SC0021139)". United States. doi:https://doi.org/10.15485/1909712. https://www.osti.gov/servlets/purl/1909712. Pub date:Sun Jan 01 00:00:00 EST 2023
@article{osti_1909712,
title = {Raw soil carbon dioxide, moisture, temperature and micrometeorological data in the East River Watershed, Colorado June 2021-October 2022. (DE-SC0021139)},
author = {Simonpietri, Austin and Carbone, Mariah and Richardson, Andrew},
abstractNote = {This dataset contains raw data from four tripod stations along an elevation gradient on Snodgrass Mountain in the East River Watershed, CO, USA. Each station contains a datalogger connected to 3 soil Carbon Dioxide CO2 gas probes, 3 soil temperature/moisture sensors and a micrometeorological station. Sensors are scanned every minute, and the 30 minute average is reported. The file snodgrass_soil_ESS.csv contains raw data and a row of column descriptors and units of measurements. No data processing or QA/QC was done on the raw data sets. This research was performed to investigate the ecohydrological linkages of belowground carbon processes in the East River watershed forested communities to better understand how these ecosystems will respond to a changing cold-season moisture input.},
doi = {10.15485/1909712},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Sun Jan 01 00:00:00 EST 2023},
month = {Sun Jan 01 00:00:00 EST 2023}
}